Integrated circuit, radio device, terminal device, interference detection method and apparatus

Abstract

Integrated circuit, radio device, terminal device, interference detection method and device, the present application provides a kind of interference detection method, by the histogram statistics of signal energy in frequency domain, and the statistical characteristics of histogram are combined, to realize the detection of interference accurately and quickly, and since the requirement of histogram statistics to operation amount is very small, and is realized based on frequency domain, carries out statistical analysis between impulse, so the real-time requirement of system is lower.

Description

Technical Field

[0001] This invention relates to the field of interference detection technology, and more particularly to an interference detection method and apparatus, as well as integrated circuits, radio devices and terminal equipment. Background Technology

[0002] Interference detection methods for target sensors typically employ time-frequency analysis techniques, such as Short-Time Fourier Transform (STFT), to extract interference features. This method requires real-time STFT calculations across all pulses, resulting in a large computational load and high real-time performance requirements for the system. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides an interference detection method. By performing histogram statistics on signal energy in the frequency domain and combining the statistical characteristics of histograms, interference can be detected accurately and quickly. Furthermore, since histogram statistics require very little computation and are based on frequency domain statistical analysis between pulses, the real-time requirements of the system are low.

[0004] This application provides an interference detection method, which may include: performing a two-dimensional fast Fourier transform on a received signal to obtain a range-Doppler spectrum, the range-Doppler spectrum including a range dimension, a velocity dimension, and an energy dimension; performing energy dimension distribution statistics along the velocity dimension for a preset range gate in the range-Doppler spectrum to obtain an energy statistical histogram; and performing interference detection on the preset range gate based on the statistical characteristics of the energy statistical histogram.

[0005] In this embodiment, in the range-Doppler spectrum obtained by 2D-FFT, the energy dimension histogram statistics of the target range gate (such as a preset range gate) are performed, and the interference can be detected based on the obtained histogram statistical characteristics.

[0006] In some optional embodiments, constant false alarm rate (CFAR) detection can also be performed based on the statistical characteristics of the energy statistical histogram, thereby achieving interference detection. For distance gates that are not affected by interference, CFAR detection can also be achieved based on the above-mentioned histogram statistical characteristics, so as to further reduce the computing power requirements of the system.

[0007] In some optional embodiments, the range-Doppler spectrum has discrete range gates along its range dimension, and the preset range gates include at least one of the range gates. When the preset range gates include one range gate, it can be understood that the interference detection method of any embodiment of this application is performed for any range gate. When interference detection is performed on all range gates, each range gate can be performed separately or simultaneously using the interference detection method of any embodiment of this application. When the preset range gates include two or more range gates, the preset range gates can be treated as a whole for interference detection in any embodiment of this application. For example, if two adjacent range gates are treated as a whole, all data corresponding to the two range gates are aggregated, and then subsequent energy histogram statistics are performed to determine whether the two range gates are interfered with.

[0008] In some optional embodiments, the distribution statistics of the energy dimension along the velocity dimension of a preset distance gate are performed to obtain an energy statistical histogram. This includes: discretizing the energy values ​​along the energy dimension to obtain multiple energy value intervals that are continuously distributed at equal intervals according to their energy magnitude; and counting the number of samples in each energy value interval of the preset distance gate to generate the energy statistical histogram. For example, for the energy value of each discrete point, one or two significant digits are removed using methods such as rounding to determine the energy value interval, which also facilitates subsequent histogram sample statistics.

[0009] In some optional embodiments, the distribution statistics of the energy dimension are performed on the preset distance gate edge velocity dimension to obtain an energy statistical histogram; it may also include: after preprocessing the energy values ​​on the energy dimension, discretization processing is performed to obtain the plurality of energy value intervals that are continuously distributed at equal intervals; wherein, the preprocessing includes normalization processing or logarithmic operation processing, for example, the decibel value of each energy value can be obtained.

[0010] In some optional embodiments, interference detection of the preset distance gate based on the statistical characteristics of the energy statistical histogram may include: taking the energy value interval with the most samples in the energy statistical histogram as the noise floor interval; obtaining the sum of the energy of the noise floor interval and the peak energy value interval as a first energy sum; and determining whether the preset distance gate is interfered with based on the first energy sum.

[0011] In some optional embodiments, the method may further include: obtaining the sum of energy values ​​of all energy value intervals located between the noise floor interval and the peak energy value interval, and adding the first energy sum to obtain a second energy sum; and determining whether the preset distance gate is disturbed based on the second energy sum.

[0012] In some optional embodiments, the noise floor interval may also be the energy value interval containing the median value of the energy values ​​within the statistical histogram.

[0013] In some optional embodiments, the method may further include: for any energy value range, determining the effective energy value of that energy value range, and multiplying the number of samples by the effective energy value to obtain the energy sum corresponding to that energy value range. For example, if the energy value range is 20-25 and the number of samples is 5, to facilitate subsequent energy sum statistics, the effective energy value of that energy value range can be set to 22.5, and the corresponding energy sum would be 5*22.5 = 112.5; alternatively, the median of the energy value range can be set as the effective energy value, for example, if 3 samples have an energy value of 23, then the corresponding energy sum would be 5*23 = 115. Of course, in some optional embodiments, the actual energy of each sample can also be directly summed to obtain the energy sum of the preset distance gate.

[0014] The determination of whether the preset distance gate is interfered with based on the second energy includes: when the second energy is greater than a preset first threshold, determining that the radar signal includes an interference signal.

[0015] In some optional embodiments, determining whether the preset distance gate is interfered with based on the second energy sum includes: calculating the difference between the sum of the energy of the current frame and the adjacent frames, and determining that the radar signal of the current frame is interfered with when the difference is greater than a second threshold.

[0016] It should be noted that the first and second thresholds mentioned above can be adjusted according to actual needs. Specifically, they can be determined based on the requirements of the system and the scenario, or they can be combined with big data analysis to obtain reference threshold ranges for each system and corresponding scenario to facilitate interference detection.

[0017] This application embodiment also provides an interference detection device, which may include: an FFT module configured to perform a two-dimensional fast Fourier transform on the received signal to obtain a range-Doppler spectrum, the range-Doppler spectrum including a range dimension, a velocity dimension, and an energy dimension; a histogram generation module coupled to the FFT module, configured to: perform energy dimension distribution statistics along the velocity dimension for a preset range gate in the range-Doppler spectrum to obtain an energy statistical histogram; and an interference determination module coupled to the histogram generation module, configured to: perform interference detection on the preset range gate based on the statistical characteristics of the energy statistical histogram.

