Adaptive filtering for FMCW interference mitigation in PMCW radar systems

Information

  • Patent Grant
  • 10976431
  • Patent Number
    10,976,431
  • Date Filed
    Thursday, May 31, 2018
    6 years ago
  • Date Issued
    Tuesday, April 13, 2021
    3 years ago
Abstract
A radar sensing system for a vehicle includes a transmitter and a receiver. The transmitter is configured for installation and use on a vehicle. The transmitter is configured to transmit radio signals. The receiver is configured for installation and use on the vehicle. The receiver is configured to receive radio signals that include (i) the transmitted radio signals transmitted by the transmitter and reflected from objects in an environment, and (ii) other radio signals that include radio signals transmitted by at least one other radar sensing system. The receiver is configured to filter frequency modulated continuous wave (FMCW) radio signals from the received radio signals to produce filtered radio signals. The receiver is further configured to select between (i) the filtered radio signals, and (ii) the received radio signals before filtering. The filtered radio signals are selected when the other radio signals include FMCW radio signals.
Description
FIELD OF THE INVENTION

The present invention is directed to radar systems, and more particularly to radar systems for vehicles.


BACKGROUND OF THE INVENTION

The use of radar to determine range and velocity of objects in an environment is important in a number of applications including automotive radar and gesture detection. A radar system typically transmits radio signals and listens for the reflection of the radio signals from objects in the environment. By comparing the transmitted radio signals with the received radio signals, a radar system can determine the distance to an object. Using multiple transmissions, the velocity of an object can be determined. Using multiple transmitters and receivers, the location (angle) of an object can also be determined.


There are several types of signals used in different types of radar systems. One type of radar signal is known as a frequency-modulated continuous waveform (FMCW). In an FMCW radar system, the transmitter of the radar system sends a continuous signal in which the frequency of the signal varies. This is sometimes called a chirp radar system. Mixing (multiplying) the reflected wave from an object with a replica of the transmitted signal results in a CW signal with a frequency that represents the distance between the radar transmitter/receiver and the object. By sweeping up in frequency and then down in frequency, the Doppler frequency can also be determined.


Another type of radar signal is known as a phase-modulated continuous waveform (PMCW). For this type of radio signal, the phase of the transmitted signal is modulated according to a certain pattern or code, sometimes called the spreading code, known at the PMCW radar receiver. The transmitted signal is phase modulated by mixing a baseband signal (e.g., with two values +1 and −1) with a local oscillator to generate a transmitted signal with a phase that is changing corresponding to the baseband signal (e.g., +1 corresponding to a phase of 0 radians and −1 corresponding to a phase of π radians). For a single transmitter, a sequence of phase values that form the code or spreading code that has good autocorrelation properties is required so that ghost objects are minimized. The rate at which the phase is modulated determines the bandwidth of the transmitted signal and is called the chip rate.


In a PMCW radar system, the receiver performs correlations of the received signal with time-delayed versions of the transmitted signal and looks for peaks in the correlation. The time-delay of the transmitted signal that yields peaks in the correlation corresponds to the delay of the transmitted signal when reflected off an object. The distance to the object is found from that delay and the speed of light.


A PMCW radar will receive not only the reflected signals from the transmitter of the PMCW radar. A PMCW radar operating in the presence of an FMCW radar will also receive the signals from the FMCW radar. The signal from the FMCW radar can significantly affect the performance of a conventional PMCW radar system. Potentially, these FMCW signals can be much stronger than the reflected signals from the PMCW radar. This may cause the radar system's estimated range, velocity and direction to be significantly in error.


SUMMARY OF THE INVENTION

The present invention provides methods and a system for achieving better performance in a radar system using phase-modulated continuous wave (PMCW) radar when there are one or more other radar systems using a frequency-modulated continuous wave (FMCW) type of radar transmission and operating simultaneously. The invention accomplishes better detectability of a PMCW radar object by applying a filtering technique to the received radio signal that mitigates the effect of an interfering FMCW radar on the PMCW radar. Another source of potential interference is clock harmonics. The same techniques that are described below for FMCW interference mitigation will also work on clock harmonics.


A radar sensing system for a vehicle in accordance with an embodiment of the present invention includes at least one transmitter, at least one receiver, a memory, and a processor. The at least one transmitter is configured for installation and use on a vehicle and further operable or configured to transmit a radio frequency (RF) signal. The at least one transmitter is further operable or configured to transmit an RF signal using a phase modulated signal. The transmitted RF signal is generated by up-converting a baseband signal. The at least one receiver is configured for installation and use on the vehicle and further operable or configured to receive an RF signal. The received RF signal includes the transmitted RF signal reflected from multiple objects in the environment and potentially radio signals from other radars such as a frequency modulated continuous wave (FMCW) radar transmitter. The received RF signal is down-converted and sampled. The sampled result is provided to a processor. The processor selectively applies an adaptive filter to the received RF signal to mitigate the effect of an interfering waveform from a radar transmitting an FMCW radio signal. After adaptively filtering the received RF signal, the radar performs correlations with various delayed versions of the baseband transmitted signal. The correlations are used to determine an improved range, velocity and angle of objects in the environment.


A radar sensing system for a vehicle in accordance with an embodiment of the present invention includes at least one transmitter, at least one receiver, a memory, and a processor. The at least one transmitter is configured for installation and use on a vehicle and transmits a radio frequency (RF) signal. The at least one transmitter phase modulates the transmitted RF signal using codes generated by at least one of a pseudo-random sequence generator and a truly random number generator. The at least one receiver is configured for installation and use on the vehicle and further operable or configured to receive an RF signal. The received RF signal includes the transmitted RF signal reflected from an object. In addition, the received RF signal may also include radio signals transmitted from one or more other radar systems, for example an FMCW radar. A down-converted received RF signal is sampled and provided to a processor. The processor selectively and adaptively filters the sampled signal to mitigate the effect of the FMCW radar on the PMCW radar system and then estimates the range, velocity and angle of objects in the environment.


A radar sensing system for a vehicle in accordance with an embodiment of the present invention includes at least one transmitter, at least one receiver, a memory, and a processor. The at least one transmitter is configured for installation and use on a vehicle and transmits a radio frequency (RF) signal. The at least one receiver is configured for installation and use on the vehicle and further operable or configured to receive an RF signal containing signals reflected from the transmitted signal as well as signals from one or more other radar systems. The reflected RF signal is the transmitted RF signal reflected from objects in the environment of the radar system. The radio signals from one or more other radar systems may be from an FMCW type of radar. A down-converted received RF signal is sampled and provided to a processor. The processor selectively filters out the interference from the FMCW radar system in an adaptive manner.


