Patent Grant
11176345
Fingerprint sensors have become ubiquitous in mobile devices as well as other applications for authenticating a user's identity. They provide a fast and convenient way for the user to unlock a device, provide authentication for payments, etc. Current fingerprint sensors are typically area sensors that obtain a two-dimensional image of the user's finger area presented to the sensor. Different technologies can be used to image the finger such as capacitive, ultrasound, and optical sensing. Once an image is obtained, that image is processed by a matcher to extract features and to compare against stored images to authenticate the user. As such, accuracy of captured images is essential to the performance of image matching for user authentication.
The accompanying drawings, which are incorporated in and form a part of the Description of Embodiments, illustrate various embodiments of the subject matter and, together with the Description of Embodiments, serve to explain principles of the subject matter discussed below. Unless specifically noted, the drawings referred to in this Brief Description of Drawings should be understood as not being drawn to scale. Herein, like items are labeled with like item numbers.
The following Description of Embodiments is merely provided by way of example and not of limitation. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding background or in the following Description of Embodiments.
Reference will now be made in detail to various embodiments of the subject matter, examples of which are illustrated in the accompanying drawings. While various embodiments are discussed herein, it will be understood that they are not intended to limit to these embodiments. On the contrary, the presented embodiments are intended to cover alternatives, modifications and equivalents, which may be included within the spirit and scope the various embodiments as defined by the appended claims. Furthermore, in this Description of Embodiments, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present subject matter. However, embodiments may be practiced without these specific details. In other instances, well known methods, procedures, components, and circuits have not been described in detail as not to unnecessarily obscure aspects of the described embodiments.
Some portions of the detailed descriptions which follow are presented in terms of procedures, logic blocks, processing and other symbolic representations of operations on data within an electrical device. These descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. In the present application, a procedure, logic block, process, or the like, is conceived to be one or more self-consistent procedures or instructions leading to a desired result. The procedures are those requiring physical manipulations of physical quantities. Usually, although not necessarily, these quantities take the form of acoustic (e.g., ultrasonic) signals capable of being transmitted and received by an electronic device and/or electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated in an electrical device.
It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussions, it is appreciated that throughout the description of embodiments, discussions utilizing terms such as “performing,” “controlling,” “capturing,” “activating,” “generating,” “combining,” “transmitting,” “receiving,” “repeating,” “measuring,” “selecting,” “determining,” or the like, refer to the actions and processes of an electronic device such as an electrical device.
Embodiments described herein may be discussed in the general context of processor-executable instructions residing on some form of non-transitory processor-readable medium, such as program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or distributed as desired in various embodiments.
In the figures, a single block may be described as performing a function or functions; however, in actual practice, the function or functions performed by that block may be performed in a single component or across multiple components, and/or may be performed using hardware, using software, or using a combination of hardware and software. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, logic, circuits, and steps have been described generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure. Also, the example fingerprint sensing system and/or mobile electronic device described herein may include components other than those shown, including well-known components.
Various techniques described herein may be implemented in hardware, software, firmware, or any combination thereof, unless specifically described as being implemented in a specific manner. Any features described as modules or components may also be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques may be realized at least in part by a non-transitory processor-readable storage medium comprising instructions that, when executed, perform one or more of the methods described herein. The non-transitory processor-readable data storage medium may form part of a computer program product, which may include packaging materials.
The non-transitory processor-readable storage medium may comprise random access memory (RAM) such as synchronous dynamic random access memory (SDRAM), read only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), FLASH memory, other known storage media, and the like. The techniques additionally, or alternatively, may be realized at least in part by a processor-readable communication medium that carries or communicates code in the form of instructions or data structures and that can be accessed, read, and/or executed by a computer or other processor.
Various embodiments described herein may be executed by one or more processors, such as one or more motion processing units (MPUs), sensor processing units (SPUs), host processor(s) or core(s) thereof, digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), application specific instruction set processors (ASIPs), field programmable gate arrays (FPGAs), a programmable logic controller (PLC), a complex programmable logic device (CPLD), a discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein, or other equivalent integrated or discrete logic circuitry. The term “processor,” as used herein may refer to any of the foregoing structures or any other structure suitable for implementation of the techniques described herein. As it employed in the subject specification, the term “processor” can refer to substantially any computing processing unit or device comprising, but not limited to comprising, single-core processors; single-processors with software multithread execution capability; multi-core processors; multi-core processors with software multithread execution capability; multi-core processors with hardware multithread technology; parallel platforms; and parallel platforms with distributed shared memory. Moreover, processors can exploit nano-scale architectures such as, but not limited to, molecular and quantum-dot based transistors, switches and gates, in order to optimize space usage or enhance performance of user equipment. A processor may also be implemented as a combination of computing processing units.
In addition, in some aspects, the functionality described herein may be provided within dedicated software modules or hardware modules configured as described herein. Also, the techniques could be fully implemented in one or more circuits or logic elements. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of an SPU/MPU and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with an SPU core, MPU core, or any other such configuration.
Discussion begins with a description of an example piezoelectric micromachined ultrasonic transducer (PMUT), in accordance with various embodiments. Example arrays including PMUT devices are then described. Example operations of example arrays of ultrasonic transducers (e.g., PMUT devices) are then further described, including the use of multiple PMUT devices to form a beam for capturing a pixel. Examples of the ultrasonic fingerprint sensors having contact layers with non-uniform thickness are then described. Examples of accounting for non-uniform thickness of a contact layer in an ultrasonic fingerprint sensor are then described.
Fingerprint sensors, in accordance with the described embodiments, are used for capturing fingerprint images that are used for performing fingerprint authentication. As the use of fingerprint sensors proliferates, there is a desire to include fingerprint sensors in devices having varying form factors. In many potential use cases, an ultrasonic fingerprint sensor that is substantially flat is overlaid with a contact layer that is not flat (e.g., has a curved profile, rounded edges, etc.), thus having a varying thickness. This variation in material thickness results in a skewing or redirection of the return signal level (e.g., reflected ultrasonic beam), which can result in artifacts related to contact layer curvature and acoustic wavelength. Moreover, a contact layer having a non-uniform thickness will cause an interference pattern to be generated in a captured image due to the difference in interference between the transmitted and received ultrasonic waves. In some locations, the transmitted and received ultrasonic waves will be in phase, while in other locations the transmitted and received ultrasonic waves will be out of phase, and gradients in between, causing an interference pattern that may obscure the underlying image being captured (e.g., a fingerprint). Embodiments described herein account for the interference pattern caused by the varying thickness of the contact layer.
Embodiments described herein provide a sensor device including a two-dimensional array of ultrasonic transducers, wherein the two-dimensional array of ultrasonic transducers is substantially flat, a contact layer having a non-uniform thickness overlying the two-dimensional array of ultrasonic transducers, and an array controller configured to control activation of ultrasonic transducers during an imaging operation for imaging a plurality of pixels. During the imaging operation, the array controller is configured to control a transmission frequency of activated ultrasonic transducers during the imaging operation, wherein a plurality of transmission frequencies are used during the imaging operation to account for an impact of an interference pattern caused by the non-uniform thickness of the contact layer, and is configured to capture at least one fingerprint image using the plurality of transmission frequencies.
At least one fingerprint image is captured using the plurality of transmission frequencies. In one embodiment, a plurality of fingerprint images is captured using the plurality of transmission frequencies. In one embodiment, the plurality of transmission frequencies operate to cancel out the interference pattern of the plurality of fingerprint images. In another embodiment, a plurality of portions of a fingerprint image is captured using the plurality of transmission frequencies.
The captured at least one fingerprint image is combined to generate an output fingerprint image. In one embodiment, the plurality of fingerprint images is combined into a single output fingerprint image, wherein the single output fingerprint image reduces the impact of the interference pattern caused by the non-uniform thickness of the contact layer. In one embodiment, the plurality of fingerprint images is combined into a single output fingerprint image by averaging the plurality of fingerprint images. In another embodiment, the plurality of fingerprint images is combined into a single output fingerprint image by using convolution.
In another embodiment, the plurality of portions of the fingerprint image is combined into a single output fingerprint image. In one embodiment, the plurality of transmission frequencies provide constructive interference for corresponding portions of the plurality of portions of the fingerprint image during the imaging operation. In one embodiment, the portions of the plurality of portions include a plurality of pixels. In another embodiment, the portions of the plurality of portions include single pixels.
In other embodiments, an image is captured at an ultrasonic sensor using a temperature to control the transmission frequency, according to embodiments. An imaging operation is performed at a two-dimensional array of ultrasonic transducers of the ultrasonic sensor to generate a plurality of pixels, wherein the ultrasonic sensor has a contact layer having a non-uniform thickness overlying the two-dimensional array of ultrasonic transducers and wherein the two-dimensional array of ultrasonic transducers is substantially flat. A temperature of the ultrasonic sensor is determined. A transmission frequency of activated ultrasonic transducers is controlled during the imaging operation, wherein the transmission frequency is controlled based on the temperature of the ultrasonic sensor. The transmission frequency is selected to generate a constant interference pattern across all temperatures. At least one fingerprint image is captured using the transmission frequency. An interference pattern correction is applied to the fingerprint image to generate the output fingerprint image.