[0018] This application also provides an interference detection method applicable to processing radar signals from an LFMCW millimeter-wave radar. The method includes: performing a two-dimensional fast Fourier transform on the radar signal to obtain a range-Doppler spectrum, wherein the range-Doppler spectrum includes a range dimension, a velocity dimension, and an energy dimension; performing energy distribution statistics along the velocity dimension in the range-Doppler spectrum for a preset range gate to obtain a number of samples corresponding to multiple first energy values; and performing interference detection or constant false alarm rate (CFAR) processing on the radar signal based on the number of samples corresponding to the multiple first energy values.

[0019] According to one aspect of the invention, the LFMCW millimeter-wave radar transmits a continuous wave whose frequency varies linearly with time, and the radar signal is generated by mixing the millimeter-wave signal received by the LFMCW millimeter-wave radar with the continuous wave signal transmitted by the LFMCW millimeter-wave radar.

[0020] According to one aspect of the invention, the range-Doppler spectrum has discrete range gates in the range dimension and discrete velocity gates in the velocity dimension, and the preset range gates include one or more range gates in the range dimension.

[0021] According to one aspect of the present invention, the energy distribution statistics for a preset distance gate edge velocity dimension include: removing one or more preset valid bits from the energy values ​​in the energy dimension to form the first energy value; and generating a statistical histogram based on the number of samples corresponding to the plurality of first energy values.

[0022] According to one aspect of the invention, the horizontal axis of the statistical histogram is the logarithm of the first energy value, and the vertical axis is the number of samples of the first energy value.

[0023] According to one aspect of the present invention, the method may further include: calculating the sum of energy within a preset energy range based on the number of samples corresponding to the plurality of first energy values; and determining whether the radar signal includes an interference signal based on the sum of energy.

[0024] According to one aspect of the present invention, the preset energy range includes: the range from the first energy value corresponding to the highest value of the number of samples in the statistical histogram to the maximum value of the first energy value.

[0025] According to one aspect of the present invention, the preset energy range includes: the range from the median value of the first energy value in the statistical histogram to the maximum value of the first energy value.

[0026] According to one aspect of the present invention, the calculation of the energy within a preset energy range includes: calculating the sum of a plurality of first energy values ​​multiplied by the corresponding number of samples within the preset energy range of the statistical histogram.

[0027] According to one aspect of the present invention, the determination of whether the radar signal includes an interference signal based on the sum of the energy comprises: determining that the radar signal includes an interference signal when the sum of the energy is greater than a first threshold.

[0028] According to one aspect of the present invention, wherein the LFMCW millimeter-wave radar transmits a continuous wave signal whose frequency varies linearly with time multiple times, and generates a radar signal frame by repeatedly mixing the millimeter-wave signal received by the LFMCW millimeter-wave radar with the continuous wave signal, the step of determining whether the radar signal includes an interference signal based on the energy sum includes: calculating the difference between the energy sum of adjacent frames and the current frame, and determining that the current frame radar signal includes an interference signal when the difference is greater than a second threshold.

[0029] According to one aspect of the present invention, the method may include: searching for samples of size K in the statistical histogram, where K is a preset ordinal number; and generating a detection threshold based on a first energy value of the samples of size K.

[0030] According to one aspect of the present invention, the method may include: multiplying the first energy value of the Kth sample by a preset factor to generate a detection threshold.

[0031] According to one aspect of the present invention, the method may include: determining the preset distance threshold based on the distance range of the target object.

[0032] This invention also provides an interference detection device for processing radar signals from an LFMCW radar. The interference detection device includes: an FFT module configured to perform a two-dimensional fast Fourier transform on the electrical signal to obtain a range-Doppler spectrum, wherein the range-Doppler spectrum includes a range dimension, a velocity dimension, and an energy dimension; a histogram generation module coupled to the FFT module, configured to: perform energy distribution statistics on the velocity dimension at a preset range gate in the range-Doppler spectrum to obtain the number of samples corresponding to multiple first energy values; and generate a statistical histogram based on the number of samples corresponding to the multiple first energy values; and an interference determination module coupled to the histogram generation module, configured to: perform interference detection or constant false alarm rate (CFAR) processing on the radar signal based on the statistical histogram.

[0033] According to one aspect of the present invention, the histogram generation module is further configured to: remove one or more preset valid bits from the energy value on the energy dimension to form the first energy value; wherein the horizontal axis of the statistical histogram is the logarithm of the first energy value, and the vertical axis is the number of samples of the first energy value.

[0034] According to one aspect of the present invention, the interference determination module is further configured to: calculate the sum of energy within a preset energy range based on the statistical histogram; and determine whether the radar signal includes an interference signal based on the sum of energy.

[0035] According to one aspect of the present invention, the preset energy range includes: the range from the first energy value corresponding to the highest value of the number of samples in the statistical histogram to the maximum value of the first energy value; or the range from the median value of the first energy value in the statistical histogram to the maximum value of the first energy value.

[0036] According to one aspect of the present invention, the interference determination module is further configured to: calculate the sum of multiple first energy values ​​multiplied by the corresponding number of samples within the preset energy range of the statistical histogram.

[0037] According to one aspect of the present invention, the interference determination module is further configured to: determine that the radar signal includes an interference signal when the sum of the energy is greater than a first threshold.

[0038] According to one aspect of the present invention, wherein the LFMCW millimeter-wave radar transmits a continuous wave signal whose frequency varies linearly with time multiple times, and generates a radar signal frame by repeatedly mixing the millimeter-wave signal received by the LFMCW millimeter-wave radar with the continuous wave signal, the interference determination module is further configured to: calculate the difference between the sum of the energy of the adjacent frames and the current frame, and determine that the radar signal of the current frame includes an interference signal when the difference is greater than a second threshold.

[0039] According to one aspect of the invention, the interference determination module is further configured to: search for a sample of size K based on the statistical histogram, where K is a preset ordinal number; and generate a detection threshold based on a first energy value of the sample of size K.

[0040] According to one aspect of the invention, the interference determination module is further configured to: multiply the first energy value of the Kth size sample by a preset factor to generate the detection threshold.

[0041] According to one aspect of the invention, the histogram generation module is further configured to: determine the preset distance gate based on the distance range of the target object.

