This application relates to radio frequency-based systems and methods for detecting movement. Specifically, this application describes systems and methods for detecting avalanches and other land movement.
Example systems and methods are disclosed herein for detecting movement on a sloped surface, such as an avalanche or landslide. Locations on the sloped surface may be defined relative to a detection system using a three-dimensional coordinate system. For instance, the detection system may specify locations on the sloped surface in terms of azimuth, elevation, and range. A two-dimensional projection of the sloped surface may be described in terms of azimuth and elevation.
An example apparatus may include one or more transmit antennas to transmit at least one radio frequency (RF) chirp to a portion of the sloped surface. For example, a horn antenna may be used to transmit an RF chirp to a relatively large portion of a mountainside. Multiple receive antennas may receive reflected chirps from the sloped surface. The receive antennas may be arranged in a one-dimensional array.
In some embodiments, the system comprises one or more transmit antennas to sequentially transmit RF chirps to a target slope. The system may include a signal generator to generate the RF chirps or receive a drive signal from an external source. The system includes multiple receive antennas to receive reflections of transmitted RF chirps as reflected chirps from locations on the target slope. In three-dimensional space, each reflected chirp can be accurately described as originating from a location on the sloped surface defined with respect to the receiver antennas in terms of a range, an elevation angle, and an azimuth angle (e.g., in a spherical or cylindrical coordinate system).
However, in many of the embodiments described herein, reflected chirps are locationally defined with respect to a two-dimensional projection of the sloped surface. Assuming the sloped surface does not have any inverted slopes or ignoring them if it does, there is a one-to-one correspondence between elevation angle and range for a given azimuth angle. Accordingly, the location of each reflected chirp may be conveniently defined in terms of an azimuth (e.g., an x-axis coordinate) and an elevation (e.g., a y-axis coordinate) on a two-dimensional projection of a sloped surface to facilitate two-dimensional visualization of a return value. Thus, a reflected chirp is described herein as having an azimuth and an elevation in that those values define the location of the reflected chirp on the two-dimensional projection and can be mapped to three-dimensional space without any loss of specificity.
In some embodiments, the receiver antennas comprise a one-dimensional array of antennas and the azimuth is determined using digital beamforming techniques. In other embodiments, the detection subsystem determines an azimuth of each reflected chirp based on the relative positions of the receive antennas and differences in timing at which different receive antennas detect the reflected chirp. In some instances, the detection system may additionally or alternatively use differences in the phase angle at which different receive antennas detect the reflected chirp.
The detection subsystem may calculate an elevation angle of each reflected chirp based on a calculated distance (e.g., based on a time-of-flight) that each reflected chirp traveled, the determined azimuth angle of the reflected chirp, and a known topography of the mountainside. For example, the topography of a mountain may be known or previously calculated such that, for a given azimuth angle, there is a one-to-one correspondence between the distance to the surface of the mountainside and the elevation angle. For instance, for a given azimuth, the base of the mountain might be at a distance of two kilometers and the peak of the mountain might be at a distance of four kilometers. Assuming the topography between the base and the peak is known, there is a one-to-one correspondence between the distance to the surface of the mountain and the angle of elevation. The system may ignore portions of a mountainside that are inverted since inverted slopes cannot accumulate snow or debris that may eventually lead to an avalanche or landslide.
The system may also determine one or more return values of each received reflected chirp, such as phase shifts and/or power levels. Accordingly, for each transmitted RF chirp, the system may receive a large number of reflected chirps from various locations on the mountainside. The system may identify the location from which each reflected chirp originated and determine a phase shift, power level, or other return value. For a sequence of transmitted RF chirps, the system may generate sequential return value representations of the target slope based on reflected chirps from multiple locations on the target slope. The representation may be a mathematical representation (e.g., a three-dimensional or four-dimensional matrix) or an imaging representation. For example, the system may generate an imaging representation of the mountainside as a two-dimensional projection with azimuth along one axis and elevation along the other axis. Various color or grayscale shades may be used to represent the varying return values of reflected chirps from each azimuth-elevation location on the imaging representation.
Movement of objects on the mountainside affects the return values of reflected chirps. Thus, movement on the mountainside can be identified by comparing the representation over time. Small movement may be attributed to animals or humans, while large-scale movement across a large portion of the representation may be indicative of an avalanche or landslide. The system may detect motion events based on variations in return value representations from one moment to another. Detected motion events that match defined movement patterns or exceed defined thresholds may be flagged and reported. In some embodiments, motion events identified by the system may be characterized and described by humans after the fact. The system may improve motion event characterization over time through the use of computer learning, artificial intelligence techniques, neural network machine learning approaches, and the like.
In various embodiments, the return value representations of the target slope are generated as imaging representations in an azimuth domain (or range domain) to facilitate visual analysis by humans. The two-dimensional projection of the mountainside in the range domain may be easily identifiable and similar to a map of the mountainside.