Systems and methods disclosed herein, in one or more aspects provide efficient structures for an acoustic transducer (e.g., a piezoelectric micromachined actuated transducer or PMUT). One or more embodiments are now described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the various embodiments. It may be evident, however, that the various embodiments can be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate describing the embodiments in additional detail.
As used in this application, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. That is, unless specified otherwise, or clear from context, “X employs A or B” is intended to mean any of the natural inclusive permutations. That is, if X employs A; X employs B; or X employs both A and B, then “X employs A or B” is satisfied under any of the foregoing instances. In addition, the articles “a” and “an” as used in this application and the appended claims should generally be construed to mean “one or more” unless specified otherwise or clear from context to be directed to a singular form. In addition, the word “coupled” is used herein to mean direct or indirect electrical or mechanical coupling. In addition, the word “example” is used herein to mean serving as an example, instance, or illustration.
Embodiments described herein provide ultrasonic fingerprint sensors having non-uniform contact layers. It should be appreciated that different types of ultrasonic fingerprint sensors having different architectures may be utilized herein. For instance, some architectures include an array of ultrasonic transducers (e.g., PMUTs), embodiments of which are described herein. In some embodiments, the ultrasonic transducers may be bulk piezo actuator elements, e.g., lead zirconate titanate (PZT). Other architectures may utilize a film-based design. Although embodiments are described herein with respect to an array of ultrasonic transducers, the methods and techniques may be applied to other ultrasonic sensing architectures where the control of the operating parameters of different segments of the sensors can be adjusted separately to correct for the non-uniform contact surface. The embodiments described herein are with respect to sensors with a non-uniform contact layer, but the techniques and principles discussed may in some situations also be used to improve performance of sensors with uniform contact surfaces.
In one embodiment, both edge support 102 and interior support 104 are attached to a substrate 140. In various embodiments, substrate 140 may include at least one of, and without limitation, silicon or silicon nitride. It should be appreciated that substrate 140 may include electrical wirings and connection, such as aluminum or copper. In one embodiment, substrate 140 includes a CMOS logic wafer bonded to edge support 102 and interior support 104. In one embodiment, the membrane 120 comprises multiple layers. In an example embodiment, the membrane 120 includes lower electrode 106, piezoelectric layer 110, and upper electrode 108, where lower electrode 106 and upper electrode 108 are coupled to opposing sides of piezoelectric layer 110. As shown, lower electrode 106 is coupled to a lower surface of piezoelectric layer 110 and upper electrode 108 is coupled to an upper surface of piezoelectric layer 110. It should be appreciated that, in various embodiments, PMUT device 100 is a microelectromechanical (MEMS) device.
In one embodiment, membrane 120 also includes a mechanical support layer 112 (e.g., stiffening layer) to mechanically stiffen the layers. In various embodiments, mechanical support layer 112 may include at least one of, and without limitation, silicon, silicon oxide, silicon nitride, aluminum, molybdenum, titanium, etc. In one embodiment, PMUT device 100 also includes an acoustic coupling layer 114 above membrane 120 for supporting transmission of acoustic signals. It should be appreciated that acoustic coupling layer can include air, liquid, gel-like materials, epoxy, or other materials for supporting transmission of acoustic signals. In one embodiment, PMUT device 100 also includes platen layer 116 above acoustic coupling layer 114 for containing acoustic coupling layer 114 and providing a contact surface for a finger or other sensed object with PMUT device 100. It should be appreciated that, in various embodiments, acoustic coupling layer 114 provides a contact surface, such that platen layer 116 is optional. Moreover, it should be appreciated that acoustic coupling layer 114 and/or platen layer 116 may be included with or used in conjunction with multiple PMUT devices. For example, an array of PMUT devices may be coupled with a single acoustic coupling layer 114 and/or platen layer 116. It should be appreciated that platen layer 116 can include one or more materials, including without limitation: glass, plastic, metal (e.g., aluminum, titanium, stainless steel), etc. In some embodiments, platen 116 is a display device (e.g., an organic light emitting diode (OLED) display device) overlying one or more PMUT devices. In such an embodiment, platen 116 includes multiple layers of the display device.
The described PMUT device 100 can be used with almost any electrical device that converts a pressure wave into mechanical vibrations and/or electrical signals. In one aspect, the PMUT device 100 can comprise an acoustic sensing element (e.g., a piezoelectric element) that generates and senses ultrasonic sound waves. An object in a path of the generated sound waves can create a disturbance (e.g., changes in frequency or phase, reflection signal, echoes, etc.) that can then be sensed. The interference can be analyzed to determine physical parameters such as (but not limited to) distance, density and/or speed of the object. As an example, the PMUT device 100 can be utilized in various applications, such as, but not limited to, fingerprint or physiologic sensors suitable for wireless devices, industrial systems, automotive systems, robotics, telecommunications, security, medical devices, etc. For example, the PMUT device 100 can be part of a sensor array comprising a plurality of ultrasonic transducers deposited on a wafer, along with various logic, control and communication electronics. A sensor array may comprise homogenous or identical PMUT devices 100, or a number of different or heterogonous device structures.
In various embodiments, the PMUT device 100 employs a piezoelectric layer 110, comprised of materials such as, but not limited to, aluminum nitride (AlN), scandium doped aluminum nitride (ScAlN), lead zirconate titanate (PZT), quartz, polyvinylidene fluoride (PVDF), and/or zinc oxide, to facilitate both acoustic signal production and sensing. The piezoelectric layer 110 can generate electric charges under mechanical stress and conversely experience a mechanical strain in the presence of an electric field. For example, the piezoelectric layer 110 can sense mechanical vibrations caused by an ultrasonic beam and produce an electrical charge at the frequency (e.g., ultrasonic frequency) of the vibrations. Additionally, the piezoelectric layer 110 can generate an ultrasonic wave by vibrating in an oscillatory fashion that might be at the same frequency (e.g., ultrasonic frequency) as an input current generated by an alternating current (AC) voltage applied across the piezoelectric layer 110. It should be appreciated that the piezoelectric layer 110 can include almost any material (or combination of materials) that exhibits piezoelectric properties, such that the structure of the material does not have a center of symmetry and a tensile or compressive stress applied to the material alters the separation between positive and negative charge sites in a cell causing a polarization at the surface of the material. The polarization is directly proportional to the applied stress and is direction dependent so that compressive and tensile stresses results in electric fields of opposite polarizations.
Further, the PMUT device 100 comprises electrodes 106 and 108 that supply and/or collect the electrical charge to/from the piezoelectric layer 110. It should be appreciated that electrodes 106 and 108 can be continuous and/or patterned electrodes (e.g., in a continuous layer and/or a patterned layer). For example, as illustrated, electrode 106 is a patterned electrode and electrode 108 is a continuous electrode. As an example, electrodes 106 and 108 can be comprised of almost any metal layers, such as, but not limited to, Aluminum (Al)/Titanium (Ti), Molybdenum (Mo), etc., which are coupled with and on opposing sides of the piezoelectric layer 110. In one embodiment, PMUT device also includes a third electrode, as illustrated in
According to an embodiment, the acoustic impedance of acoustic coupling layer 114 is selected to be similar to the acoustic impedance of the platen layer 116, such that the acoustic wave is efficiently propagated to/from the membrane 120 through acoustic coupling layer 114 and platen layer 116. As an example, the platen layer 116 can comprise various materials having an acoustic impedance in the range between 0.8 to 4 MRayl, such as, but not limited to, plastic, resin, rubber, Teflon, epoxy, etc. In another example, the platen layer 116 can comprise various materials having a high acoustic impedance (e.g., an acoustic impendence greater than 10 MRayl), such as, but not limited to, glass, aluminum-based alloys, sapphire, etc. Typically, the platen layer 116 can be selected based on an application of the sensor. For instance, in fingerprinting applications, platen layer 116 can have an acoustic impedance that matches (e.g., exactly or approximately) the acoustic impedance of human skin (e.g., 1.6×106Rayl). Further, in one aspect, the platen layer 116 can further include a thin layer of anti-scratch material. In various embodiments, the anti-scratch layer of the platen layer 116 is less than the wavelength of the acoustic wave that is to be generated and/or sensed to provide minimum interference during propagation of the acoustic wave. As an example, the anti-scratch layer can comprise various hard and scratch-resistant materials (e.g., having a Mohs hardness of over 7 on the Mohs scale), such as, but not limited to sapphire, glass, MN, Titanium nitride (TiN), Silicon carbide (SiC), diamond, etc. As an example, PMUT device 100 can operate at 20 MHz and accordingly, the wavelength of the acoustic wave propagating through the acoustic coupling layer 114 and platen layer 116 can be 70-150 microns. In this example scenario, insertion loss can be reduced and acoustic wave propagation efficiency can be improved by utilizing an anti-scratch layer having a thickness of 1 micron and the platen layer 116 as a whole having a thickness of 1-2 millimeters. It is noted that the term “anti-scratch material” as used herein relates to a material that is resistant to scratches and/or scratch-proof and provides substantial protection against scratch marks.