[0042] This invention also provides a millimeter-wave radar, comprising: a transmitting unit configured to transmit a continuous wave whose frequency varies linearly with time; a receiving unit configured to receive a millimeter-wave signal, the millimeter-wave signal including an echo transmitted by the transmitting unit and reflected by a target; a mixing unit coupled to the receiving unit, configured to mix the millimeter-wave signal received by the receiving unit with the continuous wave signal transmitted by the transmitting unit to generate a radar signal; an FFT unit coupled to the mixing unit, configured to perform a two-dimensional fast Fourier transform on the radar signal to obtain a range-Doppler spectrum, the range-Doppler spectrum including a range dimension, a velocity dimension, and an energy dimension; a histogram generation unit coupled to the FFT unit, configured to: perform energy distribution statistics on the velocity dimension along a preset range gate in the range-Doppler spectrum to obtain a number of samples corresponding to multiple first energy values; and generate a statistical histogram based on the number of samples corresponding to the multiple first energy values; and an interference determination unit coupled to the histogram generation unit, configured to: perform interference detection or constant false alarm rate (CFAR) processing on the radar signal based on the statistical histogram.

[0043] According to one aspect of the present invention, the millimeter-wave radar further includes: a target detection unit, coupled to the FFT unit and the interference determination unit respectively, configured such that: when the interference determination unit determines that the radar signal does not contain an interference signal, the target detection unit obtains the distance and velocity of the target object in the range-Doppler spectrum according to the interference detection threshold after constant false alarm rate processing.

[0044] This application also provides an integrated circuit, which may include a radio frequency (RF) module, an analog signal processing module, and a digital signal processing module connected in sequence; the RF module is used to generate RF transmit signals and receive RF receive signals; the analog signal processing module is used to down-convert the RF receive signals to obtain intermediate frequency (IF) signals; the digital signal processing module is used to perform analog-to-digital conversion on the IF signals to obtain digital signals; and a data processing module is used to process the digital signals to achieve target detection and / or wireless communication; wherein, the data processing module further uses the method described in any embodiment of this application to perform interference detection.

[0045] In some alternative embodiments, the integrated circuit may be a sensor or communication chip, such as a millimeter-wave radar chip.

[0046] This application also provides a wireless device, which may include: a carrier; an integrated circuit as described in any embodiment of this application, disposed on the carrier; an antenna, disposed on the carrier, or the antenna and the integrated circuit are integrated into a single device disposed on the carrier; wherein the integrated circuit is connected to the antenna and is used to transmit the radio frequency transmission signal and / or receive the radio frequency reception signal.

[0047] This application also provides a terminal device, which may include: a device body; and a wireless device as described in the embodiments of this application, disposed on the device body; wherein the wireless device is used for target detection and / or communication to provide reference information to the operation of the device body.

[0048] The method for millimeter-wave radar provided by this invention, while detecting the distance and velocity of targets, uses the detected data to form a statistical histogram for interference detection or constant false alarm rate (CFAR) processing. This simplifies the calculation process, saves computing power, and improves signal processing speed. Compared with existing algorithms such as OS-CFAR, the time complexity of the sorting operation is reduced from O(N²) or O(Nlog(N)) to O(N), significantly improving the real-time performance of signal processing and making it more suitable for vehicle-mounted millimeter-wave radar. The interference detection device provided by this invention has a simple structure and is easy to integrate. Its histogram generation module and interference determination module perform statistical and computational operations on the FFT data of the millimeter-wave radar, with a small computational load and fast interference detection speed. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings, without exceeding the scope of protection claimed by this application.

[0050] Figure 1 The present invention illustrates an LFMCW millimeter-wave radar applicable to some embodiments thereof;

[0051] Figure 2A The frequency domain waveform of the transmitted signal from the LFMCW millimeter-wave radar is shown.

[0052] Figure 2B The time-domain waveform of the transmitted signal from the LFMCW millimeter-wave radar is shown.

[0053] Figure 2C The frequency domain waveform of the transmitted signal from the LFMCW millimeter-wave radar is shown.

[0054] Figure 2DThe time-domain waveform of the transmitted signal from the LFMCW millimeter-wave radar is shown.

[0055] Figure 3A The beat signal in the frequency domain of the transmitted and received signals of the LFMCW millimeter-wave radar is shown.

[0056] Figure 3B The waveform of the mixed signal from the LFMCW millimeter-wave radar is shown.

[0057] Figure 4 The plane formed by the range dimension and velocity dimension obtained by performing a two-dimensional fast Fourier transform (2D FFT) on the raw radar data is shown.

[0058] Figure 5 The range-Doppler spectrum (RD spectrum) obtained by performing a two-dimensional fast Fourier transform (2D FFT) on the raw radar data is shown.

[0059] Figure 6A The transmitted, received, and jamming signals of the LFMCW millimeter-wave radar are shown.

[0060] Figure 6B It shows Figure 6A The mixing result of the transmitted and received signals in the presence of interference;

[0061] Figure 7 The range-Doppler spectrum (RD spectrum) obtained by performing a two-dimensional fast Fourier transform (2D FFT) on the raw radar data is shown.

[0062] Figure 8 An embodiment of the present invention provides a method for LFMCW millimeter-wave radar;

[0063] Figure 9 An energy statistics interval in a method for LFMCW millimeter-wave radar provided by an embodiment of the present invention is shown;

[0064] Figure 10 A statistical histogram corresponding to a method for LFMCW millimeter-wave radar provided by an embodiment of the present invention is shown;

[0065] Figure 11a -b shows a statistical histogram corresponding to a method for LFMCW millimeter-wave radar provided in an embodiment of the present invention;

[0066] Figure 12 An embodiment of the present invention provides a method for LFMCW millimeter-wave radar;

[0067] Figure 13An energy statistics interval in a method for LFMCW millimeter-wave radar provided by an embodiment of the present invention is shown;

[0068] Figure 14 A statistical histogram corresponding to a method for LFMCW millimeter-wave radar provided by an embodiment of the present invention is shown;

[0069] Figure 15 An interference detection device for millimeter-wave radar provided by an embodiment of the present invention is shown;

[0070] Figure 16 This illustration shows a millimeter-wave radar provided by an embodiment of the present invention. Detailed Implementation

[0071] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0072] This application provides a method for interference detection, which may include the following steps:

[0073] First, the received signal can be subjected to operations such as mixing, analog-to-digital conversion, sampling, and discretized spectrum analysis (such as fast Fourier transform) to obtain spectral data containing the energy dimension, such as range-Doppler spectra including distance, velocity, and energy dimensions.