In various embodiments, the transmitted RF chirp may be generated by a signal generator comprising a radio frequency mixer that mixes an oscillating frequency signal and a transmission signal.
The detection subsystem described herein may comprise hardware, firmware, and/or software implemented by a process. For example, the detection subsystem may include one or more of a field-programmable gate array (FPGA), an application specific integrated circuit (ASIC), or a processor and computer-readable medium with instructions stored therein that, when executed by the processor, cause the processor to determine the elevation and azimuth information as described above.
In one specific embodiment, the detection subsystem may be partially implemented using a plurality of receive mixers to mix each transmitted RF chirp with reflected chirps received by each of the receive antennas to generate difference signals. The difference signals may be processed to determine elevation and azimuth information as described herein.
While specific embodiments are described herein, it is appreciated that many different combinations of hardware, firmware, and software may be used to implement the systems described herein. Accordingly, this application encompasses any combination of components designed to transmit a sequence of RF chirps to a target mountainside, receive reflected chirps from various locations, determine an azimuth of each reflected chirp, and determine an elevation of each reflected chirp based further on a time-of-flight of each reflected chirp, and a known topography of the mountainside.
Many embodiments of the systems described herein may be utilized to detect avalanches and/or landslides. Providing a warning signal at the start of an avalanche can save lives by giving the time for potential victims to get out of the way, close roads, and/or close trails potentially affected by the slide. In addition, providing a warning signal can facilitate the response of emergency personnel (e.g., more rapidly than without that warning signal). Further, knowing a location, size, and/or other metrics of an avalanche may help in forecasting future avalanches or for developing mitigation plans.
While examples described herein include devices and methods in the context of avalanche detection on a mountain slope, it can be appreciated that the systems and devices described herein may also be utilized in the detection of various objects moving across a portion of land. The movement of land or objects on land could also be detected by the devices and methods herein to provide a warning signal to potential victims. For example, falling rocks may be detected on a mountain slope and a warning signal may be provided to potential victims and/or facilitate the response of emergency personnel. As another example, moving objects on the land may be detected by the devices and methods described herein, such as skiers skiing down a mountain slope.
In some embodiments, the system may detect the number of skiers affected or potentially affected by an avalanche. In other embodiments, the systems and methods described herein may be used to detect the movement of people into and/or out of an area, such as a building, stadium, or other public, private, secured, or unsecured location.
The systems and methods described herein can operate with one or more transmit antennas and a one-dimensional array of receive antennas. In fact, in some embodiments, a sparse or thinned one-dimensional array of receive antennas may be utilized. As described herein, the azimuth may be determined through digital beamforming or other digital signal processing techniques based on the arrival time of reflected chirps at the various receive antennas and/or the received phase angle differences. The elevation is determined based on calculated distances (e.g., based on time-of-flight measurements) and a known static topography of a mountainside. Knowledge of the topography of the mountainside allows the system to operate with reduced complexity and reduced cost. The presently described systems and methods avoid the cost and complexity of conventional radar systems that may operate by mechanically rotating an antenna and/or include complex and costly phased arrays. Furthermore, the presently described systems and methods allow for a snapshot of return values (e.g., power levels and/or phase shifts) to be captured for an entire portion of a mountainside after each transmitted RF chirp. The approach described herein is different than and in contrast to systems that use raster-scanning or rotational slice-scanning.
The range resolution of the systems described herein may be selected based on the pulse length of transmitted RF, frequency and/or phase modulation of transmitted RF coupled with matched-filter compression, and/or the bandwidth of the modulation. Modulation schemes such as linear frequency modulation (LFM) make fine range resolution practical and provide adequate bandwidth. The azimuth (or cross-range) resolution of the system is associated with the effective antenna azimuth beamwidth, which is determined in part based on antenna size and the center frequency used.
The azimuth resolution (e.g., ‘over the ground’) can be calculated as the azimuth beamwidth by the range. To achieve fine azimuth resolution with a real-aperture antenna, large antenna sizes are typically utilized, even when the radio frequencies used are very high. Smaller antennas generally have wider azimuth beams and correspondingly coarser azimuth resolutions.
In some embodiments, a system may include multiple fixed antennas and a processor or other controller to generate multiple antenna beams that cover a target area using digital signal processing (DSP). For example, DSP may be used to generate beamforms that cover a target area across an azimuth axis parallel to an alignment of a fixed antenna array. In some embodiments, the system may utilize linear frequency modulation (LFM) to increase range resolution.
In some embodiments, a return value representation (e.g., a power level map image of a mountainside) may be generated for each transmitted RF chirp. In other embodiments, multiple received reflected chirps may be averaged over time to generate each return value representation. As a specific example, N samples of received reflected chirps may be received, for example, over a time period of T length. The T length of the time period may be a time length, such as 10 nanoseconds, 10 milliseconds, or 1 second.