In accordance with various embodiments, the PMUT device 100 can include metal layers (e.g., Aluminum (Al)/Titanium (Ti), Molybdenum (Mo), etc.) patterned to form electrode 106 in particular shapes (e.g., ring, circle, square, octagon, hexagon, etc.) that are defined in-plane with the membrane 120. Electrodes can be placed at a maximum strain area of the membrane 120 or placed at close to either or both the surrounding edge support 102 and interior support 104. Furthermore, in one example, electrode 108 can be formed as a continuous layer providing a ground plane in contact with mechanical support layer 112, which can be formed from silicon or other suitable mechanical stiffening material. In still other embodiments, the electrode 106 can be routed along the interior support 104, advantageously reducing parasitic capacitance as compared to routing along the edge support 102.
For example, when actuation voltage is applied to the electrodes, the membrane 120 will deform and move out of plane. The motion then pushes the acoustic coupling layer 114 it is in contact with and an acoustic (ultrasonic) wave is generated. Oftentimes, vacuum is present inside the cavity 130 and therefore damping contributed from the media within the cavity 130 can be ignored. However, the acoustic coupling layer 114 on the other side of the membrane 120 can substantially change the damping of the PMUT device 100. For example, a quality factor greater than 20 can be observed when the PMUT device 100 is operating in air with atmosphere pressure (e.g., acoustic coupling layer 114 is air) and can decrease lower than 2 if the PMUT device 100 is operating in water (e.g., acoustic coupling layer 114 is water).
In operation, during transmission, selected sets of PMUT devices in the two-dimensional array can transmit an acoustic signal (e.g., a short ultrasonic pulse) and during sensing, the set of active PMUT devices in the two-dimensional array can detect an interference of the acoustic signal with an object (in the path of the acoustic wave). The received interference signal (e.g., generated based on reflections, echoes, etc. of the acoustic signal from the object) can then be analyzed. As an example, an image of the object, a distance of the object from the sensing component, a density of the object, a motion of the object, etc., can all be determined based on comparing a frequency and/or phase of the interference signal with a frequency and/or phase of the acoustic signal. Moreover, results generated can be further analyzed or presented to a user via a display device (not shown).
In one embodiment, fingerprint sensor 415 includes processor 460 for performing the pixel capture, where pixel capture is performed using subsets of ultrasonic transducers (e.g., PMUTs) of fingerprint sensor 415. In some embodiments, pixel capture for groups of pixels is handled the same, such that the groups of pixels utilize same imaging operations (e.g., utilize a same relative activation of the first subset of ultrasonic transducers and the second subset of ultrasonic transducers according to a same local angle). In other embodiments, processor 460 can perform at least some signal analysis, e.g., thresholding, to determine whether an object has interacted with fingerprint sensor 415. In other embodiments, processor 460 can analyze captured pixels and determine whether the object has characteristics of finger, e.g., a pattern resembling the ridge/valley pattern of a fingerprint. In other embodiments, processor 460 can capture an image of the fingerprint and forward it to a processor of system circuitry for further analysis.
In accordance with embodiments, processor 460 is configured to control the activation of the subsets of ultrasonic transducers to generate an ultrasonic signal, also referred to herein as an ultrasonic beam. Using multiple ultrasonic transducers, some of which are time delayed with respect to other ultrasonic transducers, embodiments described herein provide for focusing a transmit beam (e.g., forming a beam) of an ultrasonic signal to a desired point, allowing for high resolution sensing of a fingerprint, or other object. For instance, transmitting an ultrasonic signal from multiple PMUTs, where some PMUTs transmit at a time delay relative to other PMUTs, provides for focusing the ultrasonic beam to a contact point of a fingerprint sensing system (e.g., a top of a platen layer) for sensing a high resolution image of a pixel associated with the transmitting PMUTs. In some embodiments, the activation includes transmitting ultrasonic signals from a first group of ultrasonic transducers of the plurality of ultrasonic transducers, wherein at least some ultrasonic transducers of the first group of ultrasonic transducers are phase delayed with respect to other ultrasonic transducers of the first group of ultrasonic transducers, the first group of ultrasonic transducers for forming a focused ultrasonic beam. The activation also includes receiving reflected ultrasonic signals at a second group of ultrasonic transducers of the plurality of ultrasonic transducers
While the embodiment of
In some embodiments, fingerprint sensor also includes temperature sensor 480 which includes circuitry for temperature measurement. In an embodiment, temperature sensor 480 is an integrated silicon thermistor that can be incorporated in the manufacturing process with array 450. In another embodiment, temperature sensor 480 is a MEMS structure different from array 450 but compatible with the manufacturing process for PMUT array 450. In another embodiment, temperature sensor 480 is comprised within a CMOS control layer of the array 450. It should be appreciated that temperature sensor 480 may be any other type of sensor for determining a temperature of ultrasonic sensor 415.
Fingerprint sensors are used in electronic devices for user authentication, such as mobile electronic devices, building locks, automobile locks, etc. In many situations, the surface area of the fingerprint sensor needs to be as flat and as uniform as possible in order to obtain a good fingerprint. However, in some situation it may be desirable to have a non-flat or non-uniform fingerprint surface. For example, when a fingerprint sensor is mounted on the back of a mobile phone, a concave form or structured surface may help guide the user's finger to the correct position on the FP sensor. In other situations, the design employs a non-flat form factor, such as a convex button, a rounded door knob or automobile handle. Some designs may require a smooth surface, while other designs may require a rough or textured surface. In further situations, the fingerprint sensor may be integrated in a wearable device, e.g., a smart watch, either on the face of the watch (e.g., behind the display), or on the side of the body. While in the former placement the surface can be relatively flat, in the latter placement the sensor surface may have a small radius of curvature. In general, the smaller the device, or section of the device, where the sensor is integrated, the smaller the radius of curvature, i.e., the more curved the surface is.
Currently, there are different technologies employed by fingerprint sensors for obtaining a fingerprint, including ultrasonic sensing, capacitive sensing, and optical sensing. For instance, for capacitive sensing and optical sensing to perform properly, the sensing layer must be parallel with the contact layer. Otherwise, the signals received may be distorted in a way that precludes proper imaging. In particular, for a capacitive or optical fingerprint sensor to image through a layer of , the capacitive or optical fingerprint sensor would be required to be specially manufactured to conform to the non-uniform surface. However, the tailored manufacture of fingerprint sensors is a costly endeavor, impacting the adoption of such tailored fingerprint sensors within commodity devices.
Embodiments described herein provide an ultrasonic fingerprint sensor comprising a substantially flat two-dimensional array of ultrasonic transducers and a contact layer of non-uniform thickness overlying the two-dimensional array, where the imaging operation is performed through the contact layer of non-uniform thickness. As used herein, the term “substantially” means mostly, primarily, or completely. In particular, the ultrasonic sensor described herein can operate using a two-dimensional array of ultrasonic transducers that is capable of sensing through a contact layer of uniform or non-uniform thickness without having to modify the two-dimensional array of ultrasonic transducers. Embodiments provided herein control the operating parameters of the ultrasonic fingerprint sensor to correct for the non-uniform thickness of the contact layer, generating an image. Although embodiments are described with respect to an array of ultrasonic transducers, the methods and techniques may be applied to other ultrasound sensing architectures where the control of the operating parameters of different segments of the sensors can be adjusted separately to correct for the non-uniform thickness of the contact layer. As utilized herein, a contact layer of non-uniform thickness is non-uniform with respect to the shape (e.g., non-flat) of at least a portion of the contact layer.
In some embodiments, an acoustic coupling layer, and/or other layers such as display devices, (not shown) may be used between sensing layer 520 and contact layer 530 onto which the user puts his or her finger. It should be appreciated that in some embodiments, contact layer 530 and the acoustic coupling layer are a single layer. It should be further appreciated that ultrasonic fingerprint sensor 500 may include other layers, such as bonding layers and laminate layers, and is not intended to be limited to the specific layers shown. In other embodiments, an ultrasonic fingerprint sensor including separate signal transmission and signal detection layers may be used (e.g., within sensing layer 520).
In an ultrasonic fingerprint sensor 500, the acoustic waves travel from the sensing layer 520 through contact layer 530 to contact surface 540, interact with the object on the surface (e.g., a finger), and may then be reflected back to the sensing layer 520, thereby again traversing the contact layer 530. The time from the emission of the waves to the detection of the waves is the time-of-flight (ToF) and depends on the acoustic properties and thicknesses of the contact layer and/or acoustic coupling layer. Due to the varying thickness of contact layer 530 at the edge regions of contact layer 530 (indicated by box 535), ultrasonic beams sent from different locations at sensing layer 520 would result in ToF variations. The ToF variations result in interference patterns, as will be describe below in accordance with
Due to the varying thickness of contact layer 560, ultrasonic beams sent from different locations at sensing layer 520 would result in ToF variations, as the path traversed by the ultrasonic beams would vary across the contact layer. In some embodiments, in order to select the signal of interest, e.g., the signal from waves directly reflected from the object on the surface, a measurement window is used.
Due to the varying thickness of contact layer 590, ultrasonic beams sent from different locations at sensing layer 520 would result in ToF variations, as the path traversed by the ultrasonic beams would vary across the contact layer. In some embodiments, in order to select the signal of interest, e.g., the signal from waves directly reflected from the object on the surface, a measurement window is used.