The radar system may include in the receiver a mechanism for deciding when to employ the cancellation (filtering) processing. The decision could be based on measuring the root mean square value (i.e., magnitude) of both the input and the output of the adaptive filter. The decision to filter could also be based on additional information such as obtained from other receivers in the radar system.


These and other objects, advantages, purposes and features of the present invention will become apparent upon review of the following specification in conjunction with the drawings.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a plan view of an automobile equipped with one or more radar systems in accordance with the present invention;



FIG. 2 is a block diagram illustrating a radar system with a plurality of receivers and a plurality of transmitters in accordance with the present invention;



FIGS. 3 and 4 illustrate aspects of how PMCW digital radar works;



FIG. 5 is a block diagram illustrating the basic processing blocks of a transmitter and receiver in a radar system in accordance with the present invention;



FIG. 6 is a block diagram illustrating an exemplary baseband signal processor in accordance with the present invention;



FIG. 7 is a block diagram illustrating an interference mitigation processor in accordance with the present invention;



FIG. 8 is a block diagram illustrating the adaptive filter of FIG. 7 in accordance with the present invention;



FIG. 9 is an exemplary plot of an output of a correlator without any external interference in the case of two objects in the environment in accordance with the present invention;



FIG. 10 is an exemplary plot of an output of a correlator with a fixed frequency external interferer without the adaptive mitigation processing in accordance with the present invention;



FIG. 11 is an exemplary plot of an output of a correlator with a fixed frequency external interferer with adaptive mitigation processing in accordance with the present invention;



FIG. 12 is an exemplary plot of an output of a correlator without any external interference in the case of two objects in the environment and spreading codes of length 1023 in accordance with the present invention;



FIG. 13 is an exemplary plot of an output of a correlator with a chirp type external interferer without the adaptive mitigation processing in accordance with the present invention; and



FIG. 14 is an exemplary plot of an output of a correlator with a chirp type external interferer with adaptive mitigation processing in accordance with the present invention.





DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention will now be described with reference to the accompanying figures, wherein numbered elements in the following written description correspond to like-numbered elements in the figures. Methods and systems of the present invention may achieve better performance from a radar system in the presence of a simultaneously operating FMCW radar by applying an adaptive filter to the down-converted and sampled received RF signal at one or more of the receivers in a radar system. The adaptive filtering may be selectively applied based on a measurement of the interference as well by considering other factors or conditions.


A radar system utilizes one or more transmitters to transmit signals. These signals are reflected from objects (also known as targets) in the environment and received by one or more receivers of the radar system. A transmitter-receiver pair is called a virtual radar (or sometimes a virtual receiver).


The transmitted radio signal from each radar transmitter consists of a baseband transmitted signal, which is up-converted to an RF signal by an RF upconverter. The up-converted RF signal may be obtained by mixing the baseband transmitted signal with a local oscillator signal at a carrier frequency. The baseband transmitted signal used for transmission by one transmitter of the radar system might be phase modulated using a series of codes. These codes, for example, consist of repeated sequences of random or pseudo-random binary values for one transmitter, e.g., (−1, −1, −1, −1, 1, 1, 1, −1, 1, 1, −1, −1, 1, −1, 1), although any sequence, including non-binary sequences and non-periodic sequences could be used and different sequences could be used for phase modulating the outputs of different transmitters. Each value of the phase modulation code sequence is often called a chip. A chip would last a certain duration called the chip time. The inverse of the chip time is the chip rate. That is, the chip rate is the number of chips per second. In an exemplary aspect of the present invention, the sequences of random binary values may be provided by a truly random number generator. A truly random number generator is explained in more detail in U.S. Pat. No. 9,575,160, which is hereby incorporated by reference herein in its entirety. The random bit stream (with values +1 or −1) from the truly random number generator may be multiplied with an output of pseudorandom binary values from a pseudorandom number generator (PRNG).


The transmitted radio signals are reflected from objects in the environment and are received back at the radar receivers (or virtual receivers). Each object in the environment may reflect the transmitted radio signal. The received radio signal at the radar system would consist of the sum of the radio signals reflected from various objects (targets) in the environment. In addition, a second radar system operating in the vicinity of the first radar system will generate a transmitted radio signal that may be received by the first radar system and interfere with the reflected radio signals from the first radar system. In other words, the first radar system would receive radio signals that include radio signals from transmitters of the first radar system that are reflected from objects in the environment, as well as radio signals transmitted by one or more other radar systems.


At the receiver (receive pipeline) of the radar system, the received radio signal is down-converted by typical amplification, filtering, and mixing with in-phase and quadrature-phase components of an oscillator. The output after down-conversion and sampling is a sequence of complex value digitized samples comprising a mathematical real component and a mathematical imaginary component that are provided to a processor. The baseband signals used at the transmitter and the reflected radio signals after down-conversion in the receiver are provided to correlators. The complex valued digitized samples at the output of the down-converter are correlated with various time-delayed replicas of the baseband transmitted signals for different receivers to produce complex correlation values over a certain duration. That is, a sequence of digitized samples that correspond to a certain time duration of the received signal are correlated with a time-delayed replica of the baseband transmitted signal. The process is repeated for subsequent samples, thus producing a sequence of complex correlation values for a given time-delay. This process is also performed for different transmitter/receiver pairs (virtual receivers).


A selected correlator that has a replica that is matched in delay to the time delay of the reflected radio signal from an object will produce a large magnitude complex correlator output. A single correlator will produce a sequence of correlator outputs that are large if the reflected signal has a delay that matches the delay of the replica of the baseband transmitted signal. If the velocity of the radar system is different from the velocity of the object causing the reflection, there will be a Doppler shift in the frequency of the reflected signal relative to the transmitted signal. A sequence of correlator outputs for one particular delay corresponding to an object moving in the environment will have complex values that rotate at a rate related to the Doppler shift. Using a sequence of correlator outputs (also referred to as a scan), the Doppler shift may be estimated, and thus the velocity of the object in the environment determined. The longer the sequence of correlator outputs used to estimate the Doppler frequency, the greater the accuracy and resolution of the estimation of the Doppler frequency, and thus the greater the accuracy in estimating the velocity of the object.