The system may identify changes in power levels of reflected chirps from a target region as indicative of movement. Similarly, the system may identify changes in the phase shifts of reflected chirps from a target region as indicative of movement. In some embodiments, movement may only be identified if both changes in power levels and changes in phase angle indicate movement. Moving objects may shift or modulate the phase and/or power level of reflected chirps. Detected power levels of received reflected chirps returned from moving objects may vary due to deflections of the transmitted RF chirps at different angles, phase shifts in the reflected chirps, and/or variations in absorption of the transmitted RF chirps.
Each different spatial pattern of power level changes over time may correspond to different movement types. For example, one spatial pattern of power level changes over time may correspond to movement of a skier. Another spatial pattern of power level changes over time may correspond to movement of a hiker or an animal. The system may identify other spatial patterns of movement (power level changes over time) as corresponding to avalanches or landslides.
Threshold and constant false alarm (CFAR) techniques may be utilized to detect temporal changes that indicate an avalanche in progress. When a sufficiently large area in an image is changing or moving, as detected by a processor executing a detection routine, an avalanche indication may be sent or reported that provides a notification that an avalanche is in progress. For example, the processor may provide a text-based notification to a cell phone, an electronic notification through a cloud-based computer server, an audible alarm, a visual alert, and/or the like.
Many existing computing devices and infrastructures may be used in combination with the presently described systems and methods. Some of the infrastructure that can be used with embodiments disclosed herein is already available, such as general-purpose computers, computer programming tools and techniques, digital storage media, and communication links. Many of the systems, subsystems, modules, components, and the like that are described herein may be implemented as hardware, firmware, and/or software. Various systems, subsystems, modules, and components are described in terms of the function(s) they perform because such a wide variety of possible implementations exist. For example, it is appreciated that many existing programming languages, hardware devices, frequency bands, circuits, software platforms, networking infrastructures, and/or data stores may be utilized alone or in combination to implement a specific function.
It is also appreciated that two or more of the systems, subsystems, components, and/or modules as described herein may be combined as a single system, subsystem, module, or component. Moreover, many of the systems, subsystems, components, and modules may be duplicated or further divided into discrete systems, subsystems, components, or modules to perform subtasks of those described herein. Any of the embodiments described herein may be combined with any combination of other embodiments described herein. Many of the embodiments of the systems and methods described herein that appear to be mutually exclusive may be used in combination as weighted functions of one another and/or in primary-backup configurations in which one embodiment is used primarily, and the other embodiment is available as a backup.
As used herein, a computing device, system, subsystem, module, or controller may include a processor, such as a microprocessor, a microcontroller, logic circuitry, or the like. A processor may include one or more special-purpose processing devices, such as an application-specific integrated circuit (ASIC), a programmable array logic (PAL), a programmable logic array (PLA), a programmable logic device (PLD), a field-programmable gate array (FPGA), or another customizable and/or programmable device. The system may also include a computing device with a machine-readable storage device, such as non-volatile memory, static RAM, dynamic RAM, ROM, flash memory, or another machine-readable storage medium. Various aspects of certain embodiments may be implemented using hardware, software, firmware, or a combination thereof.
The components of some of the disclosed embodiments are described and illustrated in the figures herein. Many portions thereof could be arranged and designed in a wide variety of different configurations. Furthermore, the features, structures, and operations associated with one embodiment may be applied to or combined with the features, structures, or operations described in conjunction with another embodiment. In many instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of this disclosure. The right to add any described embodiment or feature to any one of the figures and/or as a new figure is explicitly reserved.
The embodiments of the systems and methods provided within this disclosure are not intended to limit the scope of the disclosure but are merely representative of possible embodiments. In addition, the steps of a method do not necessarily need to be executed in any specific order, or even sequentially, nor do the steps need to be executed only once. Many descriptions and variations of antennas described in terms of transmitters are equally applicable to receivers, and vice versa, unless context or functionality dictates otherwise.
As illustrated, the antennas 110 of the system 120 are oriented toward the mountain slope along a range axis 101 (X-axis) such that the RF chirps transmitted by the system 120 are transmitted along the range axis 101 with a beamheight defined in an elevation axis 102 (Y-axis) and a beamwidth defined in an azimuth axis 103 (Z-axis). In other embodiments, system 120 operations may be spatially defined using a polar coordinate system with standard azimuth, range, and elevation values. The system 120 may repeatedly transmit a single RF chirp that covers the entire target area. Alternatively, the system 120 may transmit RF chirps at different elevations and/or at different azimuth angles during each time period. The system 120 may include any number or configuration of the transmit antennas 110. The transmit antennas 110 may each or collectively have a fixed position such that transmitted RF chirps do not vary along the elevation axis 102.