In an example adaptive ToF method, first the optimal ToF to obtain the desired performance is determined for different ultrasonic transducers or different sections of the sensor. Next, a ToF map, ToF listing, or ToF index is created which links the optimum TOF to the different transducers and or segments of the sensor. The TOF map, listing, or index is then used to control the measurement window setting for the different transducers/pixels. The linking may be based on the location of the transducers. For example, a ToF map can be created, where groups of transducers having ToF values within a range are created, allowing for grouped control of the measurement windows for each group. When the ToF information is used to control the measurement window, in general the timing of the transmission of the ultrasonic waves from the different transducers or different section is not adapted. In other embodiments, instead of controlling the measurement window, the transmission timing of the ultrasonic waves may be adapted to correct for the non-uniform contact surface.
Once the ToF has been determined and stored, it may be applied to determine the correct operational settings of the measurement windows for the respective subsets of transducers. Regular updates of the ToF map may be performed to make sure the optimum ToF is always available. The update may be regularly in time, or may be triggered by certain events or operational conditions, such as e.g., high motion or acceleration, mechanical shock, (fast) temperature change, extreme temperatures, etc.
In some embodiments, each ultrasonic transducer or group of ultrasonic transducers may be controlled using a determined optimum ToF, where the measurement window is shifted in time according to the optimum ToF. The width of the measurement window may be adapted to the received signal and the variation in the ToF over the selected transducers. The larger the number of transducers that are combined, the higher the possibility that there is a variation of the ToF, and therefore the wider/longer the size of the integration window. A distribution of the optimum ToF values may be determined, and the applied setting may be chosen to comprise a predefined portion or percentage of the distribution. In one embodiment, only a single measurement window size is used, and the ToF investigation is used to determine what the variation in ToF across the sensor surface is, and then the window size is adapted accordingly to capture the desired signal or depending on the ToF distribution.
In some architectures, the measurement window may not be changeable or adaptable for individual transducers, and therefore in some embodiments the measurement window may be divided in a number of sub-windows each having a certain ToF range. Then, based on the optimum ToF for a certain transducer or set of transducers, one or more of the sub-windows are selected corresponding to the optimal ToF. For example, in some architectures, where control of the transducers is collective, in order to capture signals for the entire array of the ultrasonic sensor, the measurement window must be big enough to capture signals over the entire ToF range. In other architectures, where transducers are controllable at a more granular level (e.g., grouped control or individual control), the measurement windows for groups of transducers or individual transducers can be tuned according to the ToF range for the groups of transducers or individual transducers. It should be appreciated that there is a tradeoff between the granular control of transducers and the number of distinct measurement windows. For instance, granular control provides higher quality measurement of received signals, but requires more complicated control mechanisms (e.g., driving circuit, routing, etc.) and might result in higher power consumption. Moreover, it should be appreciated that an ultrasonic fingerprint sensor capable of granular control of transducers utilize the granular control during operations requiring high degrees of precision, while using collective control of the transducers during operations that do not require high degrees of precision.
In the discussion above, the measurements window is varied to correct for the difference in time-of-flight. In alternative embodiments, the measurement window may be constant but the transmission timing may be adapted for the different pixels, so that even with a different ToF, the signal of interest still is measured within the static measurement window. In some embodiments, the transmission timing and the measurement window are both adapted to correct for the differences in ToF. In such embodiments, the ToF map is used to control the transmission of signals from different groups of transducers or individual transducers, such that signals might be transmitted at different times, but are received within a constant measurement window.
The various embodiments described herein may be applied to an ultrasonic fingerprint sensor, where the contact layer is non-uniform. The surface may need to have a certain amount of roughness or variation in depth or thickness, before advantages of the techniques disclosure here become of significant importance. For many applications, if the depth/thickness variations are very small, for example, only a few micrometers, the advantage of applying these techniques may be minor. However, in some applications where high precision is required (e.g. banking applications, high security application, etc.), even the small depth/angle variations are of importance. For example, operation of the ultrasonic fingerprint sensor can be adaptive and use a higher precision mode (e.g., more granular control of transducers) when high precision is required, and use a lower precision mode (e.g., collective control of transducers) during normal operation. The application of the high precision mode may also depend on the available resources and may not be applied when few power and/or computation resources are available. In devices where the device is designed such that the user can feel where the fingerprint sensor is positioned, a certain depth, thickness, or angle variation is required so that the user can actually feel the fingerprint sensor. In these use cases, the depth, thickness, or angle variation is generally more than 100 micrometers, and often more than 200-300 micrometers. These depth, thickness, or angle variations typically benefit from the application of the described embodiments in order to improve the performance of the ultrasonic fingerprint sensor. The discussion of depth, thickness, and angle variations relates to the distance between the non-flat surface of the contact layer and the generally flat surface of the sensing layer or substrate layer, as shown in the figures. If the ultrasonic fingerprint sensor and the contact surface are not parallel, the described embodiments can be used to correct for the ToF differences.
As illustrated in
For example, as illustrated, ultrasonic signal 650 is generated at such a position and frequency that the incident wave (e.g., transmitted ultrasonic beam) and the reflected wave (e.g., received ultrasonic beam) are in phase and result in constructive interference (e.g., resultant wave) that amplifies the received signal strength of ultrasonic signal 650. Ultrasonic signal 660 is generated at such a position and frequency that the incident wave (e.g., transmitted ultrasonic beam) and the reflected wave (e.g., received ultrasonic beam) are out of phase and result in destructive interference (e.g., resultant wave) that weakens the received signal strength of ultrasonic signal 660. As image capture is performed across ultrasonic sensor 610, interference pattern 680 is generated within image 670, where interference pattern 680 of image 670 illustrates an example of the varying signal strength intensity across image 670. Interference pattern 680 can be dominant over the underlying captured fingerprint (e.g., fingerprint ridge/valley features), thereby obfuscating or otherwise impacting fingerprint quality of the underlying captured fingerprint. It should be appreciated that interference pattern 680 will vary with respect to the transmission frequency of ultrasonic signals 650 and 660, in that the locations of constructive and destructive interference will vary, but that image 670, regardless of frequency, will include an interference pattern 680 (e.g., as long as the thickness variation is greater than the acoustic wavelength in the contact layer material). The interference pattern also depends on the acoustic characteristics of contact layer 630, such as the speed of sound in the material of contact layer 630. Furthermore, the acoustic characteristics may depend on external factors such as e.g. temperature. As a consequence, interference pattern 680 may also vary with temperature.
Embodiments described herein provide a sensor device including a two-dimensional array of ultrasonic transducers, wherein the two-dimensional array of ultrasonic transducers is substantially flat, and a contact layer having a non-uniform thickness overlying the two-dimensional array of ultrasonic transducers, and methods for using such a device, to account for an interference pattern of a captured image caused by the non-uniform thickness of the contact layer. An imaging operation at an ultrasonic sensor is performed, where a transmission frequency of the activated ultrasonic transducers is controlled during the imaging operation. A plurality of transmission frequencies is used during the imaging operation to account for an impact of an interference pattern caused by the non-uniform thickness of the contact layer.
In one embodiment, a plurality of images is captured using a plurality of transmission frequencies, where images of the plurality of images are captured at different transmission frequencies. The plurality of images captured is combined into a single output image, wherein the single output image reduces the impact of the interference pattern caused by the non-uniform thickness of the contact layer. It should be appreciated that changing the transmission frequency may also result in changing the ToF and beamforming pattern as well, as these settings are dependent on local thickness to focus a point of reflection on contact surface.
It should be appreciated that the combination of multiple images captured at different transmission frequencies can use any number of fingerprint images captured at different transmission frequencies, and that any transmission frequency can be used, and is not limited to the illustrated embodiment. It should be appreciated that the number of images and frequencies used can be design specific, and based on the actual non-uniform thickness of the contact layer of the ultrasonic sensor, and can be experimentally determined (e.g., during design and/or calibration). Furthermore, the number of images and frequencies used may also depend on the required accuracy or the permitted latency of the capturing process (which may depends on the application). The frequencies are selected to provide an optimum correction of the interference pattern. The (number of) frequencies may be determined in calibration process. The sensor may run a calibration procedure to verify a plurality of frequency combinations and quantify the correction quality. The calibration procedure may be done when no finger is present on the sensor.
As illustrated, fingerprint images 710, 720, 730, 740, 750, and 760 are combined to reduce, minimize, or cancel out the impact of the interference pattern caused by the non-uniform thickness of the contact layer. In one embodiment, fingerprint images 710, 720, 730, 740, 750, and 760 are combined by averaging fingerprint images 710, 720, 730, 740, 750, and 760 into a single output image. In the averaging, different weights may be applied to different images to account for differences in signal level and background level. In another embodiment, fingerprint images 710, 720, 730, 740, 750, and 760 are combined using convolution of fingerprint images 710, 720, 730, 740, 750, and 760 to generate a single output image. In some embodiments, only portions of images 710, 720, 730, 740, 750, and 760 exhibiting interference (e.g., above an interference threshold) are combined.