The correlation values for various time delays and various virtual radars are arranged in two-dimensional arrays known as time slices. A time slice is a two-dimensional array with one dimension corresponding to delay or range bin and the other dimension corresponding to the virtual radar (transmitter-receiver pair). The samples are placed into respective range bins of the two-dimensional array (as used herein, a range bin refers to a distance range corresponding to a particular time delay corresponding to the round-trip time of the radar signal from a transmitter, to the target/object, and back to the receiver). The virtual receivers of the radar system define one axis of the two-dimensional time slice and the range bins define the second axis of the two-dimensional time slice. Another new time slice comprising complex correlation values is generated every 2-30 microseconds. Over a longer time interval, herein referred to as a “scan” (typically, in a duration of 1-60 milliseconds or longer), multiple time slices are accumulated to form a three-dimensional radar data cube. One axis or dimension of the three-dimensional radar data cube is defined by time (of each respective time slice requiring 2-30 microseconds), while the receivers (or virtual radar) define a second axis of the three-dimensional radar data cube, and the range bins and their corresponding time delays define a third axis of the three-dimensional radar data cube. A radar data cube may have a preselected or dynamically defined quantity of time slices. For example, a radar data cube may include 100 time slices or 1000 time slices of data. Similarly, a radar data cube may include different numbers of range bins. The optimized use of radar data cubes is described in detail in U.S. Pat. No. 9,599,702, which is hereby incorporated by reference herein in its entirety.


A single correlator output corresponding to a particular range bin (or delay) is a complex value that corresponds to the sum of products between a time-delayed replica of the baseband transmitted signal—with a time-delayed replica corresponding to each range bin—and the received down-converted complex samples. When a particular time-delayed replica in a particular range bin correlates highly with the received signal, it is an indication of the time delay (i.e., range of the object) for the transmitted radio signal that is received after the transmitted radio signal reflects from an object. Multiple correlators produce multiple complex correlation values corresponding to different range bins or delays. As discussed herein, each time slice contains one correlation value in a time series of correlation values upon which Doppler processing is performed (e.g., Fast Fourier Transform). In other words, a time series of complex correlation values for a given range bin is used to determine the Doppler frequency and thus the velocity of an object in the range bin. The larger the number of correlation values in the time series, the higher the Doppler resolution. A matched filter may also be used to produce a set of outputs that correspond to the correlator outputs for different delays.


There may be scans for different correlators that use replicas of the transmitted signal with different delays. Because there are multiple transmitters and multiple receivers, there may be correlators that process a received radio signal at each receiver that are matched to a particular transmitted radio signal by a particular transmitter. Each transmitter-receiver pair is called a “virtual radar” (a radar system preferably has 4 virtual radars, or more preferably 32 virtual radars, and most preferably 256 or more virtual radars). The receive pipeline of the radar system will thus generate a sequence of correlator outputs (time slices) for each possible delay and for each transmitter-receiver pair. This set of data is called a radar data cube (RDC). The delays are also called range bins. The part of the radar data cube for one point in the sequence of correlator outputs is called a time slice, and it contains one correlator output for each range bin and transmitter-receiver pair combination.


The complex-valued correlation values contained in a three-dimensional radar data cube may be processed, preferably by a processor established as a CMOS processor and coprocessor on a semiconductor substrate, which is typically a silicon substrate. In one embodiment, the processor comprises fixed function and programmable CPUs and/or programmable logic controls (PLCs). Preferably, the system will be established with a radar system architecture (including, for example, analog RF circuitry for the radar, processor(s) for radar processing, memory module(s), and other associated components of the radar system) all on a common semiconductor substrate. The system may preferably incorporate additional processing capabilities (such as, for example, image processing of image data captured by one or more vehicle cameras such as by utilizing aspects of the systems described in U.S. Pat. Nos. 5,877,897; 5,796,094; 6,396,397; 6,690,268 and 5,550,677, which are hereby incorporated herein by reference in their entireties) within the same semiconductor substrate as well.


The ability of a continuous wave radar system to distinguish multiple targets is dependent upon the radar system's range, angle, and Doppler resolutions. Range resolution is limited by a radar's bandwidth (i.e., the chip rate in a phase modulated continuous wave radar), while angle resolution is limited by the size of the antenna array aperture. Meanwhile, increasing Doppler resolution only requires a longer scan. A high Doppler resolution is very valuable because no matter how close two objects or targets are to each other, as long as they have slightly differing radial velocity (their velocity towards or away from the radar system), they can be distinguished by a radar system with a sufficiently high enough Doppler resolution. As discussed herein, the detection of objects with a PMCW radar system may be adversely effected by the nearby operation of one or more frequency modulated continuous wave (FMCW) radar systems.



FIG. 1 illustrates an exemplary radar system 100 configured for use in a vehicle 150. In an aspect of the present invention, a vehicle 150 may be an automobile, truck, or bus, etc. As illustrated in FIG. 1, the radar system 100 may comprise one or more transmitters and one or more receivers 104a-104d for a plurality of virtual radars. Other configurations are also possible. As illustrated in FIG. 1, the radar system 100 may comprise one or more receivers/transmitters 104a-104d, control and processing module 102 and indicator 106. Other configurations are also possible. FIG. 1 illustrates the receivers/transmitters 104a-104d placed to acquire and provide data for object detection and adaptive cruise control. The radar system 100 (providing such object detection and adaptive cruise control or the like) may be part of an Advanced Driver Assistance System (ADAS) for the automobile 150.



FIG. 2 illustrates the structure of an exemplary radar system 200 containing one or more transmitting antennas 201, one or more receiving antennas 202, one or more transmitters 203, one or more receivers 204, memory modules 205, 206, as well as interfaces to other parts of a vehicle system via various types of networks 207, such as Ethernet, CAN-FD, or FlexRay. There may also be processing capability contained in the ASIC 208 apart from the transmitters 203 and receivers 204.


The radar sensing system of the present invention may utilize aspects of the radar systems described in U.S. Pat. Nos. 9,772,397; 9,753,121; 9,575,160 and/or 9,599,702, and/or U.S. provisional applications, Ser. No. 62/382,857, filed Sep. 2, 2016, Ser. No. 62/381,808, filed Aug. 31, 2016, Ser. No. 62/327,003, filed Apr. 25, 2016, Ser. No. 62/327,004, filed Apr. 25, 2016, Ser. No. 62/327,006, filed Apr. 25, 2016, Ser. No. 62/327,015, filed Apr. 25, 2016, Ser. No. 62/327,016, filed Apr. 25, 2016, Ser. No. 62/327,017, filed Apr. 25, 2016, Ser. No. 62/327,018, filed Apr. 25, 2016, and/or Ser. No. 62/319,613, filed Apr. 7, 2016, which are all hereby incorporated by reference herein in their entireties.