[0074] Then, in the aforementioned spectrum, for preset data points in a specific dimension, the distribution statistics of the energy dimension are performed along another dimension, the velocity dimension, to obtain an energy statistical histogram. For example, for the range-Doppler spectrum, the distribution statistics of the energy dimension can be performed along the velocity dimension based on preset range gates (such as one range gate, two range gates, or three range gates) to obtain the aforementioned energy statistical histogram.

[0075] Finally, based on the statistical characteristics of the aforementioned energy statistical histogram, operations such as interference detection or constant false alarm rate (CFAR) detection are performed. For example, interference detection is performed on the aforementioned preset distance gate based on the statistical characteristics of the energy statistical histogram.

[0076] In some optional embodiments, the energy values ​​along the energy dimension can be discretized to obtain multiple energy value intervals that are continuously distributed at equal intervals according to their energy magnitudes. An energy statistical histogram can then be generated by counting the number of samples in each energy value interval. For example, for a range-Doppler spectrum, the energy statistical histogram can be generated by counting the number of samples in each energy value interval within a preset range gate. Alternatively, the energy values ​​can be preprocessed, such as by discretization, square root operations, or logarithmic calculations, before further discretization and division into energy value intervals to generate a preprocessed energy statistical histogram.

[0077] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. Furthermore, any changes or modifications made by those skilled in the art based on the ideas of this application, and on the specific implementation methods and application scope of this application, are all within the scope of protection of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

[0078] The following example, using millimeter-wave radar as a practical application, illustrates the interference detection and related technical content of this application:

[0079] Millimeter-wave radar is a detection radar that operates in the millimeter-wave band. Millimeter waves typically refer to electromagnetic wave signals in the 30 GHz to 300 GHz frequency range (corresponding to wavelengths of 1 mm to 10 mm). Since the wavelength of millimeter waves falls between microwaves and centimeter waves, millimeter-wave radar combines some advantages of both microwave and electro-optical radar. For example, millimeter-wave radar is small in size, lightweight, has high spatial resolution, strong penetration capabilities through fog, smoke, and dust, and possesses all-weather detection performance. Millimeter-wave radar can distinguish and identify very small targets and can simultaneously identify multiple targets.

[0080] Linear Frequency Modulated Continuous Wave (LFMCW) is widely used in automotive millimeter-wave radar systems. In this system, the transmitter continuously transmits multiple LFMCW pulse waveforms. The receiver down-converts the received LFMCW reflected signals to obtain the baseband signal, and then performs a 2D Fast Fourier Transform (FFT). The first dimension is the FFT within each LFMCW pulse, i.e., the range-dimensional FFT; the second dimension is the value at the same spectral line position within the FFT spectrum of all pulses, which is then subjected to another FFT operation, i.e., the Doppler-dimensional FFT. In the resulting 2D FFT plane, targets at different distances and velocities will appear as spikes at different coordinates. The stronger the reflected signal of a target, the higher its energy (or gain, power) peak will be. The target detection process involves searching for energy peaks within the 2D FFT plane. When the energy value at a certain coordinate in the 2D FFT is higher than a certain detection threshold, such as the noise floor of the 2D FFT plane, and meets certain specific conditions, it can be considered a target coordinate. The distance and Doppler coordinate values ​​corresponding to this target coordinate correspond to the target's distance and velocity, respectively.

[0081] Specifically, such as Figure 1 As shown, the LFMCW millimeter-wave radar 100 includes a signal generator 110, a digital-to-analog converter 120, an oscillator 130, a splitter 140, a transmitting antenna 150, and a mixer 160. Specifically: the LFMCW millimeter-wave radar 100 generates a digital signal whose frequency varies linearly with time through the signal generator 110; the digital-to-analog converter 120 is coupled to the signal generator 110 and configured to receive the digital signal and convert it into an analog signal; the oscillator 130 is coupled to the digital-to-analog converter 120 and configured to receive the analog signal and generate a millimeter-wave band radio frequency signal based on the analog signal; the splitter 140 is coupled to the oscillator 130 and configured to separate the radio frequency signal generated by the oscillator 130, with one part serving as a transmitted signal transmitted by the transmitting antenna 150 towards the detection space where a target may exist, and the other part serving as the input signal to the mixer 160 to generate a mixed signal.

[0082] Optionally, such as Figures 2A to 2D As shown, the radio frequency signal includes one or more of a triangular wave and a sawtooth wave. The triangular wave radio frequency signal has an upward scanning modulation band with linearly increasing frequency and a downward scanning modulation band with linearly decreasing frequency. The sawtooth wave radio frequency signal has an upward scanning modulation band with linearly increasing frequency.

[0083] like Figure 1As shown, the LFMCW millimeter-wave radar 100 also includes a receiving antenna 170, an analog-to-digital converter 180, and a signal processing unit 190. The receiving antenna 170 of the LFMCW millimeter-wave radar 100 is configured to receive millimeter-wave signals within the detection space, including echoes formed by reflections of transmitted signals from targets within the detection space, and may also include interference signals, such as those from other vehicle-mounted millimeter-wave radars. A mixer 160 is coupled to the receiving antenna 170 and configured to mix the millimeter-wave signals received by the receiving antenna 170 with the transmitted signals. The mixer 160 includes a low-pass filter 161. After the transmitted and received signals are multiplied in the time domain, they are low-pass filtered by the low-pass filter 161 to form a mixed signal (i.e., the raw data of the millimeter-wave radar). The analog-to-digital converter 180 is coupled to the low-pass filter 161 and configured to sample the mixed signal and output it to the signal processing unit 190.

[0084] The signal processing unit 190 is coupled to the analog-to-digital converter 180 and configured to receive the sampled mixed signal and perform a two-dimensional Fast Fourier Transform (FFT) on it. First, a Fast Fourier Transform is performed on the time-domain sampled signal; the resulting frequency value (beat frequency) is related to the distance to the target object. After the one-dimensional Fourier Transform, the velocity information of the target object is still retained in the phase information of the mixed signal. The one-dimensional FFT data with the same range resolution (range gate) is sampled again, and a Fast Fourier Transform is performed on the sampled FFT data; the resulting frequency value (Doppler frequency) is related to the velocity of the target object.