In one embodiment, a plurality of portions of an image is captured using the plurality of transmission frequencies, where some portions are captured at different transmission frequencies. The transmission frequencies of the portions are selected based on the thickness of contact layer 630 associated with the portions and the acoustic properties of the contact layer material, such as speed of sound. The plurality of portions captured is combined into a single output image, wherein the single output image reduces the impact of the interference pattern caused by the non-uniform thickness of the contact layer. It should be appreciated that each portion may have ToF and beamforming settings corresponding to the transmission frequency of the portion.
Graph 800 illustrates that the maximum and minimum signal strength varies according to frequency and contact layer thickness. Using this information, an ultrasonic sensor can be controlled to capture different portions of an image using different transmission frequencies, and then combined into a single output image that accounts for the interference caused by the non-uniform thickness of the contact layer. It should be appreciated that this relationship may vary based on design of an ultrasonic sensor, and can be experimentally determined (e.g., during design and/or calibration). The number of frequencies and image portions used may also depend on the required accuracy and precision-mode the sensor is operating in. Furthermore, number of frequencies and image portions, and size of image portions, may also depends on the change of thickness. A calibration procedure may be run to determine which frequencies to use for which portions of the images, and which pixels are contained within the different portions. The calibration process may comprise capturing signals at different frequencies for different pixels or groups of pixels, and based on analyzing the captured signals, determine the appropriate frequencies and pixels groupings. The calibration process may be assisted by data providing information about the shape and form of the contact surface, such as e.g. a thickness map/model of the contact surface. The calibration process may also include developing a model for the shape and form of the contact surface using the ToF information of each pixel, collected by using a minimal interference drive scheme (e.g. small number of pulses and/or low frequency).
Pixel grouping map 900 includes twenty-five pixel groups (e.g., pixel groups 910a, 910b, 910c, and 910n), each using a particular transmission frequency during pixel capture. It should be appreciated that some pixel groups can use the same transmission frequency, as some pixel groups may have a same or similar thickness profile of the contact layer. During imaging, different portions of an image are captured using the different transmission frequencies. It should be appreciated that each portion may have ToF and beamforming settings corresponding to the transmission frequency of the portion. The pixels groups may be captured based on the order of the groups, for example, starting with pixel group 910a, then 910b etc. Alternatively, the pixel groups maybe captures in order of frequency, going from a low frequency to a high frequency, or vice-versa. It should be appreciated that portions can be individually captured or all portions using the same transmission frequency can be captured at the same imaging operation. In other embodiments, entire images may be captured using particular transmission frequencies, and the pertinent pixel groups may be extracted from these images for use in the final output image. The pixel groups of pixels grouping map are then combined into a single output image.
Pixel grouping map 950 includes four pixel groups 960a, 960b, 960c, and 960d, each using a particular transmission frequency during pixel capture. For example, pixel grouping map 950 may be used with an ultrasonic sensor having a circular convex or concave contact layer (e.g., ultrasonic fingerprint sensor 550 of
Temperature of an ultrasonic sensor can impact the operation of the ultrasonic sensor, because the temperature affects the acoustic characteristics of contact layer 630 (and other layers). For instance, in one embodiment, a temperature can impact the speed at which an ultrasonic signals traverses the contact layer. In some embodiments, a transmission frequency used by the ultrasonic sensor is varied according to temperature, to generate an image with a constant interference pattern, e.g., an interference pattern that does not change, or changes little, with temperature. Where an interference pattern is constant, an image interference correction can be applied to the resultant image to account for the impact of the interference pattern. The image correction is more accurate, the more stable the interference pattern is.
At procedure 1130, at least one fingerprint image is captured using the plurality of transmission frequencies. In one embodiment, as shown at procedure 1132, a plurality of fingerprint images is captured using the plurality of transmission frequencies. In one embodiment, the plurality of transmission frequencies operate to cancel out the interference pattern of the plurality of fingerprint images. In another embodiment, as shown at procedure 1134, a plurality of portions of a fingerprint image is captured using the plurality of transmission frequencies. In one embodiment, aspects of procedures 1132 and 1134 are both performed, where at least one fingerprint image is captured and at least one portion of a fingerprint image are captured, where at least two transmission frequencies are used.
At procedure 1140, the captured at least one fingerprint image is combined to generate an output fingerprint image. In one embodiment, as shown at procedure 1142, the plurality of fingerprint images (e.g., the plurality of fingerprint images captured at procedure 1132) is combined into a single output fingerprint image, wherein the single output fingerprint image reduces the impact of the interference pattern caused by the non-uniform thickness of the contact layer. In one embodiment, the plurality of fingerprint images is combined into a single output fingerprint image by averaging the plurality of fingerprint images. In another embodiment, the plurality of fingerprint images is combined into a single output fingerprint image by using convolution, which operates to reinforce similar signals (e.g., fingerprint ridges) and cancel out dissimilar signals (e.g., interference).
In another embodiment, as shown at procedure 1144, the plurality of portions of the fingerprint image (e.g., the plurality of portions captured at procedure 1134) is combined into a single output fingerprint image. In one embodiment, the plurality of transmission frequencies provide constructive interference for corresponding portions of the plurality of portions of the fingerprint image during the imaging operation. In one embodiment, the portions of the plurality of portions include a plurality of pixels. In another embodiment, the portions of the plurality of portions include single pixels.
At procedure 1150, the output fingerprint image is output (e.g., for use in fingerprint authentication).
At procedure 1220 of flow diagram 1200, a temperature of the ultrasonic sensor is determined. At procedure 1230, a transmission frequency of activated ultrasonic transducers is controlled during the imaging operation, wherein the transmission frequency is controlled based on the temperature of the ultrasonic sensor. The transmission frequency is selected to generate a constant interference pattern across all temperatures. At procedure 1240, at least one fingerprint image is captured using the transmission frequency. At procedure 1250, an interference pattern correction determined or calibrated at an initial temperature state is applied to the fingerprint image to generate the output fingerprint image.
At procedure 1260, the output fingerprint image is output (e.g., for use in fingerprint authentication).
What has been described above includes examples of the subject disclosure. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the subject matter, but it is to be appreciated that many further combinations and permutations of the subject disclosure are possible. Accordingly, the claimed subject matter is intended to embrace all such alterations, modifications, and variations that fall within the spirit and scope of the appended claims.
In particular and in regard to the various functions performed by the above described components, devices, circuits, systems and the like, the terms (including a reference to a “means”) used to describe such components are intended to correspond, unless otherwise indicated, to any component which performs the specified function of the described component (e.g., a functional equivalent), even though not structurally equivalent to the disclosed structure, which performs the function in the herein illustrated exemplary aspects of the claimed subject matter.
The aforementioned systems and components have been described with respect to interaction between several components. It can be appreciated that such systems and components can include those components or specified sub-components, some of the specified components or sub-components, and/or additional components, and according to various permutations and combinations of the foregoing. Sub-components can also be implemented as components communicatively coupled to other components rather than included within parent components (hierarchical). Additionally, it should be noted that one or more components may be combined into a single component providing aggregate functionality or divided into several separate sub-components. Any components described herein may also interact with one or more other components not specifically described herein.
In addition, while a particular feature of the subject innovation may have been disclosed with respect to only one of several implementations, such feature may be combined with one or more other features of the other implementations as may be desired and advantageous for any given or particular application. Furthermore, to the extent that the terms “includes,” “including,” “has,” “contains,” variants thereof, and other similar words are used in either the detailed description or the claims, these terms are intended to be inclusive in a manner similar to the term “comprising” as an open transition word without precluding any additional or other elements.
Thus, the embodiments and examples set forth herein were presented in order to best explain various selected embodiments of the present invention and its particular application and to thereby enable those skilled in the art to make and use embodiments of the invention. However, those skilled in the art will recognize that the foregoing description and examples have been presented for the purposes of illustration and example only. The description as set forth is not intended to be exhaustive or to limit the embodiments of the invention to the precise form disclosed.
This application claims also priority to and the benefit of co-pending U.S. Provisional Patent Application 62/875,479, filed on Jul. 17, 2019, entitled “FINGERPRINT IMAGING UNDER CURVED SURFACE,” by Quy Chau et al., having Attorney Docket No. IVS-921-PR, and assigned to the assignee of the present application, which is incorporated herein by reference in its entirety.