FIG. 3 illustrates the basic waveforms of a PMCW radar. Depending on the baseband signal, one of two phases of a sinusoidal signal are generated. In a binary system, one of two phases of a sinusoidal signal are generated, typically 0 degrees and 180 degrees. This also corresponds to transmitting a signal or the opposite of that signal when the binary baseband chip is a 0 or a 1. More than two phases could be used if the baseband signal is not binary.


The transmitted radio signal is then a sequence of sinusoidal signals with different phases as illustrated in FIG. 4. Each phase lasts T, seconds, which is called the chip time. The inverse of the chip time is the chip rate, which is measured in chips per second. The chip rate might be on the order of 500 Mbps.


Also illustrated in FIG. 4 is the received radio signal that is due to a reflection of the transmitted radio signal from an object. The received radio signal (that includes the transmitted radio signal reflected from an object in the environment) will have the same basic shape as the transmitted radio signal but will be delayed by an amount corresponding to the round-trip time for the radio signal to propagate from the transmitter, to reflect from the object, and then back to be received by the receiver.



FIG. 5 illustrates an exemplary block diagram of a transmitter 500 in a radar system and an exemplary block diagram of a receiver 550 in the radar system. There may be more than one transmitter 500 and more than one receiver 550 in the radar system. A baseband signal is generated by a base band signal generator 510 which outputs digital signal samples that are used to form a baseband signal. These samples could be complex samples, representing the in-phase (I) and quadrature-phase (Q) baseband signals. These samples are used as the input to a digital-to-analog converter (DAC), represented as block 520. The baseband analog signal at the output of the DAC is used as the input to the up-converter 530 which generates the RF signal for transmission through the transmit antenna 540. The received radio signal from the receiver antenna 560 is down-converted in an exemplary down-converter module 570, and sampled and quantized in an exemplary analog-to-digital converter (ADC) 580. The down-converted signals might be complex (or a pair of real signals) representing the in-phase (I) and quadrature-phase (Q) of the RF signal. The output of the ADC 580 is processed by the baseband processing unit 590. The baseband processing unit 590 will be aware of the baseband transmitted signal output from the baseband signal generator 510. Optionally, the baseband signal generator 510 and the baseband signal processor 590 may be combined into a single processor 510/590. There may be multiple baseband processing units 590 for a given ADC output that correspond to different transmitters (e.g., in a MIMO radar system, with multiple transmitters and multiple receivers). That is, for one receiver there may be a baseband processing unit that uses the baseband signal of a first transmitter and another baseband processing unit that uses the baseband signal of a second transmitter.


Aspects of the present invention are concerned with the baseband signal processing unit 590 of the receiver 550. Because there may be signal interference from one or more radar systems of the FMCW-type, the output of the ADC 580 at the receiver 550 may include an interfering frequency-modulated radio signal in addition to the desired radio signal that has been generated by the PMCW radar system transmitter, reflected off of objects in the environment, and then received for processing by the receiver 550. Mitigating interference from FMCW-type radar systems is the subject of this invention. In one aspect of the present invention, an adaptive filter is used to remove the interfering FMCW interference. However, it is possible that there are no waveforms from FMCW-type radar systems present (or that those waveform(s) are present, but below a threshold level), in which case there is no need to adaptively filter the received radio signal. As illustrated in FIG. 6, exemplary baseband signal processor 590 includes an FMCW mitigation module 610, followed by a correlation and FFT processing module 620 that provides further processing, such as a correlation to determine the range bin (distance) of an object, and an FFT to determine the velocity (or Doppler shift) of the object. An input to the FMCW mitigation module 610 is the output of the ADC 580. The results of the baseband processing for one receiver are combined with other similar receivers to perform an angle-of-arrival estimation of an object. The baseband processing unit 590 of one receiver 550 may be combined with the baseband processing of other receivers 550.


Baseband signal processor (590) will first adaptively filter the complex digitized sample with a least mean square (LMS) type of adaptive filter. An LMS filter is a well-known example of an adaptive filter that finds a difference between an input and an output, and using an error function and previous filter coefficients, determines updated filter coefficients. Exemplary LMS adaptation equations are illustrated below. The notation uses bold values for vectors. The vector wn=represents the vector of L tap weights. The vector xn represents the last L inputs xn=(xn,xn−1, . . . ,xn−L+1). The step size parameter is denoted as μ. A leakage coefficient a is chosen between 0 and 1.

wn+1=awn+μenxn
en=xn−yn
yn=wnTxn



FIG. 8 illustrates an exemplary block diagram of an adaptive filter 710. The adaptive filter of FIG. 8 includes a finite impulse response (FIR) filter 810 with L taps, an error calculator 820, and a weight update calculator 830. The FIR filter output is a correlation of the contents of a shift register with a weight vector w. The difference between the filter output and the input is an error signal. This is also the output of the mitigation filter. The error signal, the current input of complex samples, and the current set of weights used for the FIR filter, are used to update the set of weights of the FIR filter. In other words, the error signal is the output of the adaptive filter process. The eventual goal of the adaptive filter process will be to have removed much of the FMCW interference from the input of the filter.


The complex signal at the output of the interference mitigation filter will have reduced effect due to the interfering FMCW signal. As illustrated in FIG. 6, this mitigation filter output is correlated with the spreading code corresponding to one or more desired transmitters. After adaptively filtering the received radio signal, correlations with various delayed versions of the transmitted baseband signal are performed in the correlation, FFT processing module 620.



FIG. 9 illustrates an output of a matched filter when there are two objects in the environment but no other radar system operating. The exemplary transmitted radio signal is transmitting 8 periods of an m-sequence of length 255 with a chip rate of 500M chips/second. The received radio signal is down-converted, sampled, and used as the input to a matched filter where the filter is matched to one period of the m-sequence of length 255. A matched filter is a method of correlating the received signal with all possible delays of the transmitted sequence. The output has 8 large spikes corresponding to a near object for each period of the m-sequence transmitted. FIG. 9 also illustrates that there are also 8 smaller amplitude spikes corresponding to a more distant target/object.



FIG. 10 illustrates an output of the same matched filter when, in addition to the two objects in the environment, there is a tone jammer with fixed frequency (which is similar to an FMCW radar system) that interferences with the reflected radio signals reflecting off of the objects. The output of the tone jammer, illustrated in FIG. 10 is used to simulate an interfering FMCW radar system. While the large spikes due to the radio signal reflecting off of the near object are still visible and detectable, the spikes due to the more distant object are sometimes lower than the signal due to the interference. Here, the interference is assumed to be 4 times (12 dB) larger than the desired signal from the nearer object.