[0085] like Figure 3A As shown, the LFMCW millimeter-wave radar 100 transmits millimeter-wave signals with frequencies varying over time. When it encounters a target, the millimeter-wave signal is reflected and received by the radar's receiving antenna 170. At this point, there is a delay between the received and transmitted signals. The distance between the target and the LFMCW millimeter-wave radar 100 can be calculated using this delay information. Figure 3A As shown, the beat frequency between the transmitted and received signals is f, the bandwidth of the transmitted signal is B, the delay time is τ, and the period of the transmitted signal is T. Then:

[0086]

[0087] Distance between the target and the millimeter-wave radar:

[0088] Right now

[0089] Where c is the propagation speed of electromagnetic waves. Frequency subtraction corresponds to time-domain multiplication. The transmitted signal is multiplied by the received signal, and then the high-frequency component is filtered out by a low-pass filter 161 (the subtraction of the two signals in the frequency domain still includes a high-frequency component f).c -f b , where f c (where the carrier frequency is used), the frequency of the resulting mixed signal is the beat frequency f mentioned above. b .like Figure 3B The image shows a mixed signal. By performing a fast Fourier transform on the mixed signal in the time domain, the beat frequency can be obtained, and then the distance between the target and the LFMCW millimeter-wave radar 100 can be calculated.

[0090] Since the analog-to-digital converter 180 has a preset sampling rate for sampling the mixed signal, let the preset sampling frequency be f. S The number of sampling points for performing the Fast Fourier Transform (FFT) is N. f Then the minimum frequency resolution of the Fast Fourier Transform is:

[0091]

[0092] Let the analog-to-digital converter 180 sample N data points within one signal period T, then:

[0093]

[0094] but:

[0095]

[0096] The minimum resolution of distance can be determined from the minimum resolution of frequency:

[0097]

[0098] Therefore, the calculated distance between the target and the LFMCW millimeter-wave radar 100 has the minimum range resolution (range gate).

[0099] If a target object in the detection space has a certain velocity relative to the LFMCW millimeter-wave radar 100, the received signal will experience a frequency shift relative to the target object's echo waveform due to the Doppler effect. Since the propagation speed of electromagnetic waves is much greater than the target object's moving speed, during a single detection process of the millimeter-wave radar 100 (a single detection includes multiple transmissions of chirped pulses with frequencies that change linearly with time, and multiple mixing with the received signal), the target object can be considered stationary, i.e., within the same minimum range resolution (range gate). After performing a Fast Fourier Transform (FFT) on the sampled signals of multiple mixed signals, the FFT data is sampled again along the same range gate. Since the target object's velocity information is retained in the phase information of the mixed signals, a Fast Fourier Transform is performed again on the one-dimensional FFT data of the same range gate. The resulting signal frequency is the Doppler frequency, thus allowing the calculation of the target object's velocity. Similarly, the calculated velocity of the target object relative to the LFMCW millimeter-wave radar 100 has a minimum velocity resolution (velocity gate).

[0100] like Figure 4 As shown, the plane composed of the distance dimension and the velocity dimension is called the 2D FFT plane, where the distance dimension has the minimum distance resolution (distance gate) and the velocity dimension has the minimum velocity resolution (velocity gate).

[0101] Based on the results of the two Fourier transforms, we can establish as follows: Figure 5 The range-Doppler spectrum (RD spectrum) shown includes range, velocity, and energy dimensions. On the 2D FFT plane (the plane formed by the range and velocity dimensions), targets at different distances and velocities will appear as peaks at different coordinates on the 2D FFT plane. The stronger the reflection of the target, the higher the peak will be. The target detection process is essentially searching for peaks in the 2D FFT plane. When the value at a certain coordinate in the 2D FFT is higher than a certain detection threshold (e.g., the noise floor value of the 2D FFT plane), the target is considered to exist at that location. The coordinate values ​​in the range and velocity dimensions corresponding to that location represent the target's distance and velocity, respectively.

[0102] When the millimeter-wave radar's receiving antenna receives millimeter-wave signals that include interference signals, i.e., when it is interfered with by other signals (such as adjacent-channel interference and / or co-channel interference), such as... Figure 6A As shown, under normal circumstances, if the interference signal originates from other vehicle-mounted millimeter-wave radars, it is also a linear frequency modulated (LFM) signal. Since the slope of the interference signal is usually different from the transmitted and echo signals, a portion of the interference signal can be filtered out using a low-pass filter. However, in cases such as... Figure 6APoints A and B, as shown, have interference signals with frequencies close to the transmitted and echo signals, meaning that adjacent-channel interference and / or co-channel interference will occur, which cannot be removed by low-pass filtering. Interference waveforms appear in the mixed signal output from mixer 160, such as... Figure 6B As shown. Due to the presence of this interference signal, after the signal processing unit 190 performs a two-dimensional fast Fourier transform on the mixed signal, the generated range-Doppler spectrum will also exhibit an increased noise floor or the presence of false alarms, such as... Figure 7 As shown.

[0103] In LFMCW radar systems, interference detection methods typically leverage the characteristic that the interference signal is a linearly modulated frequency (LFM) signal, meaning its frequency changes linearly with time. Time-frequency analysis methods, such as the Short Time Fourier Transform (STFT), are used to extract interference features. This method requires real-time STFT calculations across all pulses, resulting in a large computational load and high real-time performance requirements for the system.

[0104] To address the signal interference problem of LFMCW millimeter-wave radar, this invention provides a method 10 for interference detection of LFMCW millimeter-wave radar. The LFMCW millimeter-wave radar receives millimeter-wave signals as radar signals. These millimeter-wave signals include echoes emitted by the millimeter-wave radar and reflected by a target, as well as electromagnetic waves directly radiated or received after reflection / scattering from other signal sources. Figure 8 As shown, the interference detection method 10 may include steps S101 to S104. Wherein:

[0105] In step S101, a two-dimensional fast Fourier transform (FFT) is performed on the radar signal to obtain the range-Doppler spectrum (RD spectrum), wherein the range-Doppler spectrum may include range, velocity, and energy dimensions. As described above, the LFMCW millimeter-wave radar transmits a continuous wave whose frequency varies linearly with time. The radar signal is generated by mixing the millimeter-wave signal received by the LFMCW millimeter-wave radar with the continuous wave signal transmitted by the LFMCW millimeter-wave radar. By performing a two-dimensional fast Fourier transform (FFT) on the radar signal (such as the signal after analog-to-digital conversion following mixing), the following is obtained: Figure 5 or Figure 7 The distance-Doppler spectrum shown. Figure 5 or Figure 7 As an example of the range-Doppler spectrum, the range-Doppler spectrum will present different distributions depending on the transmitted frequency modulation signal, target information, and real-time interference information. All range-Doppler spectra with different distributions are applicable to the interference detection method 10 provided by this invention.