| Number | Name | Date | Kind |
|---|---|---|---|
| 4880012 | Sato | Nov 1989 | A |
| 5575286 | Weng et al. | Nov 1996 | A |
| 5684243 | Gururaja et al. | Nov 1997 | A |
| 5808967 | Yu et al. | Sep 1998 | A |
| 5867302 | Fleming | Feb 1999 | A |
| 5911692 | Hussain et al. | Jun 1999 | A |
| 6071239 | Cribbs et al. | Jun 2000 | A |
| 6104673 | Cole et al. | Aug 2000 | A |
| 6289112 | Jain et al. | Sep 2001 | B1 |
| 6292576 | Brownlee | Sep 2001 | B1 |
| 6350652 | Libera et al. | Feb 2002 | B1 |
| 6428477 | Mason | Aug 2002 | B1 |
| 6500120 | Anthony | Dec 2002 | B1 |
| 6676602 | Barnes et al. | Jan 2004 | B1 |
| 6736779 | Sano et al. | May 2004 | B1 |
| 7067962 | Scott | Jun 2006 | B2 |
| 7109642 | Scott | Sep 2006 | B2 |
| 7243547 | Cobianu et al. | Jul 2007 | B2 |
| 7257241 | Lo | Aug 2007 | B2 |
| 7400750 | Nam | Jul 2008 | B2 |
| 7433034 | Huang | Oct 2008 | B1 |
| 7459836 | Scott | Dec 2008 | B2 |
| 7471034 | Schlote-Holubek et al. | Dec 2008 | B2 |
| 7489066 | Scott et al. | Feb 2009 | B2 |
| 7634117 | Cho | Dec 2009 | B2 |
| 7739912 | Schneider et al. | Jun 2010 | B2 |
| 8018010 | Tigli et al. | Sep 2011 | B2 |
| 8139827 | Schneider et al. | Mar 2012 | B2 |
| 8255698 | Li et al. | Aug 2012 | B2 |
| 8311514 | Bandyopadhyay et al. | Nov 2012 | B2 |
| 8335356 | Schmitt | Dec 2012 | B2 |
| 8433110 | Kropp et al. | Apr 2013 | B2 |
| 8508103 | Schmitt et al. | Aug 2013 | B2 |
| 8515135 | Clarke et al. | Aug 2013 | B2 |
| 8666126 | Lee et al. | Mar 2014 | B2 |
| 8703040 | Liufu et al. | Apr 2014 | B2 |
| 8723399 | Sammoura et al. | May 2014 | B2 |
| 8805031 | Schmitt | Aug 2014 | B2 |
| 9056082 | Liautaud et al. | Jun 2015 | B2 |
| 9070861 | Bibl et al. | Jun 2015 | B2 |
| 9224030 | Du et al. | Dec 2015 | B2 |
| 9245165 | Slaby et al. | Jan 2016 | B2 |
| 9424456 | Kamath Koteshwara | Aug 2016 | B1 |
| 9572549 | Belevich et al. | Feb 2017 | B2 |
| 9582102 | Setlak | Feb 2017 | B2 |
| 9582705 | Du et al. | Feb 2017 | B2 |
| 9607203 | Yazdandoost et al. | Mar 2017 | B1 |
| 9607206 | Schmitt et al. | Mar 2017 | B2 |
| 9613246 | Gozzini et al. | Apr 2017 | B1 |
| 9665763 | Du et al. | May 2017 | B2 |
| 9747488 | Yazdandoost et al. | Aug 2017 | B2 |
| 9785819 | Oreifej | Oct 2017 | B1 |
| 9815087 | Ganti et al. | Nov 2017 | B2 |
| 9817108 | Kuo et al. | Nov 2017 | B2 |
| 9818020 | Schuckers et al. | Nov 2017 | B2 |
| 9881195 | Lee et al. | Jan 2018 | B2 |
| 9881198 | Lee et al. | Jan 2018 | B2 |
| 9898640 | Ghavanini | Feb 2018 | B2 |
| 9904836 | Yeke Yazdandoost et al. | Feb 2018 | B2 |
| 9909225 | Lee | Mar 2018 | B2 |
| 9922235 | Cho et al. | Mar 2018 | B2 |
| 9934371 | Hong et al. | Apr 2018 | B2 |
| 9939972 | Shepelev et al. | Apr 2018 | B2 |
| 9953205 | Rasmussen et al. | Apr 2018 | B1 |
| 9959444 | Young et al. | May 2018 | B2 |
| 9967100 | Hong et al. | May 2018 | B2 |
| 9983656 | Merrell et al. | May 2018 | B2 |
| 9984271 | King et al. | May 2018 | B1 |
| 10275638 | Yousefpor et al. | Apr 2019 | B1 |
| 10315222 | Salvia et al. | Jun 2019 | B2 |
| 10322929 | Soundara Pandian et al. | Jun 2019 | B2 |
| 10387704 | Dagan et al. | Aug 2019 | B2 |
| 10461124 | Berger et al. | Oct 2019 | B2 |
| 10478858 | Lasiter et al. | Nov 2019 | B2 |
| 10497747 | Tsai et al. | Dec 2019 | B2 |
| 10515255 | Strohmann et al. | Dec 2019 | B2 |
| 10539539 | Garlepp et al. | Jan 2020 | B2 |
| 10600403 | Garlepp et al. | Mar 2020 | B2 |
| 10656255 | Ng et al. | May 2020 | B2 |
| 10670716 | Apte et al. | Jun 2020 | B2 |
| 10706835 | Garlepp et al. | Jul 2020 | B2 |
| 10755067 | De Foras et al. | Aug 2020 | B2 |
| 20020135273 | Mauchamp et al. | Sep 2002 | A1 |
| 20030013955 | Poland | Jan 2003 | A1 |
| 20040085858 | Khuri-Yakub et al. | May 2004 | A1 |
| 20040122316 | Satoh et al. | Jun 2004 | A1 |
| 20040174773 | Thomenius et al. | Sep 2004 | A1 |
| 20050023937 | Sashida et al. | Feb 2005 | A1 |
| 20050057284 | Wodnicki | Mar 2005 | A1 |
| 20050100200 | Abiko et al. | May 2005 | A1 |
| 20050110071 | Ema et al. | May 2005 | A1 |
| 20050146240 | Smith et al. | Jul 2005 | A1 |
| 20050148132 | Wodnicki, et al. | Jul 2005 | A1 |
| 20050162040 | Robert | Jul 2005 | A1 |
| 20060052697 | Hossack et al. | Mar 2006 | A1 |
| 20060079777 | Karasawa | Apr 2006 | A1 |
| 20060230605 | Schlote-Holubek et al. | Oct 2006 | A1 |
| 20070046396 | Huang | Mar 2007 | A1 |
| 20070047785 | Jang et al. | Mar 2007 | A1 |
| 20070073135 | Lee et al. | Mar 2007 | A1 |
| 20070202252 | Sasaki | Aug 2007 | A1 |
| 20070215964 | Khuri-Yakub et al. | Sep 2007 | A1 |
| 20070230754 | Jain et al. | Oct 2007 | A1 |
| 20080125660 | Yao et al. | May 2008 | A1 |
| 20080150032 | Tanaka | Jun 2008 | A1 |
| 20080194053 | Huang | Aug 2008 | A1 |
| 20080240523 | Benkley et al. | Oct 2008 | A1 |
| 20090005684 | Kristoffersen et al. | Jan 2009 | A1 |
| 20090182237 | Angelsen et al. | Jul 2009 | A1 |
| 20090232367 | Shinzaki | Sep 2009 | A1 |
| 20090274343 | Clarke | Nov 2009 | A1 |
| 20090303838 | Svet | Dec 2009 | A1 |
| 20100030076 | Vortman et al. | Feb 2010 | A1 |
| 20100046810 | Yamada | Feb 2010 | A1 |
| 20100113952 | Raguin et al. | May 2010 | A1 |
| 20100168583 | Dausch et al. | Jul 2010 | A1 |
| 20100195851 | Buccafusca | Aug 2010 | A1 |
| 20100201222 | Adachi et al. | Aug 2010 | A1 |
| 20100202254 | Roest et al. | Aug 2010 | A1 |
| 20100239751 | Regniere | Sep 2010 | A1 |
| 20100251824 | Schneider et al. | Oct 2010 | A1 |
| 20100256498 | Tanaka | Oct 2010 | A1 |
| 20100278008 | Ammar | Nov 2010 | A1 |
| 20110285244 | Lewis et al. | Nov 2011 | A1 |
| 20110291207 | Martin et al. | Dec 2011 | A1 |
| 20120016604 | Irving et al. | Jan 2012 | A1 |
| 20120092026 | Liautaud et al. | Apr 2012 | A1 |
| 20120095347 | Adam et al. | Apr 2012 | A1 |
| 20120147698 | Wong et al. | Jun 2012 | A1 |
| 20120232396 | Tanabe | Sep 2012 | A1 |
| 20120238876 | Tanabe et al. | Sep 2012 | A1 |
| 20120263355 | Monden | Oct 2012 | A1 |
| 20120279865 | Regniere et al. | Nov 2012 | A1 |
| 20120288641 | Diatezua et al. | Nov 2012 | A1 |
| 20120300988 | Ivanov et al. | Nov 2012 | A1 |
| 20130051179 | Hong | Feb 2013 | A1 |
| 20130064043 | Degertekin et al. | Mar 2013 | A1 |
| 20130127592 | Fyke et al. | May 2013 | A1 |
| 20130133428 | Lee et al. | May 2013 | A1 |
| 20130201134 | Schneider et al. | Aug 2013 | A1 |
| 20130271628 | Ku et al. | Oct 2013 | A1 |
| 20130294201 | Hajati | Nov 2013 | A1 |
| 20130294202 | Hajati | Nov 2013 | A1 |
| 20140060196 | Falter et al. | Mar 2014 | A1 |
| 20140117812 | Hajati | May 2014 | A1 |
| 20140176332 | Alameh et al. | Jun 2014 | A1 |
| 20140208853 | Onishi et al. | Jul 2014 | A1 |
| 20140219521 | Schmitt et al. | Aug 2014 | A1 |
| 20140232241 | Hajati | Aug 2014 | A1 |
| 20140265721 | Robinson et al. | Sep 2014 | A1 |
| 20140313007 | Harding | Oct 2014 | A1 |
| 20140355387 | Kitchens et al. | Dec 2014 | A1 |
| 20150036065 | Yousefpor et al. | Feb 2015 | A1 |
| 20150049590 | Rowe et al. | Feb 2015 | A1 |
| 20150087991 | Chen et al. | Mar 2015 | A1 |
| 20150097468 | Hajati et al. | Apr 2015 | A1 |
| 20150145374 | Xu et al. | May 2015 | A1 |
| 20150164473 | Kim et al. | Jun 2015 | A1 |
| 20150165479 | Lasiter et al. | Jun 2015 | A1 |
| 20150169136 | Ganti et al. | Jun 2015 | A1 |