FIG. 11 illustrates an output of the same matched filter when prior to performing the matched filtering, adaptive interference cancelling is done as described above. As illustrated in FIG. 11, the adaptive filter effectively removes the undesired signal(s) and now signals reflected from both the nearby object and from the more distant object are clearly visible.


As another example, consider a radar system that transmits 4 periods of a spreading code of length 1023 with a chip rate of 500M chips/s. There are two objects in the environment. FIG. 12 illustrates an exemplary filter output when there is no signal interference (e.g., from an FMCW radar or equivalent) in the signal input and no adaptive filtering performed by the adaptive filter 710. FIG. 13 illustrates an exemplary filter output when there is interference from another radar system, such as an FMCW radar that acts as a jammer. This FMCW radar transmits a chirp signal, which is a tone which varies in frequency. FIG. 13 further illustrates the effect of interference from an FMCW radar in the absence of any adaptive filtering. FIG. 13 also illustrates the output of a matched filter when the tone or chirp signal from the interfering FMCW radar has 20 dB larger amplitude than the desired return signals from the objects. As illustrated in FIG. 13, the second object (the more distant object) becomes buried in the interfering FMCW radar signal. When an adaptive filter is employed, as described herein, the interference from the FMCW radar may be significantly reduced so that the radio signal reflected from the second, weaker object is visible. This is illustrated in FIG. 14, where even when an input signal includes interference from an FMCW-type radar system, adaptive filtering has removed the majority of the interference so that the radio signal reflected from the second, weaker object is not buried in the interference.


In some cases, there is not another radar transmitting an FMCW-type of signal or the signal from an interfering FMCW-type radar is small in amplitude. In such a case, it is not useful to try to remove the nonexistent interference. As illustrated in FIG. 7, a selection mechanism 730 and controller 720 may be used to bypass the adaptive filtering (as performed by the adaptive filter 710). The selection mechanism 730 and controller 720 may also be referred to as a bypass mechanism. By default, the received radio signal bypasses the adaptive filter 710 without any cancelation/filtering. As illustrated in FIG. 7, the input radio signal to the adaptive filter 710 is also received by the selection mechanism 730 and a controller 720. To determine when to use the adaptive filter output and when to use the unfiltered input signal, a measurement of the root mean square (RMS) signal amplitude before and after cancelation/filtering may be performed by the controller 720 and a ratio of the RMS amplitude of the filter output to the RMS amplitude of the filter input is calculated. If the ratio is smaller than a selected threshold value, the adaptive filter's output, with the signal interference removed, is used. If the ratio is larger than the selected threshold value, the output of the adaptive filter is not selected for use, instead, the unfiltered input signal is used.


By default, the switch 730 that determines whether to employ the adaptive filtering can be set by the controller 720 to pass the received complex samples without any filtering. While a filter output is generated by the adaptive filter 710, the unfiltered signal is selected by the switch 730, as controlled by the controller 720.


An alternative to this automatic determination of whether to employ or bypass the interference canceller, software can be used to decide whether to use the adaptive filter, where the decision is based not only on the RMS values or amplitude of the input and output but upon other information as well. The other information could include information provided by other receivers in the radar system.


The preferred embodiments work with a value of mu between 2−6 and 2−13. The preferred leakage includes values from 2−8 to 2−15. The number of taps may be changed depending on the situation. The values of the taps may be read and written from a processor executing software. Optionally, the taps may be frozen (unchanged) for some period of time.


In a preferred embodiment, only a single adaption filter is needed, even for multiple receivers. For example, there may be separate complex FIRs for each receiver that use a same set of coefficients. This is possible because the correction or filtering is phase-independent. The notch filtering of the FMCW tone works for all RX paths even though they may be phase-shifted relative to each other. This may save quite a bit of area in the implementation.


Changes and modifications in the specifically described embodiments can be carried out without departing from the principles of the present invention, which is intended to be limited only by the scope of the appended claims, as interpreted according to the principles of patent law including the doctrine of equivalents.