At least two of the antennas 325 are receive antennas. The receive antennas may be, for example, a full or thinned array of microstrip antennas to receive reflections of the transmitted RF chirps 313 as reflected chirps 324. As illustrated, the system 320 may be oriented towards the mountain with the planar receive surface of the array of microstrip antennas substantially parallel with the azimuth-elevation plane (Z-Y plane) with the individual receive antennas extending along the azimuth dimension 303 (the Z-axis). The antennas 325 may be positionally fixed (i.e., they do not rotate or tilt during operation) along the azimuth axis 303. The range axis 301 (X-axis) is orthogonal to the azimuth axis 303 and the elevation axis 302 (Y-axis). The transmit antenna(s) and/or receive antennas 325 may be configured during manufacturing or adjusted during setup to have a fixed transmit and receive elevation angle for beamforming to the target portion 305 of the mountainside. In some embodiments, distinct RF chirps (e.g., uniquely modulated, different frequencies, encoded, etc.) may be transmitted at different elevations such that received reflected chirps can be coarsely identified as originating from a specific elevation on the mountainside.
Each of the plurality of receive antennas 325 of the system 320 may receive reflected chirps 324 from the target area 305. The reflected chirps 324 may be received at respective receiving antennas at different times and/or at different phase angles. For example, since the target area 305 is to the right of the system 320, the right-most receive antenna will receive reflected chirps before the left-most receive antenna. Similarly, the reflected chirps may be received at different phase angles due to the different travel distances from the origin location of a given reflected chirp. The system may calculate an azimuth angle to the location on the mountainside from which each received reflected chirp originated using the distances between the receiving antennas and (i) the different phase angles at which each receive antenna receives a reflected chirp and/or (ii) the slightly different times at which each receive antenna receives a reflected chirp. The time differences and/or phase angle differences correspond to precise distances, allowing the azimuth angle to be calculated to a high degree of precision using trigonometric identities, triangulation algorithms, multi-antenna angle of detection methods, and the like.
In still other embodiments, multiple transmit antennas may be used to collectively transmit unique RF chirp signals to different portions or subregions of a sloped surface. In such embodiments, reflected chirps may be coarsely identified as originating from one of the different portions or subregions. Higher resolution localization can be performed as described above, by first determining an azimuth from which the reflected signal originates and then determining an elevation based further on time-of-flight measurements and a known topography of the sloped surface.
The detection subsystem 450 is connected to a one-dimensional array of receive antennas 474, including receive antennas 426, 428, and 430. The array of antennas 474 receives reflections of the transmitted RF chirps as reflected chirps 424 from each of a plurality of locations that can each be defined in terms of azimuth and elevation on the sloped surface. For each of a plurality of reflected chirps 424 received by the array of receive antennas 474, the detection subsystem 450 may determine an azimuth of the reflected chirp. In the illustrated example, the receive antenna 426 will receive the reflected chirp 424 earlier and at a different phase angle than, for example, receive antenna 430.
The system may utilize measured phase angle differences and known distances between the various receive antennas 426, 428, and 430 to calculate an azimuth angle at which the reflected chirp 424 is received. In other embodiments, the azimuth angle at which the reflected chirp 424 is received can be determined using triangulation based on the difference in arrival times of the reflected chirp 424 at each of the receive antennas 426-430. Additionally or alternatively, the azimuth angle of the reflected chirp 424 can be determined using the principles and approaches described in “Determining RF Angle of Arrival using COTS Antenna Arrays: A Field Evaluation” by Hseih-Chung Chen, et al., School of Engineering and Applied Sciences, Harvard University (2012), which is hereby incorporated by reference in its entirety.
The detection subsystem 450 may determine an elevation for each reflected chirp 424 based on a time-of-flight of the reflected chirp 424, the azimuth of the reflected chirp 424, and the known distances from the system 420 to each unique location on the target slope. For a given azimuth angle, there is a one-to-one correspondence between distances to the sloped surface and elevation angles. The detection subsystem 450 can determine the distance traveled by the reflected chirp 424 based on the calculated time-of-flight of the reflected chirp 424.
The detection subsystem 450 may also identify a return value associated with each reflected chirp 424. For example, the detection subsystem 450 may identify a power level associated with each reflected chirp 424. In other embodiments, the detection subsystem 450 may alternatively or additionally identify a phase shift associated with each reflected chirp 424. The detection subsystem 450 may generate sequential return value representations of the sloped surface based on reflected chirps 424 from multiple locations on the target slope. Each return value representation comprises a mapping of return value representations to associated azimuths and elevations, or alternatively to associated azimuths and ranges.
In some embodiments, the detection subsystem 450 may generate an imaging representation of the return values. For example, the detection subsystem 450 may generate a two-dimensional image that spatially maps to the target area on the sloped surface with one dimension corresponding to the azimuth and the other dimension corresponding to the elevation. The return values of reflected chirps 424 at each azimuth-elevation coordinate may be represented by letters, numbers, percentages, symbols or the like. In some embodiments, the return values of reflected chirps 424 at each azimuth-elevation coordinate may be represented by different colors or grayscale values. In other embodiments, the system 420 may not present users with visualizations of the return values, in which case the return value representations may comprise a multidimensional data structure, such as a matrix or an array data structure, to facilitate subsequent computer processing.