| 20150189136 | Chung et al. | Jul 2015 | A1 |
| 20150198699 | Kuo et al. | Jul 2015 | A1 |
| 20150206738 | Rastegar | Jul 2015 | A1 |
| 20150213180 | Herberholz | Jul 2015 | A1 |
| 20150220767 | Yoon et al. | Aug 2015 | A1 |
| 20150241393 | Ganti et al. | Aug 2015 | A1 |
| 20150261261 | Bhagavatula et al. | Sep 2015 | A1 |
| 20150286312 | Kang et al. | Oct 2015 | A1 |
| 20150301653 | Urushi | Oct 2015 | A1 |
| 20150345987 | Hajati | Dec 2015 | A1 |
| 20150371398 | Qiao et al. | Dec 2015 | A1 |
| 20160051225 | Kim et al. | Feb 2016 | A1 |
| 20160063294 | Du et al. | Mar 2016 | A1 |
| 20160063300 | Du et al. | Mar 2016 | A1 |
| 20160070967 | Du et al. | Mar 2016 | A1 |
| 20160070968 | Gu et al. | Mar 2016 | A1 |
| 20160086010 | Merrell et al. | Mar 2016 | A1 |
| 20160092715 | Yazdandoost et al. | Mar 2016 | A1 |
| 20160092716 | Yazdandoost et al. | Mar 2016 | A1 |
| 20160100822 | Kim et al. | Apr 2016 | A1 |
| 20160107194 | Panchawagh et al. | Apr 2016 | A1 |
| 20160180142 | Riddle et al. | Jun 2016 | A1 |
| 20160326477 | Fernandez-Alcon et al. | Nov 2016 | A1 |
| 20160350573 | Kitchens, II | Dec 2016 | A1 |
| 20160358003 | Shen et al. | Dec 2016 | A1 |
| 20170004352 | Jonsson et al. | Jan 2017 | A1 |
| 20170330552 | Garlepp et al. | Jan 2017 | A1 |
| 20170032485 | Vemury | Feb 2017 | A1 |
| 20170075700 | Abudi et al. | Mar 2017 | A1 |
| 20170100091 | Eigil et al. | Apr 2017 | A1 |
| 20170110504 | Panchawagh et al. | Apr 2017 | A1 |
| 20170119343 | Pintoffl | May 2017 | A1 |
| 20170124374 | Rowe et al. | May 2017 | A1 |
| 20170168543 | Dai et al. | Jun 2017 | A1 |
| 20170185821 | Chen et al. | Jun 2017 | A1 |
| 20170194934 | Shelton et al. | Jul 2017 | A1 |
| 20170219536 | Koch et al. | Aug 2017 | A1 |
| 20170231534 | Agassy et al. | Aug 2017 | A1 |
| 20170255338 | Medina et al. | Sep 2017 | A1 |
| 20170293791 | Mainguet et al. | Oct 2017 | A1 |
| 20170316243 | Ghavanini | Nov 2017 | A1 |
| 20170316248 | He et al. | Nov 2017 | A1 |
| 20170322290 | Ng | Nov 2017 | A1 |
| 20170322291 | Salvia et al. | Nov 2017 | A1 |
| 20170322292 | Salvia et al. | Nov 2017 | A1 |
| 20170322305 | Apte et al. | Nov 2017 | A1 |
| 20170323133 | Tsai | Nov 2017 | A1 |
| 20170325081 | Chrisikos | Nov 2017 | A1 |
| 20170326590 | Daneman | Nov 2017 | A1 |
| 20170326591 | Apte et al. | Nov 2017 | A1 |
| 20170326593 | Garlepp et al. | Nov 2017 | A1 |
| 20170326594 | Berger | Nov 2017 | A1 |
| 20170328866 | Apte | Nov 2017 | A1 |
| 20170328870 | Garlepp et al. | Nov 2017 | A1 |
| 20170330012 | Salvia et al. | Nov 2017 | A1 |
| 20170330553 | Garlepp et al. | Nov 2017 | A1 |
| 20170357839 | Yazdandoost et al. | Dec 2017 | A1 |
| 20180025202 | Ryshtun et al. | Jan 2018 | A1 |
| 20180101711 | D'Souza et al. | Apr 2018 | A1 |
| 20180107854 | Tsai et al. | Apr 2018 | A1 |
| 20180129849 | Strohmann et al. | May 2018 | A1 |
| 20180129857 | Bonev | May 2018 | A1 |
| 20180178251 | Foncellino et al. | Jun 2018 | A1 |
| 20180206820 | Anand et al. | Jul 2018 | A1 |
| 20180225495 | Jonsson et al. | Aug 2018 | A1 |
| 20180229267 | Ono et al. | Aug 2018 | A1 |
| 20180276443 | Strohmann et al. | Sep 2018 | A1 |
| 20180329560 | Kim et al. | Nov 2018 | A1 |
| 20180349663 | Garlepp et al. | Dec 2018 | A1 |
| 20180357457 | Rasmussen et al. | Dec 2018 | A1 |
| 20180369866 | Sammoura et al. | Dec 2018 | A1 |
| 20180373913 | Panchawagh et al. | Dec 2018 | A1 |
| 20190005300 | Garlepp et al. | Jan 2019 | A1 |
| 20190012673 | Chakraborty | Jan 2019 | A1 |
| 20190018123 | Narasimha-Iyer et al. | Jan 2019 | A1 |
| 20190057267 | Kitchens et al. | Feb 2019 | A1 |
| 20190073507 | D'Souza et al. | Mar 2019 | A1 |
| 20190087632 | Raguin | Mar 2019 | A1 |
| 20190102046 | Miranto et al. | Apr 2019 | A1 |
| 20190130083 | Agassy et al. | May 2019 | A1 |
| 20190171858 | Ataya et al. | Jun 2019 | A1 |
| 20190188441 | Hall et al. | Jun 2019 | A1 |
| 20190188442 | Flament et al. | Jun 2019 | A1 |
| 20190325185 | Tang | Oct 2019 | A1 |
| 20190340455 | Jung et al. | Nov 2019 | A1 |
| 20190370518 | Maor | Dec 2019 | A1 |
| 20200030850 | Apte et al. | Jan 2020 | A1 |
| 20200050816 | Tsai | Feb 2020 | A1 |
| 20200050817 | Salvia et al. | Feb 2020 | A1 |
| 20200050820 | Iatsun | Feb 2020 | A1 |
| 20200050828 | Li et al. | Feb 2020 | A1 |
| 20200074135 | Garlepp et al. | Mar 2020 | A1 |
| 20200125710 | Andersson et al. | Apr 2020 | A1 |
| 20200147644 | Chang | May 2020 | A1 |
| 20200158694 | Garlepp et al. | May 2020 | A1 |
| 20200175143 | Lee et al. | Jun 2020 | A1 |
| 20200210666 | Flament | Jul 2020 | A1 |
| 20200285882 | Skovgaard Christensen | Sep 2020 | A1 |
| 20200302140 | Lu et al. | Sep 2020 | A1 |
| Number | Date | Country |
|---|---|---|
| 1826631 | Aug 2006 | CN |
| 102159334 | Aug 2011 | CN |
| 105264542 | Jan 2016 | CN |
| 105378756 | Mar 2016 | CN |
| 109255323 | Jan 2019 | CN |
| 1214909 | Jun 2002 | EP |
| 2884301 | Jun 2015 | EP |
| 3086261 | Oct 2016 | EP |
| 2011040467 | Feb 2011 | JP |
| 201531701 | Aug 2015 | TW |
| 2009096576 | Aug 2009 | WO |
| 2009137106 | Nov 2009 | WO |
| 2014035564 | Mar 2014 | WO |
| 2015009635 | Jan 2015 | WO |
| 2015112453 | Jul 2015 | WO |
| 2015120132 | Aug 2015 | WO |
| 2015131083 | Sep 2015 | WO |
| 2015134816 | Sep 2015 | WO |
| 2015183945 | Dec 2015 | WO |
| 2016007250 | Jan 2016 | WO |
| 2016011172 | Jan 2016 | WO |
| 2016040333 | Mar 2016 | WO |
| 2016061406 | Apr 2016 | WO |
| 2016061410 | Apr 2016 | WO |
| 2017003848 | Jan 2017 | WO |
| 2017053877 | Mar 2017 | WO |
| 2017192895 | Nov 2017 | WO |
| 2017196678 | Nov 2017 | WO |
| 2017196682 | Nov 2017 | WO |
| 2017192903 | Dec 2017 | WO |
| 2019164721 | Aug 2019 | WO |
| Entry |
|---|
| Tang, et al., “Pulse-Echo Ultrasonic Fingerprint Sensor on a Chip”, IEEE Transducers, Anchorage, Alaska, USA, Jun. 21-25, 2015, pp. 674-677. |
| ISA/EP, Partial International Search Report for International Application No. PCT/US2019/034032, 8 pages, dated Sep. 12, 2019, 8. |
| ISA/EP, International Search Report and Written Opinion for International Application # PCT/US2018/063431, pp. 1-15, dated Feb. 5, 2019. |
| ISA/EP, International Search Report and Written Opinion for International Application # PCT/US2019/015020, pp. 1-23, dated Jul. 1, 2019. |
| ISA/EP, International Search Report and Written Opinion for International Application # PCT/US2019/023440, pp. 1-10, dated Jun. 4, 2019. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031120, 12 pages, dated Aug. 29, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031127, 13 pages, dated Sep. 1, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031134, 12 pages, dated Aug. 30, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031140, 18 pages,dated Nov. 2, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031421 13 pages, dated Jun. 21, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031426 13 pages, dated Jun. 22, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031431, 14 pages, dated Aug. 1, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031434, 13 pages, dated Jun. 26, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031439, 10 pages, dated Jun. 20, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031824, 18 pages, dated Sep. 22, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031827, 16 pages, dated Aug. 1, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2017/031831, 12 pages, dated Jul. 21, 2017. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2018/037364, 10 pages, dated Sep. 3, 2018. |