[0106] In step S102, energy distribution statistics are performed on the range-Doppler spectrum according to the preset range gate velocity dimension to obtain the number of samples corresponding to multiple first energy values. For example... Figure 9 As shown, since both the range-Doppler spectrum (RD spectrum) and the velocity dimension have minimum resolution (i.e., discrete range gates in the range dimension and discrete velocity gates in the velocity dimension), one or more range gates can be selected on the 2D FFT plane (the plane formed by the range and velocity dimensions) created by a single detection. Figure 9 Select the k-th distance gate, the (k+1)-th distance gate, and the (k+2)-th distance gate, and perform energy distribution statistics along the velocity dimension to obtain the number of samples corresponding to multiple first energy values.

[0107] According to one embodiment of the present invention, the interference detection method 10 provided by the present invention can perform the above-mentioned statistics in the form of a histogram. Wherein:

[0108] Based on a preset distance gate (one or more distance gates selected on the 2D FFT plane), energy intervals are divided along the velocity dimension, and the number of samples in each interval is counted. The energy values ​​in the energy dimension are then reduced by one or more preset significant bits to form the first energy value. For example, to concentrate the number of energy value samples, the last three least significant bits of the energy value in the energy dimension are ignored, and the most significant bits are used for merging. A statistical histogram is generated based on the number of samples corresponding to multiple first energy values. That is, when samples with the same first energy value are obtained, the number of samples corresponding to that first energy value is incremented by 1. The horizontal axis of the statistical histogram can be the logarithm of the first energy value, and the vertical axis can correspond to the number of samples for the first energy value.

[0109] An implementation of generating statistical histograms, for example Figure 10 As shown.

[0110] In step S103, the sum of energy within a preset energy range is calculated based on the number of samples corresponding to the plurality of first energy values. The interference detection method 10 provided in this embodiment of the invention can define a preset energy range in the generated statistical histogram.

[0111] According to one embodiment of the present invention, such as Figure 10 As shown, the first energy value with the largest number of samples is taken as the noise floor energy value, the maximum value of the first energy value is taken as the peak energy value, and the interval between the noise floor energy value and the peak energy value is taken as the preset energy interval. As another possible embodiment, the interval between the median value of the first energy value in the statistical histogram and the maximum value of the first energy value can also be taken as the aforementioned preset energy interval. As another possible embodiment, the median value of the first energy value in the statistical histogram can also be taken as the noise floor energy value.

[0112] According to one embodiment of the present invention, such as Figure 10 As shown, the calculation of the energy within the preset energy range may include:

[0113] Within the preset energy range of the statistical histogram, the sum of multiple first energy values ​​multiplied by the corresponding number of samples is calculated.

[0114] Let's assume Figure 10 The noise floor energy value shown is P1, the number of samples is N1, and the peak energy value is P. m The sample size is N m If multiple first energy values ​​are arranged sequentially during this period, then the sum of the energy values ​​within the preset energy range is:

[0115]

[0116] In step S104, the energy is used to determine whether the radar signal includes interference signals.

[0117] According to an embodiment of the present invention, in the method 10 for interference detection of LFMCW millimeter-wave radar, the step of determining whether the radar signal includes an interference signal based on the energy includes:

[0118] When the sum of the energy values ​​is greater than a first threshold, it is determined that the radar signal includes an interference signal.

[0119] The first threshold can be obtained by measurement in an interference-free experimental environment or by simulation. After two-dimensional fast Fourier transform (FFT), the energy distribution obtained by statistically analyzing one or more preset distance gates along the velocity dimension usually conforms to a Gaussian distribution. In the presence of a large amount of noise, the energy corresponding to the noise frequency component appears in the interval from the noise floor energy value to the peak energy value, and the sum of these components exceeds the first threshold.

[0120] According to an embodiment of the present invention, for any frame of the radar signal, determining whether the radar signal includes interference signals based on the energy may include:

[0121] Calculate the difference between the sum of the energy of adjacent frames and the current frame. When the difference is greater than a second threshold, determine that the radar signal of the current frame includes an interference signal.

[0122] In two adjacent detections, the energy distribution corresponding to the same range gate has a small difference. Therefore, the statistical energy distribution of the same preset range gate in the current frame and its adjacent frames is calculated. That is, based on one or more preset range gates, the energy distribution is statistically analyzed along the velocity dimension to obtain the number of samples corresponding to multiple first energy values, and a statistical histogram is generated. Then, according to the same calculation standard, such as calculating the sum of energy from the noise floor energy value to the peak energy value, the sum of energy in the current frame is compared with that in the adjacent frames. When the difference between the sum of energy in the adjacent frames and the current frame is greater than a second threshold, it is determined that the radar signal in the current frame includes an interference signal.

[0123] Figure 11a -b illustrates yet another example of processing raw data from an LFMCW millimeter-wave radar using the interference detection method 10 provided by this invention. For example... Figure 11a As shown, in one detection by the LFMCW millimeter-wave radar, a two-dimensional Fast Fourier Transform (FFT) was performed on the raw radar data. For the FFT data, the 59th range gate (a preset range gate) was selected to perform energy distribution statistics along the velocity dimension, generating the statistical histogram shown in the figure. Figure 11b As shown, the first energy value corresponding to the highest number of samples is taken as the noise floor energy value, and the maximum value of the first energy value is taken as the peak energy value. The sum of energy between the noise floor energy value and the peak energy value is calculated, i.e., energy summation. The calculated energy sum is greater than the detection threshold set for the 59th range gate of this LFMCW millimeter-wave radar, so it is determined that there is interference in this frame of raw data.

[0124] The interference detection method for millimeter-wave radar provided by this invention uses detection data (2D FFT data) to perform interference detection while detecting the distance and speed of the target object, which simplifies the calculation process, saves computing power, and improves the speed of processing raw radar data.