The system 420 may transmit an RF chirp 412 once every time period, t. During each time period, t, the detection subsystem 450 may process a number, N, of reflected chirps 424 by determining a location (e.g., defined in terms of azimuth and elevation) from which the reflected chirp 424 originated and an associated return value (e.g., a power level or phase shift). The detection subsystem 450 may generate a return value representation every time period, t, in which case each return value representation would include N unique return values.
In another embodiment, the detection subsystem may generate a return value representation every kth time period, where k is a numerical constant, such that each return value representation comprises k*N unique return values. Each return value representation provides a snapshot in time, or a “frame,” of the return values of the reflected chirps received during each kt time period. Changes in return values at a given location from one frame to another indicate movement at that location that modified the return value of reflected chirps at that location.
The detection subsystem 450 may analyze sequences of two or more return value representations to detect motion. Different patterns of motion may be associated with different types of motion events. For example, a pattern of motion may be detected that is identified as leaves blowing in the wind. A different pattern of motion may be associated with movement of a human or animal. Yet another pattern of motion may be associated with vehicle movement. The detection subsystem 450 may distinguish between a human or animal movement and a vehicle based on, for example, the size of the object moving and/or the speed of the movement. The detection subsystem 450 may detect an avalanche or landslide motion event based on the shape of the movement and/or the speed of the movement. For example, the detection subsystem 450 may detect avalanche or landslide motion by comparing frame k with frame k+m, where m is an integer value.
In some embodiments, the detection subsystem 450 may use a set of return value representations to establish baseline return values. For example, the detection subsystem 450 may identify baseline power levels and/or phase shifts associated with steady-state or normal mountainside conditions. The detection subsystem 450 may identify motion in subsequent frames based on power levels and/or phase shifts exceeding the baseline levels and/or exceeding threshold values. For example, steady-state power levels may be normalized to a baseline value 50 on a scale of 0 to 100 in return value representations. Some deviation from the normalized baseline value of 50 may be attributed to noise or minor motion events. However, the detection subsystem 450 may identify received power levels exceeding the baseline values by more than a threshold amount as a motion event.
In some embodiments, certain spatial regions may be associated with a higher likelihood of an avalanche, in which case the detection subsystem 450 may be more likely to classify or categorize a detected motion pattern as an avalanche or landslide. External inputs, such as temperature, wind conditions, time of day, and other environmental data may further guide the detection subsystem 450 in classifying or categorizing a detected motion pattern. For example, if it is windy, detected motion across a large spatial region is more likely to be attributed to tree or leaf movement. If the temperature is reported as 35° C., the detection subsystem 450 may decrease the probability that detected motion is an avalanche. Conversely, if environmental conditions are likely to contribute to avalanches, then the detection subsystem 450 may increase the probability that detected motion is associated with an avalanche.
The system 420 may transmit a communication or otherwise report that a motion event has been detected. In some embodiments, the system 420 may provide a visual, audible, and/or haptic alarm. The system 420 may be configured to report or provide an alarm for some types of detected motion, but not others. For example, the system 420 may identify the motion of skiers descending a ski slope and keep count of the number of skiers in each subregion of a monitored target slope. However, the system 420 may not alarm or report the detected skiers because the motion is expected and acceptable. However, if a motion event is detected that is indicative of an avalanche, the system 420 may trigger an alarm or otherwise report that an avalanche has been detected. The detection subsystem 450 may generate a composite return value representation that shows motion associated with the avalanche over many time periods, t, to provide a visualization of the avalanche movement from the start of the avalanche to the end of the avalanche. Furthermore, the detection subsystem 450 may identify the number of skiers, vehicles, animals, or other detected persons or objects that may be impacted by the avalanche.
The system 421 includes receive antennas 431, 433, and 499 to receive reflected chirps 425. The receive antennas 431, 433, and 499 convert received RF signals to electrical signals that are amplified by low-noise amplifiers (“LNAs”) 437, 439, and 441. In some embodiments, low-pass filters may be utilized in conjunction with or instead of low noise amplifiers 437, 439, and 441. Mixers 445, 447, and 449 receive the amplified reflected chirps and mix them with a function of the electrical chirp signal generated by the transmit frequency generator 451 offset by a fixed frequency from a frequency generator 455. For example, the received reflected signals may be amplified by the LNAs 437, 439, and 441 and mixed with the transmitted electrical chirp signal from the transmit frequency generator 451 offset by a 10 MHz signal generated by the frequency generator 455 (e.g., a local oscillation signal used as a reference signal in the system 421).