| ISA/EP, International Search Report for International Application No. PCT/US2017/031826, 16 pages, dated Feb. 27, 2018. |
| ISA/EP, Partial International Search Report for International Application No. PCT/US2017/031140, 13 pages, dated Aug. 29, 2017. |
| ISA/EP, Partial International Search Report for International Application No. PCT/US2017/031826, 12 pages, dated Nov. 30, 2017. |
| “Moving Average Filters”, Waybackmachine XP05547422, Retrieved from the Internet: URL:https://web.archive.org/web/20170809081353/https//www.analog.com/media/en/technical-documentation/dsp-book/dsp_book_Ch15.pdf—[retrieved on Jan. 24, 2019], Aug. 9, 2017, 1-8. |
| “Receiver Thermal Noise Threshold”, Fisher Telecommunication Services, Satellite Communications. Retrieved from the Internet: URL:https://web.archive.org/web/20171027075705/http//www.fishercom.xyz:80/satellite-communications/receiver-thermal-noise-threshold.html, Oct. 27, 2017, 3. |
| “Sleep Mode”, Wikipedia, Retrieved from the Internet: URL:https://web.archive.org/web/20170908153323/https://en.wikipedia.org/wiki/Sleep_mode [retrieved on Jan. 25, 2019], Sep. 8, 2017, 1-3. |
| “TMS320C5515 Fingerprint Development Kit (FDK) Hardware Guide”, Texas Instruments, Literature Number: SPRUFX3, XP055547651, Apr. 2010, 1-26. |
| “ZTE V7 Max. 5,5” smartphone on MediaTeck Hello P10 cpu; Published on Apr. 20, 2016; https://www.youtube.com/watch?v=ncNCbpkGQzU (Year 2016). |
| Cappelli, et al., “Fingerprint Image Reconstruction from Standard Templates”, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society, vol. 29, No. 9, Sep. 2007, 1489-1503. |
| Dausch, et al., “Theory and Operation of 2-D Array Piezoelectric Micromachined Ultrasound Transducers”, IEEE Transactions on Ultrasonics, and Frequency Control, vol. 55, No. 11;, Nov. 2008, 2484-2492. |
| Feng, et al., “Fingerprint Reconstruction: From Minutiae to Phase”, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society, vol. 33, No. 2, Feb. 2011, 209-223. |
| Hopcroft, et al., “Temperature Compensation of a MEMS Resonator Using Quality Factor as a Thermometer”, Retrieved from Internet: http://micromachine.stanford.edu/˜amanu/linked/MAH_MEMS2006.pdf, 2006, 222-225. |
| Hopcroft, et al., “Using the temperature dependence of resonator quality factor as a thermometer”, Applied Physics Letters 91. Retrieved from Internet: http://micromachine.stanford.edu/˜hopcroft/Publications/Hopcroft_QT_ApplPhysLett_91_013505.pdf, 2007, 013505-1-031505-3. |
| Jiang, et al., “Ultrasonic Fingerprint Senseor with Transmit Beamforming Based on a PMUT Array Bonded to CMOS Circuitry”, IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, Jan. 1, 2017, 1-9. |
| Kumar, et al., “Towards Contactless, Low-Cost and Accurate 3D Fingerprint Identification”, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society, vol. 37, No. 3, Mar. 2015, 681-696. |
| Lee, et al., “Low jitter and temperature stable MEMS oscillators”, Frequency Control Symposium (FCS), 2012 IEEE International, May 2012, 1-5. |
| Li, et al., “Capacitive micromachined ultrasonic transducer for ultra-low pressure measurement: Theoretical study”, AIP Advances 5.12. Retrieved from Internet: http://scitation.aip.org/content/aip/journal/adva/5/12/10.1063/1.4939217, 2015, 127231. |
| Pang, et al., “Extracting Valley-Ridge Lines from Point-Cloud-Based 3D Fingerprint Models”, IEEE Computer Graphics and Applications, IEEE Service Center, New York, vol. 33, No. 4, Jul./Aug. 2013, 73-81. |
| Papageorgiou, et al., “Self-Calibration of Ultrasonic Transducers in an Intelligent Data Acquisition System”, International Scientific Journal of Computing, 2003, vol. 2, Issue 2 Retrieved Online: URL: https://scholar.google.com/scholar?q=self-calibration+of+ultrasonic+transducers+in+an+intelligent+data+acquisition+system&hl=en&as_sdt=0&as_vis=1&oi=scholart, 2003, 9-15. |
| Qiu, et al., “Piezoelectric Micromachined Ultrasound Transducer (PMUT) Arrays for Integrated Sensing, Actuation and Imaging”, Sensors 15, doi:10.3390/s150408020, Apr. 3, 2015, 8020-8041. |
| Ross, et al., “From Template to Image: Reconstructing Fingerprints from Minutiae Points”, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society, vol. 29, No. 4, Apr. 2007, 544-560. |
| Rozen, et al., “Air-Coupled Aluminum Nitride Piezoelectric Micromachined Ultrasonic Transducers At 0.3 MHZ to 0.9 MHZ”, 2015 28th IEEE International Conference on Micro Electro Mechanical Systems (MEMS), IEEE, Jan. 18, 2015, 921-924. |
| Savoia, et al., “Design and Fabrication of a cMUT Probe for Ultrasound Imaging of Fingerprints”, 2010 IEEE International Ultrasonics Symposium Proceedings, Oct. 2010, 1877-1880. |
| Shen, et al., “Anisotropic Complementary Acoustic Metamaterial for Canceling out Aberrating Layers”, American Physical Society, Physical Review X 4.4: 041033., Nov. 19, 2014, 041033-1-041033-7. |
| Thakar, et al., “Multi-resonator approach to eliminating the temperature dependence of silicon-based timing references”, Hilton Head'14. Retrieved from the Internet: http://blog.narotama.ac.id/wp-content/uploads/2014/12/Multi-resonator-approach-to-eliminating-the-temperature-dependance-of-silicon-based-timing-references.pdf, 2014, 415-418. |
| Zhou et al., “Partial Fingerprint Reconstruction with Improved Smooth Extension”, Network and System Security, Springer Berlin Heidelberg, Jun. 3, 2013, 756-762. |
| “ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2020/033854, 16 pages, dated Nov. 3, 2020”. |
| “ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2020/039208, 10 pages, dated Oct. 9, 2020”. |
| “ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2020/039452, 11 pages, dated Sep. 9, 2020”. |
| “ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2020/042427, 18 pages, dated Dec. 14, 2020”. |
| “ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2020/042428, 9 pages, dated Oct. 26, 2020”. |
| “ISA/EP, Partial Search Report and Provisional Opinion for International Application No. PCT/US2020/042427, 13 pages, dated Oct. 26, 2020”. |
| “ISA/EP, Partial Search Report for International Application No. PCT/US2020/033854, 10 pages, dated Sep. 8, 2020”. |
| “Office Action for CN App No. 201780029016.7 dated Mar. 24, 2020, 7 pages”. |
| “Office Action for CN App No. 201780029016.7 dated Sep. 25, 2020, 7 pages”. |
| Tang, et al., “11.2 3D Ultrasonic Fingerprint Sensor-on-a-Chip”, 2016 IEEE International Solid-State Circuits Conference, IEEE, Jan. 31, 2016, 202-203. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2019061516, 14 pages, dated Mar. 12, 2020. |
| ISA/EP, International Search Report and Written Opinion for International Application No. PCT/US2021/021412, 12 pages, dated Jun. 9, 2021. |
| Taiwan Application No. 106114623, 1st Office Action, dated Aug. 5, 2021, pp. 1-8. |
| Number | Date | Country | |
|---|---|---|---|
| 20210019488 A1 | Jan 2021 | US |
| Number | Date | Country | |
|---|---|---|---|
| 62875479 | Jul 2019 | US |