[0125] As mentioned above, due to the presence of interference signals, the range-Doppler spectrum generated after the signal processing unit performs a two-dimensional fast Fourier transform on the mixed signal may exhibit false alarms. To address the false alarm problem, an appropriate detection threshold needs to be set. If the detection threshold is set too high, some weak targets will not be detected; if the detection threshold is set too low, some noise energy may be detected, resulting in false alarms. The detection threshold is usually set based on the distance between the target and the LFMCW millimeter-wave radar. Since the LFMCW millimeter-wave radar has a minimum range resolution, different detection thresholds can be set according to different range thresholds.

[0126] Commonly used constant false alarm rate (CFAR) detection algorithms include CA-CFAR, SOGO-CFAR, and OS-CFAR. OS-CFAR is widely used due to its excellent detection performance. However, OS-CFAR requires sorting the input data, which is time-consuming. In automotive millimeter-wave radar applications, there are high requirements for the real-time performance of the algorithm. As the resolution of automotive millimeter-wave radar increases, the amount of 2D-FFT data also grows larger. At this point, the time consumption of CFAR detection becomes a bottleneck restricting the system's real-time performance.

[0127] To address the constant false alarm rate (CFAR) problem of LFMCW millimeter-wave radar, this invention also provides a method 20 for interference detection of LFMCW millimeter-wave radar, wherein the LFMCW millimeter-wave radar receives millimeter-wave signals and converts them into radar signals, and the millimeter-wave signals include echoes emitted by the LFMCW millimeter-wave radar and reflected by a target. Figure 12 As shown, the interference detection method 20 includes steps S101 to S104. Wherein:

[0128] In step S101, a two-dimensional fast Fourier transform (FFT) is performed on the radar signal to obtain the range-Doppler spectrum (RD spectrum), wherein the range-Doppler spectrum includes range, velocity, and energy dimensions. As described above, the LFMCW millimeter-wave radar transmits a continuous wave with a frequency that changes linearly with time. The radar signal is generated by mixing the millimeter-wave signal received by the LFMCW millimeter-wave radar with the continuous wave signal transmitted by the LFMCW millimeter-wave radar. By performing a two-dimensional fast Fourier transform (FFT) on the radar signal (mixed signal), the following is obtained: Figure 5 or Figure 7 The distance-Doppler spectrum shown. Figure 5 or Figure 7 As an example of range-Doppler spectrum, the range-Doppler spectrum will present different distributions depending on the transmitted frequency modulation signal, target information and real-time interference information. Range-Doppler spectra with different distributions are all applicable to the interference detection method 20 provided by this invention.

[0129] In step S102, within the range-Doppler spectrum, energy distribution statistics are performed along the velocity dimension for a preset range gate to obtain the number of samples corresponding to multiple first energy values. For example... Figure 9As shown, since both the range-Doppler spectrum (RD spectrum) and the velocity dimension have minimum resolution (i.e., discrete range gates in the range dimension and discrete velocity gates in the velocity dimension), one or more range gates can be selected on the 2D FFT plane (the plane formed by the range and velocity dimensions) created by a single detection. Figure 9 Select the k-th distance gate, the (k+1)-th distance gate, and the (k+2)-th distance gate, and perform energy distribution statistics along the velocity dimension to obtain the number of samples corresponding to multiple first energy values.

[0130] According to one embodiment of the present invention, when the range and / or velocity range of possible detection targets are known, energy distribution statistics are performed on the range-Doppler spectrum (RD spectrum) for the range and / or velocity range of possible detection targets to obtain the number of samples corresponding to multiple first energy values. For example... Figure 13 As shown, based on the possible range and velocity range of the detection target, preset distance gates and preset velocity gates are selected. Figure 13 Select the k-th distance gate, the (k+1)-th distance gate, and the (k+2)-th distance gate, as well as the l-th speed gate, the (l+1)-th distance gate, and the (l+2)-th distance gate.

[0131] According to one embodiment of the present invention, the interference detection method 20 provided by the present invention uses a histogram to perform the above-mentioned statistics. Wherein:

[0132] Based on a preset distance gate (one or more distance gates selected on the 2D FFT plane), energy distribution statistics are performed along the velocity dimension. One or more preset significant bits are removed from the energy values ​​in this dimension to form the first energy value. For example, to concentrate the sample number of energy values, the last three least significant bits of the energy values ​​in this dimension are ignored, and the most significant bits are used for merging. A statistical histogram is generated based on the sample counts corresponding to multiple first energy values. That is, when samples with the same first energy value are obtained, the sample count corresponding to that first energy value is incremented by 1.

[0133] Optionally, the horizontal axis of the statistical histogram is the logarithm of the first energy value, and the vertical axis is the number of samples of the first energy value.

[0134] An implementation of generating statistical histograms, for example Figure 10 As shown.

[0135] In step S103, based on the number of samples corresponding to the plurality of first energy values, the Kth sample is searched in the statistical histogram, where K is a preset ordinal number. For example, based on the statistical histogram, the total number of samples for the first energy value is N, and K = N / 2 is taken.

[0136] In step S104, a detection threshold is set based on the first energy value of the Kth sample.

[0137] like Figure 14 As shown, there are 128 samples in the statistical histogram corresponding to the preset distance gate; the 64th sample from the smallest to the largest is selected. Figure 14 In the statistical histogram shown, the energy range of the 64th sample is approximately -13.8 dB. This energy value can be set as the detection threshold for the corresponding distance gate.

[0138] According to one embodiment of the present invention, the Kth first energy value is multiplied by a preset factor and set as the detection threshold of the corresponding distance gate. For example: in Figure 14 In the statistical histogram shown, the energy range of the 64th sample is approximately -13.8dB. Twice this first energy value, i.e., -10.8dB, is set as the detection threshold of the corresponding distance gate.

[0139] The interference detection method provided in this invention detects the distance and speed of the target object and uses the detection data (2D FFT data) to form a statistical histogram, and then performs constant false alarm rate (CFAR) processing. Compared with the OS-CFAR algorithm in the prior art, the time complexity of the sorting operation is reduced from O(N2) or O(Nlog(N)) to O(N), which can significantly improve the real-time performance of signal processing and is more suitable for vehicle-mounted millimeter-wave radar.