The output of the mixers 445, 447, and 449 is a difference signal, or a downconverted chirp. As represented by black dots between receive antennas 433 and 499 and mixers 447 and 449, any greater number of receive antennas and associated mixers may be utilized. In one specific embodiment, two horn antennas are used as transmit antennas 411 and eight microstrip receive antennas in a thinned array are used for the receive antennas 431-499. A corresponding number of LNAs 437-441 and mixers 445-449 may be utilized. Alternatively, received reflected chirps from a large number of receive antennas may be stored temporarily and time-multiplexed through a fewer number of LNAs 437-441 and mixers 445-449.
The mixed signals are digitally converted by analog-to-digital converter (ADC) 461. A processor 471 (or another controller or control system) receives the digitized signals and generates return value representations (e.g., images of the relative power levels of reflected chirps at various calculated locations). The processor 471 may perform various signal processing operations on the information in the digitized signals, for example, as described herein with reference to
The processor 471 may provide control instructions to the transmit frequency generator 451 and the frequency generator 455. For example, the processor 471 may specify the range of frequencies that the transmit frequency generator 451 uses to generate the electrical chirp signal to be transmitted by the transmit antennas 411 as a transmitted RF chirp 413. The processor 471 may also dictate the length of each chirp and the duty cycle or delay between chirps. For example, the processor 471 may provide time periods of transmission and frequencies of transmission to the transmit signal generator 451, such that the transmit frequency generator 451 generates electrical chirp signals to be transmitted by the transmit antennas 411 during specified time periods. The processor 471 may act as a central control unit of the system 421 to implement or cause to be implemented any of the functionalities or methods described herein. For example, the processor 471 may provide instructions for timing the switch 415, such that uniquely distinguishable RF chirps 413 are transmitted by the transmit antennas 411.
The processor 471 may be coupled to a memory 481 that includes instructions to be executed by the processor 471 to implement the various functionalities and methods described herein. In some embodiments, the processor 471 may be omitted and an FPGA, ASIC, and/or other control circuitry may be utilized.
In some embodiments, the system 421 generates the transmitted RF chirp 413 using a Linear Frequency Modulated Continuous Wave (LFMCW) transmit and demodulation routine to transmit a wide band signal that is linearly swept over a bandwidth from a start frequency to an end frequency. For example, the system 421 may transmit an RF chirp 413 with a bandwidth of approximately 100 MHz with the chirp starting at a frequency of 16.01 GHz and finishing at a frequency of 16.11 GHz. The bandwidth of the chirp and the starting and ending frequencies may be adjusted for a particular application, functional range of the system, signal penetration characteristics, or other performance criteria.
In Equation 1, D is the distance between the first receive antenna 525 and the second receive antenna 526. ΔØ is the difference between the phase angles, Ø1 and Ø2, at which the first and second receive antennas 525 and 526 detect the reflected chirp 580. λ is the wavelength of the reflected chirp 580 and θ is the azimuth angle of the reflected chirp 580.
In Equation 2, t corresponds to the time delay between the transmitted RF chirp and the received reflected chirp, c corresponds to the speed of light, and the ris the range. The system 520 may calculate the range, R1, to the location from which the reflected chirp 580 originates and the range, R2, to the location from which the reflected chirp 581 originates.
Traditional imaging systems may utilize mechanically moveable antennas, two-dimensional antenna arrays, and/or other reconfigurable antenna systems to calculate range, azimuth angles, and elevation angles of received signals. However, the presently described systems and methods leverage topographical knowledge of the target slope to allow for complete localization of signals using a one-dimensional array of receive antennas. The system 520 includes a data store or has access to a data store that correlates or allows for the correlation of azimuth angles, ranges, and elevation angles between the system 520 and locations on the target slope 510.
As previously noted, for slopes greater than 0 and less than 90 degrees, there is a one-to-one correlation between ranges and elevation angles for a given azimuth angle. In some embodiments, the system 520 may have topographical information of the target slope 510 in the form of a lookup table that specifies elevation angles for various combinations of azimuth angles and ranges from the system 520 to locations on the target slope. In some embodiments, the lookup table may not include every possible azimuth angle and range combination. In such instances, the system 520 may interpolate an elevation angle for a specific azimuth angle and range combination using combinations of azimuth angles and ranges that are included in the lookup table. In one embodiment, the system 520 may have topographical information of the target slope 510 in the form of a topographical map of the target slope 510 to estimate elevation angles of reflected chirps based on calculated azimuth angles and ranges. For example, the system may utilize known latitude, longitude, and altitude values of locations on the mountainside to compute azimuth, elevation, and distance relative to the system. The values can be used to create a lookup table that can later be referenced to determine elevation values given azimuth and distance calculations.
In situations in which topographical information of a target slope is not known or available to the system 520, the system 520 may generate return value representations as two-dimensional projections of the target slope defined in terms of azimuth and range. Avalanches, landslides, and other motion events may still be detected even though the representations may be spatially distorted.