Claims
  • 1. A radar sensing system for a vehicle, the radar sensing system comprising: a transmitter configured for installation and use on a vehicle, wherein the transmitter is configured to transmit radio signals;a receiver configured for installation and use on the vehicle, wherein the receiver is configured to receive radio signals that include (i) the transmitted radio signals transmitted by the transmitter and reflected from objects in an environment, and (ii) other radio signals that include radio signals transmitted by at least one other radar sensing system;wherein the receiver is configured to filter frequency modulated continuous wave (FMCW) radio signals from the received radio signals to produce filtered radio signals; andwherein the receiver comprises a bypass mechanism configured to select between (i) the received radio signals filtered of FMCW radio signals and (ii) the received radio signals before filtering, wherein the selected radio signals are selected for signal processing.
  • 2. The radar sensing system of claim 1, wherein the selected radio signals are forwarded to a correlator and a fast Fourier transform (FFT) processing module for the signal processing.
  • 3. The radar sensing system of claim 1, wherein the receiver comprises an adaptive filter configured to filter out FMCW radio signals from the received radio signals.
  • 4. The radar sensing system of claim 3, wherein the adaptive filter comprises a least mean square (LMS)-type of filter.
  • 5. The radar sensing system of claim 4, wherein the LMS-type filter includes a finite impulse response filter.
  • 6. The radar sensing system of claim 5 further comprising a plurality of receivers, each with a finite impulse response (FIR) filter, wherein all of the FIR filters use a same set of weight values for processing the received signals.
  • 7. The radar sensing system of claim 5, wherein a portion of filter coefficients for the adaptive filter are updated and another portion of the filter coefficients are held constant.
  • 8. The radar sensing system of claim 7, wherein updated filter coefficients are determined based on an error function and previous filter coefficients of the adaptive filter.
  • 9. The radar sensing system of claim 8, wherein the error function is based on a difference between an input to, and an output of, the adaptive filter.
  • 10. The radar sensing system of claim 1, wherein the receiver is configured to sample the received radio signals to produce a sampled stream, and wherein the receiver is configured to filter the sampled stream.
  • 11. The radar sensing system of claim 10, wherein the receiver is configured to produce the sampled stream by down-converting and sampling the received radio signals to produce the sampled stream.
  • 12. The radar sensing system of claim 1, wherein the bypass mechanism is operable to select the received radio signals filtered of FMCW radio signals when the received radio signals before filtering include FMCW radio signals.
  • 13. The radar sensing system of claim 12, wherein the bypass mechanism is further configured to select the filtered radio signals when: (i) the other radio signals include FMCW radio signals and (ii) the other radio signals have an amplitude above a threshold level.
  • 14. The radar sensing system of claim 12, wherein the bypass mechanism is further configured to measure the amplitudes of the filtered radio signals and the received radio signals before filtering.
  • 15. The radar sensing system of claim 14, wherein the bypass mechanism is configured to make a selection based at least in part on a root mean square (RMS) amplitude value of the filtered radio signals and an RMS amplitude value of the received radio signals before filtering.
  • 16. The radar sensing system of claim 1, wherein the transmitter is configured to transmit phase modulated radio signals.
  • 17. The radar sensing system of claim 1, wherein removing interference due to radio signals transmitted by at least one other radar sensing system allows transmitted signals transmitted by the transmitter and reflected from both a nearby object and a more distant object to be detectable by the receiver.
  • 18. A method for removing interference from a radio signal received by a vehicle mounted radar sensing system, said method comprising: providing a radar sensing system comprising a transmitter configured for installation and use on a vehicle and configured to transmit radio signals, and a receiver configured for installation and use on the vehicle and configured to receive radio signals that include: (i) the transmitted radio signals transmitted by the transmitter and reflected from objects in an environment, and (ii) other radio signals that include radio signals transmitted by at least one other radar sensing system, wherein the receiver comprises a bypass mechanism;processing the received radio signals to produce a sampled stream;filtering the effect of frequency modulated continuous wave (FMCW) radio signals from the sampled stream to produce a filtered sampled stream;selecting, with the bypass mechanism, between the sampled stream filtered of FMCW radio signals and the sample stream before filtering; andperforming range and velocity processing on the selected sampled stream.
  • 19. The method of claim 18, wherein filtering comprises adaptive filtering.
  • 20. The method of claim 19, wherein adaptive filtering comprises filtering the sampled stream with a least mean square (LMS)-type of filter.
  • 21. The method of claim 20, wherein the LMS-type filter comprises a finite impulse response filter.
  • 22. The method of claim 18, wherein the transmitter is configured to transmit phase modulated radio signals.
  • 23. The method of claim 18, wherein performing range and velocity processing comprises performing correlation and fast Fourier transform (FFT) processing, respectively.
CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 15/782,304, filed Oct. 12, 2017, which will issue on Jun. 5, 2018 as U.S. Pat. No. 9,989,638, which is a continuation of U.S. Pat. No. 9,791,564, issued on Oct. 17, 2017, and which claims the filing benefits of U.S. provisional applications, Ser. No. 62/450,184, filed Jan. 25, 2017, and Ser. No. 62/327,005, filed Apr. 25, 2016, which are both hereby incorporated by reference herein in their entireties.