In various embodiments, the reflected chirp received by the receiver antennas may be mixed with an offset local-oscillator (“LO”) signal 850. The offset LO signal 850 may correspond to the electrical chirp used to transmit the transmitted RF chirp 830 offset by a fixed frequency, such as 10 MHz. The offset LO signal 850 may be selected based on the capabilities of an ADC.
The motion detection routines described herein may utilize RF chirps and a corresponding offset LO signal, and process reflected chirps from a target area of a mountain slope to generate azimuth, range, and/or elevation information for the detection of motion events, such as avalanches, landslides, or the like. As discussed herein, the detection system may include an antenna array with a fixed alignment along the azimuth axis, the axis parallel to the plane of the antenna array alignment.
The system may transmit, at 904, electromagnetic energy to a sloped surface, such as a mountain slope. The mountain slope may, for example, be snow covered and susceptible to an avalanche. In other instances, the mountain slope may include rocks, mud, ice, water or other objects that may susceptible to sliding (e.g., a landslide). The electromagnetic energy may be a RF chirp transmitted by one or more transmit antennas. The mountain slope may reflect some of the transmitted RF chirps as reflected chirps.
The system may mix, at 908, the received electromagnetic energy with a transmit pulse and an offset LO signal to obtain a downconverted difference signal. The system may sample, at 912, the downconverted difference signal to generate discrete pulse data for processing via a processor, ASIC, FPGA, or the like. For example, the system may sample, at 912, the downconverted difference signal via an ADC, to convert the analog, downconverted difference signal into digitized sampled values (samples).
The system may range compress, at 916, the samples for each pulse using a Fast Fourier Transform (“FFT”) or other processing routine to generate range and azimuth information. The system implements an effective digital beamforming, at 920, to generate representations of the physical target in a range domain or an azimuth domain. For example, in a uniformly spaced array of antennas, an FFT along the azimuth axis forms multiple azimuth signals in equally spaced angles in relation to the boresight of the antennas. As another example, in a sparse, non-uniformly spaced array of antennas, multiple azimuth signals are formed by multiplying the phase information of each pulse data with a constant that can be calculated using an azimuth angle.
The system may implement digital beamforming, at 920, on the multiple receive channels to generate a two-dimensional image of the slope. For example, when the azimuth signals are multiplied and summed together, the angle of arrival of the target may be calculated. In some implementations, a three-dimensional image may also be generated by converting the channel axis to the azimuth axis. Accordingly, a three-dimensional image may include axes for azimuth, range, and time. A sequence of two-dimensional projections of the mountain slope can be stepped through in time to visualize motion on the slope over time.
In some embodiments, the signal-to-noise-ratio (“SNR”) may be improved by integrating, at 924, successive pulses together. For example, integrating successive pulses may be accomplished, coherently, in averaging phase coherent pulses together after digital beamforming. As another example, integrating successive pulses may be accomplished, incoherently, in identifying the magnitude of the pulses to be utilized in the averaging of the pulses. However, incoherent integration may eliminate the phase information from the successive pulses. After averaging the successive pulses, the successive pulses may be referred to as aggregated successive pulses.
The system may determine differences, at 928, of the aggregated successive pulses, for example, to isolate movement in the target area. The reflected chirps or received electromagnetic energy may include returns from objects outside the target area (e.g., a range near the device) or from stationary objects, including higher power returns from nearby objects. To remove that higher power return, the consecutive pulses can be differenced from each other to zero-out the power return from the stationary objects and/or from the near-range objects. As another example, the processor may utilize a high pass filter to remove the portion of the frequency domain that does not exhibit return value variations over time. A high pass filter may also eliminate higher power returns from stationary objects to highlight moving objects, such as an avalanche or other moving objects.
The system may detect, at 936, spatial power returns that exceed a minimum power detection threshold. The system may generate a sequence of image representations of changes to power returns (or phase shifts) on the slope. Stepping through the sequence of image representations allows for motion on the slope to be visualized. The system may detect patterns of power returns or phase shifts indicative of specific, identifiable motion events, such as landslides or avalanches. The system may transmit, at 940, notifications of detected motion events.
This disclosure has been made with reference to various examples and embodiments, including the best mode. However, those skilled in the art will recognize that changes and modifications may be made to the exemplary embodiments without departing from the scope of the present disclosure. While the principles of this disclosure have been shown in various embodiments, many modifications of structure, arrangements, proportions, elements, materials, and components may be adapted for a specific environment, application, and/or operation parameters without departing from the principles and scope of this disclosure. These and other changes or modifications are intended to be included within the scope of the present disclosure.
This disclosure is to be regarded in an illustrative rather than a restrictive sense, and all such modifications are intended to be included within the scope thereof. Likewise, benefits, other advantages, and solutions to problems have been described above with regard to various embodiments. However, benefits, advantages, solutions to problems, and any element(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or element. This disclosure should be determined to encompass at least the following claims.
This application is a continuation of U.S. Non-Provisional patent application Ser. No. 16/735,365 titled “Systems and Methods to Detect Motion of Sloped Surfaces,” filed on Jan. 6, 2020 and issuing on Aug. 2, 2022 as U.S. Pat. No. 11,402,483, which claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application 62/789,191, filed Jan. 7, 2019 titled “Radar Devices and Systems Including Examples of Avalanche Detection,” which application is hereby incorporated by reference in its entirety. This application may be further understood in the context of and with comparison to U.S. patent application Ser. No. 13/149,881, filed on May 31, 2011, titled “Method, Apparatus, and System to Remotely Acquire Information from Volumes in a Snowpack,” granted as U.S. Pat. No. 8,581,772, which application is hereby incorporated by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
4300121 | Fritzsche | Nov 1981 | A |
4435709 | Kipp | Mar 1984 | A |
4527161 | Wehner | Jul 1985 | A |
4649390 | Andrews | Mar 1987 | A |
4961075 | Ward | Oct 1990 | A |
5245347 | Bonta | Sep 1993 | A |
5831570 | Ammar | Nov 1998 | A |
6311108 | Ammar | Oct 2001 | B1 |
6362775 | Goebel | Mar 2002 | B1 |
6430480 | Ammar | Aug 2002 | B1 |
6591171 | Ammar | Jul 2003 | B1 |
7002510 | Choate | Feb 2006 | B1 |
7196653 | Hall | Mar 2007 | B2 |
7277042 | Cho | Oct 2007 | B1 |
8686892 | McCleary | Apr 2014 | B2 |
9229102 | Wright | Jan 2016 | B1 |
9518830 | Breed | Dec 2016 | B1 |
9529082 | Rikoski | Dec 2016 | B1 |
9857453 | DeSimone, Jr. | Jan 2018 | B1 |
10139492 | Rezk | Nov 2018 | B2 |
20040040764 | Polak | Mar 2004 | A1 |
20040046690 | Reeves | Mar 2004 | A1 |
20040233098 | Millikin | Nov 2004 | A1 |
20050104763 | Hall | May 2005 | A1 |
20070063889 | Hulbert | Mar 2007 | A1 |
20070126620 | Channabasappa | Jun 2007 | A1 |
20090184865 | Valo | Jul 2009 | A1 |
20090232349 | Moses | Sep 2009 | A1 |
20090278732 | Antonik | Nov 2009 | A1 |
20100019950 | Yamano | Jan 2010 | A1 |
20100045513 | Pett | Feb 2010 | A1 |
20110074621 | Wintermantel | Mar 2011 | A1 |
20110285581 | Hol | Nov 2011 | A1 |
20120056780 | Antonik | Mar 2012 | A1 |
20120068877 | Stayton | Mar 2012 | A1 |
20120146846 | Antonik | Jun 2012 | A1 |
20130088383 | Forstner | Apr 2013 | A1 |
20150301167 | Sentelle | Oct 2015 | A1 |
20160025489 | Klepsvik | Jan 2016 | A1 |
20160116574 | Joubert | Apr 2016 | A1 |
20160131742 | Schoor | May 2016 | A1 |
20160259038 | Retterath | Sep 2016 | A1 |
20160259043 | Schär | Sep 2016 | A1 |
20170072851 | Shenoy | Mar 2017 | A1 |
20170076599 | Gupta | Mar 2017 | A1 |
20170115384 | Loesch | Apr 2017 | A1 |
20170285158 | Halbert | Oct 2017 | A1 |
20180011180 | Warnick | Jan 2018 | A1 |
20180253151 | Kletsov | Sep 2018 | A1 |
20180259641 | Vacanti | Sep 2018 | A1 |
20180275252 | Fried | Sep 2018 | A1 |
20190018143 | Thayer | Jan 2019 | A1 |
20190064338 | Holt | Feb 2019 | A1 |
20190184962 | Gierling | Jun 2019 | A1 |
20200345274 | Ghoshal | Nov 2020 | A1 |
Number | Date | Country |
---|---|---|
2008125929 | Oct 2008 | WO |
WO-2008125929 | Oct 2008 | WO |
Entry |
---|
Chen, Hsieh-Chung, et al., Determining RF Angle of Arrival using COTS Antenna Arrays: A Field Evaluation, School of Engineering and Applied Sciences, Harvard University, 2012, 6 pp. |
U.S. Appl. No. 16/735,365, Non-Final Office Action dated Nov. 19, 2021, 59 pp. |
U.S. Appl. No. 16/735,365, Notice of Allowance dated Mar. 29, 2022, 18 pp. |
Number | Date | Country | |
---|---|---|---|
20220373668 A1 | Nov 2022 | US |
Number | Date | Country | |
---|---|---|---|
62789191 | Jan 2019 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 16735365 | Jan 2020 | US |
Child | 17815498 | US |