US Referenced Citations (294)
Number Name Date Kind
1882128 Fearing Oct 1932 A
3374478 Blau Mar 1968 A
3735398 Ross May 1973 A
3750169 Strenglein Jul 1973 A
3896434 Sirven Jul 1975 A
4078234 Fishbein et al. Mar 1978 A
4176351 De Vita et al. Nov 1979 A
4566010 Collins Jan 1986 A
4882668 Schmid et al. Nov 1989 A
4910464 Trett et al. Mar 1990 A
4939685 Feintuch Jul 1990 A
5001486 Bächtiger Mar 1991 A
5034906 Chang Jul 1991 A
5087918 May et al. Feb 1992 A
5151702 Urkowitz Sep 1992 A
5175710 Hutson Dec 1992 A
5218619 Dent Jun 1993 A
5272663 Jones et al. Dec 1993 A
5280288 Sherry et al. Jan 1994 A
5302956 Asbury et al. Apr 1994 A
5341141 Frazier et al. Aug 1994 A
5345470 Alexander Sep 1994 A
5376939 Urkowitz Dec 1994 A
5379322 Kosaka et al. Jan 1995 A
5497162 Kaiser Mar 1996 A
5508706 Tsou et al. Apr 1996 A
5581464 Woll et al. Dec 1996 A
5657021 Ehsani-Nategh et al. Aug 1997 A
5657023 Lewis et al. Aug 1997 A
5691724 Aker et al. Nov 1997 A
5712640 Andou Jan 1998 A
5724041 Inoue et al. Mar 1998 A
5892477 Wehling Apr 1999 A
5917430 Greneker, III et al. Jun 1999 A
5920285 Benjamin Jul 1999 A
5931893 Dent et al. Aug 1999 A
5959571 Aoyagi et al. Sep 1999 A
5970400 Dwyer Oct 1999 A
6067314 Azuma May 2000 A
6069581 Bell et al. May 2000 A
6121872 Weishaupt Sep 2000 A
6121918 Tullsson Sep 2000 A
6151366 Yip Nov 2000 A
6163252 Nishiwaki Dec 2000 A
6184829 Stilp Feb 2001 B1
6191726 Tullsson Feb 2001 B1
6288672 Asano et al. Sep 2001 B1
6307622 Lewis Oct 2001 B1
6347264 Nicosia et al. Feb 2002 B2
6400308 Bell et al. Jun 2002 B1
6411250 Oswald et al. Jun 2002 B1
6417796 Bowlds Jul 2002 B1
6424289 Fukae et al. Jul 2002 B2
6583753 Reed Jun 2003 B1
6614387 Deadman Sep 2003 B1
6624784 Yamaguchi Sep 2003 B1
6674908 Aronov Jan 2004 B1
6714956 Liu Mar 2004 B1
6747595 Hirabe Jun 2004 B2
6768391 Dent et al. Jul 2004 B1
6865218 Sourour Mar 2005 B1
6975246 Trudeau Dec 2005 B1
7119739 Struckman Oct 2006 B1
7289058 Shima Oct 2007 B2
7299251 Skidmore et al. Nov 2007 B2
7338450 Kristofferson et al. Mar 2008 B2
7395084 Anttila Jul 2008 B2
7460055 Nishijima et al. Dec 2008 B2
7474258 Arikan et al. Jan 2009 B1
7545310 Matsuoka Jun 2009 B2
7545321 Kawasaki Jun 2009 B2
7564400 Fukuda Jul 2009 B2
7567204 Sakamoto Jul 2009 B2
7609198 Chang Oct 2009 B2
7642952 Fukuda Jan 2010 B2
7663533 Toennesen Feb 2010 B2
7728762 Sakamoto Jun 2010 B2
7791528 Klotzbuecher Sep 2010 B2
7847731 Wiesbeck et al. Dec 2010 B2
7855677 Negoro et al. Dec 2010 B2
7859450 Shirakawa et al. Dec 2010 B2
8019352 Rappaport et al. Sep 2011 B2
8049663 Frank et al. Nov 2011 B2
8059026 Nunez Nov 2011 B1
8102306 Smith, Jr. et al. Jan 2012 B2
8154436 Szajnowski Apr 2012 B2
8330650 Goldman Dec 2012 B2
8390507 Wintermantel Mar 2013 B2
8471760 Szajnowski Jun 2013 B2
8532159 Kagawa et al. Sep 2013 B2
8547988 Hadani et al. Oct 2013 B2
8686894 Fukuda et al. Apr 2014 B2
8694306 Short et al. Apr 2014 B1
9121943 Stirlin-Gallacher et al. Sep 2015 B2
9182479 Chen Nov 2015 B2
9239378 Kishigami et al. Jan 2016 B2
9239379 Burgio et al. Jan 2016 B2
9282945 Smith et al. Mar 2016 B2
9335402 Maeno et al. May 2016 B2
9541639 Searcy et al. Jan 2017 B2
9568600 Alland Feb 2017 B2
9575160 Davis et al. Feb 2017 B1
9599702 Bordes et al. Mar 2017 B1
9689967 Stark et al. Jun 2017 B1
9720073 Davis et al. Aug 2017 B1
9753121 Davis Sep 2017 B1
9753132 Bordes et al. Sep 2017 B1
9772397 Bordes et al. Sep 2017 B1
9791551 Eshraghi et al. Oct 2017 B1
9791564 Harris Oct 2017 B1
9806914 Bordes et al. Oct 2017 B1
9829567 Davis et al. Nov 2017 B1
9846228 Davis et al. Dec 2017 B2
9869762 Alland et al. Jan 2018 B1
10852408 Aslett Dec 2020 B2
20010002919 Sourour et al. Jun 2001 A1
20020004692 Nicosia et al. Jan 2002 A1
20020044082 Woodington et al. Apr 2002 A1
20020075178 Woodington et al. Jun 2002 A1
20020118522 Ho et al. Aug 2002 A1
20020130811 Voigtaender Sep 2002 A1
20020147534 Delcheccolo et al. Oct 2002 A1
20020155811 Prismantas Oct 2002 A1
20030001772 Woodington et al. Jan 2003 A1
20030011519 Breglia et al. Jan 2003 A1
20030058166 Hirabe Mar 2003 A1
20030080713 Kirmuss May 2003 A1
20030102997 Levin Jun 2003 A1
20030235244 Pessoa et al. Dec 2003 A1
20040012516 Schiffmann Jan 2004 A1
20040015529 Tanrikulu et al. Jan 2004 A1
20040066323 Richter Apr 2004 A1
20040070532 Ishii Apr 2004 A1
20040138802 Kuragaki et al. Jul 2004 A1
20040229590 Kubo Nov 2004 A1
20050069162 Haykin Mar 2005 A1
20050156780 Bonthron et al. Jul 2005 A1
20050201457 Allred et al. Sep 2005 A1
20050225476 Hoetzel et al. Oct 2005 A1
20050273480 Pugh et al. Dec 2005 A1
20060012511 Dooi et al. Jan 2006 A1
20060036353 Wintermantel Feb 2006 A1
20060050707 Sterin Mar 2006 A1
20060093078 Lewis et al. May 2006 A1
20060109170 Voigtlaender et al. May 2006 A1
20060109931 Asai May 2006 A1
20060114324 Farmer et al. Jun 2006 A1
20060140249 Kohno Jun 2006 A1
20060181448 Natsume et al. Aug 2006 A1
20060244653 Szajnowski Nov 2006 A1
20060262007 Bonthron Nov 2006 A1
20060262009 Watanabe Nov 2006 A1
20070018884 Adams Jan 2007 A1
20070018886 Watanabe et al. Jan 2007 A1
20070109175 Fukuda May 2007 A1
20070115869 Lakkis May 2007 A1
20070120731 Kelly, Jr. et al. May 2007 A1
20070132633 Uchino Jun 2007 A1
20070152870 Woodington et al. Jul 2007 A1
20070152871 Puglia Jul 2007 A1
20070152872 Woodington Jul 2007 A1
20070164896 Suzuki et al. Jul 2007 A1
20070171122 Nakano Jul 2007 A1
20070182619 Honda et al. Aug 2007 A1
20070182623 Zeng Aug 2007 A1
20070188373 Shirakawa et al. Aug 2007 A1
20070200747 Okai Aug 2007 A1
20070263748 Mesecher Nov 2007 A1
20070279303 Schoebel Dec 2007 A1
20080208472 Morcom Aug 2008 A1
20080272955 Yonak et al. Nov 2008 A1
20090003412 Negoro et al. Jan 2009 A1
20090015459 Mahler et al. Jan 2009 A1
20090015464 Fukuda Jan 2009 A1
20090027257 Arikan Jan 2009 A1
20090051581 Hatono Feb 2009 A1
20090072957 Wu et al. Mar 2009 A1
20090073025 Inoue et al. Mar 2009 A1
20090074031 Fukuda Mar 2009 A1
20090079617 Shirakawa et al. Mar 2009 A1
20090085827 Orime et al. Apr 2009 A1
20090103593 Bergamo Apr 2009 A1
20090121918 Shirai et al. May 2009 A1
20090212998 Szajnowski Aug 2009 A1
20090237293 Sakuma Sep 2009 A1
20090267822 Shinoda et al. Oct 2009 A1
20090289831 Akita Nov 2009 A1
20090295623 Falk Dec 2009 A1
20100001897 Lyman Jan 2010 A1
20100019950 Yamano et al. Jan 2010 A1
20100116365 McCarty May 2010 A1
20100156690 Kim et al. Jun 2010 A1
20100198513 Zeng et al. Aug 2010 A1
20100277359 Ando Nov 2010 A1
20100289692 Winkler Nov 2010 A1
20110006944 Goldman Jan 2011 A1
20110032138 Krapf Feb 2011 A1
20110074620 Wintermantel Mar 2011 A1
20110187600 Landt Aug 2011 A1
20110196568 Nickolaou Aug 2011 A1
20110248796 Pozgay Oct 2011 A1
20110279303 Smith, Jr. et al. Nov 2011 A1
20110279307 Song Nov 2011 A1
20110285576 Lynam Nov 2011 A1
20110291874 De Mersseman Dec 2011 A1
20110291875 Szajnowski Dec 2011 A1
20110292971 Hadani et al. Dec 2011 A1
20110298653 Mizutani Dec 2011 A1
20120001791 Wintermantel Jan 2012 A1
20120050093 Heilmann et al. Mar 2012 A1
20120105268 Smits et al. May 2012 A1
20120112957 Nguyen et al. May 2012 A1
20120133547 MacDonald et al. May 2012 A1
20120173246 Choi et al. Jul 2012 A1
20120195349 Lakkis Aug 2012 A1
20120249356 Shope Oct 2012 A1
20120257643 Wu et al. Oct 2012 A1
20120314799 In De Betou et al. Dec 2012 A1
20120319900 Johansson et al. Dec 2012 A1
20130016761 Nentwig Jan 2013 A1
20130021196 Himmelstoss Jan 2013 A1
20130027240 Chowdhury Jan 2013 A1
20130069818 Shirakawa et al. Mar 2013 A1
20130102254 Cyzs Apr 2013 A1
20130113652 Smits et al. May 2013 A1
20130113653 Kishigami et al. May 2013 A1
20130135140 Kishigami May 2013 A1
20130169485 Lynch Jul 2013 A1
20130176154 Bonaccio et al. Jul 2013 A1
20130214961 Lee et al. Aug 2013 A1
20130229301 Kanamoto Sep 2013 A1
20130244710 Nguyen et al. Sep 2013 A1
20130249730 Adcook Sep 2013 A1
20130314271 Braswell et al. Nov 2013 A1
20130321196 Binzer et al. Dec 2013 A1
20140022108 Alberth, Jr. et al. Jan 2014 A1
20140028491 Ferguson Jan 2014 A1
20140035774 Khlifi Feb 2014 A1
20140070985 Vacanti Mar 2014 A1
20140085128 Kishigami et al. Mar 2014 A1
20140111372 Wu Apr 2014 A1
20140139322 Wang et al. May 2014 A1
20140159948 Ishimori et al. Jun 2014 A1
20140168004 Chen Jun 2014 A1
20140220903 Schulz et al. Aug 2014 A1
20140253345 Breed Sep 2014 A1
20140285373 Kuwahara et al. Sep 2014 A1
20140327566 Burgio et al. Nov 2014 A1
20140348253 Mobasher et al. Nov 2014 A1
20150002329 Murad et al. Jan 2015 A1
20150002357 Sanford et al. Jan 2015 A1
20150035662 Bowers et al. Feb 2015 A1
20150061922 Kishigami Mar 2015 A1
20150103745 Negus et al. Apr 2015 A1
20150198709 Inoue Jul 2015 A1
20150204966 Kishigami Jul 2015 A1
20150204971 Kuehnle Jul 2015 A1
20150226848 Park Aug 2015 A1
20150234045 Rosenblum Aug 2015 A1
20150247924 Kishigami Sep 2015 A1
20150255867 Inoue Sep 2015 A1
20150301172 Ossowska Oct 2015 A1
20150323660 Hampikian Nov 2015 A1
20150331090 Jeong et al. Nov 2015 A1
20160003939 Stainvas Olshansky et al. Jan 2016 A1
20160018511 Nayyar et al. Jan 2016 A1
20160033631 Searcy et al. Feb 2016 A1
20160033632 Searcy et al. Feb 2016 A1
20160041260 Cao et al. Feb 2016 A1
20160061935 McCloskey et al. Mar 2016 A1
20160084941 Arage Mar 2016 A1
20160084943 Arage Mar 2016 A1
20160091595 Alcalde Mar 2016 A1
20160124086 Jansen et al. May 2016 A1
20160139254 Wittenberg May 2016 A1
20160146931 Rao et al. May 2016 A1
20160154103 Moriuchi Jun 2016 A1
20160213258 Lashkari et al. Jul 2016 A1
20160238694 Kishigami Aug 2016 A1
20160245909 Aslett Aug 2016 A1
20170010361 Tanaka Jan 2017 A1
20170023661 Richert Jan 2017 A1
20170023663 Subburaji et al. Jan 2017 A1
20170074980 Adib Mar 2017 A1
20170153316 Wintermantel Jun 2017 A1
20170176583 Gulden Jun 2017 A1
20170219689 Hung et al. Aug 2017 A1
20170234968 Roger et al. Aug 2017 A1
20170293025 Davis et al. Oct 2017 A1
20170293027 Stark et al. Oct 2017 A1
20170307728 Eshraghi et al. Oct 2017 A1
20170309997 Alland et al. Oct 2017 A1
20170310758 Davis et al. Oct 2017 A1
20170336495 Davis et al. Nov 2017 A1
Foreign Referenced Citations (10)
Number Date Country
0725480 Nov 2011 EP
2374217 Apr 2013 EP
2821808 Jul 2015 EP
2751086 Jan 1998 FR
2751086 Jan 1998 FR
WO2015175078 Nov 2015 WO
WO2015185058 Dec 2015 WO
WO2016011407 Jan 2016 WO
WO2016030656 Mar 2016 WO
WO2017187330 Nov 2017 WO
Non-Patent Literature Citations (5)
Entry
Chambers et al., An article entitled “Real-Time Vehicle Mounted Multistatic Ground Penetrating Radar Imaging System for Buried Object Detection,” Lawrence Livermore National Laboratory Reports (LLNL-TR-615452), Feb. 4, 2013; Retrieved from the Internet from https://e-reports-ext.Ilnl.gov/pdf/711892.pdf.
Fraser, “Design and simulation of a coded sequence ground penetrating radar,” In: Diss. University of British Columbia, Dec. 3, 2015.
Zhou et al., “Linear extractors for extracting randomness from noisy sources,” In: Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on Oct. 3, 2011.
V. Giannini et al., “A 79 GHz Phase-Modulated 4 GHz-BW CW Radar Transmitter in 28 nm CMOS,” in IEEE Journal of Solid-State Circuits, vol. 49, No. 12, pp. 2925-2937, Dec. 2014. (Year: 2014).
Óscar Faus García, “Signal Processing for mm Wave MIMO Radar,” University of Gavle, Faculty of Engineering and Substainable Development, Jun. 2015; Retrieved from the Internet from http://www.diva-portal.se/smash/get/diva2:826028/FULLTEXT01.pdf.
Related Publications (1)
Number Date Country
20180275270 A1 Sep 2018 US
Provisional Applications (2)
Number Date Country
62450184 Jan 2017 US
62327005 Apr 2016 US
Continuations (2)
Number Date Country
Parent 15782304 Oct 2017 US
Child 15994360 US
Parent 15492160 Apr 2017 US
Child 15782304 US