[0140] It should be noted that, in this embodiment of the invention, histogram statistics can be performed on the energy of only a few distance gates for interference detection, rather than performing histogram statistics on all distance gates, to further reduce the amount of data processing and the processing resources consumed by the system. Furthermore, when calculating the range of the energy sum of a certain distance gate, it can be a predetermined number of intervals extending from the peak interval towards the center of the histogram (the specific number of intervals can be based on empirical values ​​obtained through big data analysis in the actual application scenario), rather than necessarily selecting the noise floor interval as the benchmark or boundary for dividing a specific region in interference detection. Additionally, by comparing the differences between the interval energy sums of the distance gate histograms of adjacent frames, and determining that an interval energy sum jump occurs and the jump amplitude exceeds a certain threshold, the current signal can be output as being interfered with.

[0141] In summary, in a radar system, if the transmitter transmits M LFMCW waveform pulses per frame, the receiver, upon receiving the echo signals corresponding to these M LFMCW waveform pulses, can first sample each pulse, assuming each pulse obtains N equally spaced sampling points. Then, an N-point range-dimensional FFT is performed on each pulse with N sampling points, yielding M sets of N-point range-dimensional FFT data. From these M sets of N-point range-dimensional FFT data, M data points with the same index value (index value range dimension 1, 2, ..., n...N) are extracted and subjected to an M-point Doppler-dimensional FFT, resulting in N sets of M-point Doppler-dimensional FFT data, i.e., the final 2D FFT data. The 2D FFT data plane is shown below. Figure 7 As shown. When estimating the energy of the nth distance gate, take out M 2D FFT energy data along the Doppler dimension of the distance gate: P1, P2...PM, perform histogram statistics on these data to obtain the noise floor interval and the peak interval, and calculate the sum of the energy of all intervals between the two in the histogram.

[0142] In the interference detection method provided in this embodiment of the invention, histogram statistics can be performed on the Doppler values ​​of different range gates on the 2D-FFT plane. The energy range with the highest sample frequency can be taken as the noise floor range of the range gate, and the edge range of the histogram can be taken as the peak range. Then, by summing the energy of all ranges between the noise floor range and the peak range in the histogram (wherein, the energy sum may or may not include the energy sum of the noise floor range and the peak range, and the distance can be set according to actual needs), if the energy sum exceeds a certain threshold, it can be determined that interference has been detected, that is, the current range gate is interfered with, which facilitates signal processing such as interference suppression for the range gate or the frame signal. Specifically, the energy sum of each range can be calculated by multiplying the energy represented by each energy range by the number of samples in that range; then, for a specific range range (such as all ranges between the noise floor range and the peak range in the histogram), the energy sum of all ranges is accumulated to obtain the energy sum of all samples in these ranges, which is used for subsequent interference detection. In these embodiments, since the noise floor energy estimate is obtained through histogram statistics, it can be used not only for interference detection but also for target detection in CFAR, thereby achieving noise floor energy sharing. Furthermore, using the total energy as the basis for interference detection improves the robustness of interference detection in practical applications.

[0143] According to one embodiment of the present invention, such as Figure 15As shown, the present invention also provides an interference detection device 200, which is used to process radar signals from an LFMCW millimeter-wave radar. The interference detection device 200 includes: an FFT module 210, a histogram generation module 220, and an interference judgment module 230. The FFT module 210 is configured to perform a two-dimensional fast Fourier transform on the radar signal to obtain a range-Doppler spectrum, wherein the range-Doppler spectrum includes a range dimension, a velocity dimension, and an energy dimension.

[0144] The histogram generation module 220 is coupled to the FFT module 210 and configured to: perform energy distribution statistics on the distance-Doppler spectrum according to the preset distance gate velocity dimension to obtain the number of samples corresponding to multiple first energy values; and generate a statistical histogram based on the number of samples corresponding to the multiple first energy values.

[0145] The interference determination module 230 is coupled to the histogram generation module 220 and configured to perform interference detection or constant false alarm rate processing on the radar signal based on the statistical histogram.

[0146] According to an embodiment of the present invention, in the interference detection device 200, the histogram generation module 220 is further configured to: remove one or more preset valid bits from the energy value on the energy dimension to form the first energy value; wherein the horizontal axis of the statistical histogram is the logarithm of the first energy value, and the vertical axis is the number of samples of the first energy value.

[0147] According to an embodiment of the present invention, in the interference detection device 200, the interference determination module 230 is further configured to: calculate the sum of energy within a preset energy range based on the statistical histogram; and determine whether the radar signal includes an interference signal based on the sum of energy.

[0148] According to one embodiment of the present invention, in the interference detection device 200, the preset energy range includes: the range from the first energy value corresponding to the highest value of the number of samples in the statistical histogram to the maximum value of the first energy value; or the range from the median value of the first energy value in the statistical histogram to the maximum value of the first energy value.

[0149] According to an embodiment of the present invention, in the interference detection device 200, the interference determination module 230 is further configured to: calculate the sum of multiple first energy values ​​multiplied by the corresponding number of samples within the preset energy range of the statistical histogram.

[0150] According to an embodiment of the present invention, in the interference detection device 200, the interference determination module 230 is further configured to: determine that the radar signal includes an interference signal when the sum of the energy is greater than a first threshold.

[0151] According to an embodiment of the present invention, in the interference detection device 200, the LFMCW millimeter-wave radar transmits a continuous wave signal whose frequency changes linearly with time multiple times, and generates a radar signal frame by mixing the millimeter-wave signal received by the LFMCW millimeter-wave radar with the continuous wave signal multiple times. The interference determination module 230 is further configured to: calculate the difference between the sum of the energy of the adjacent frames and the current frame, and determine that the radar signal of the current frame includes an interference signal when the difference is greater than a second threshold.

[0152] The specific limitations of the interference detection device 200 for LFMCW millimeter-wave radar described above are similar to those in the aforementioned interference detection methods 10 and 20. Please refer to the above descriptions of interference detection methods 10 and 20 for further details.

[0153] The interference detection device for millimeter-wave radar provided by this invention has a simple structure and is easy to integrate. The histogram generation module and interference detection and judgment module perform statistical and calculation operations on the FFT data of millimeter-wave radar, with a small amount of computation and fast interference detection / constant false alarm rate processing speed.

[0154] According to one embodiment of the present invention, such as Figure 13 As shown, the present invention also provides a millimeter-wave radar 300, comprising: a transmitting unit 310, a receiving unit 320, a mixing unit 330, an FFT unit 340, a histogram generation unit 350, and an interference determination unit 360. The transmitting unit 310 is configured to transmit a continuous wave whose frequency varies linearly with time. The receiving unit 320 is configured to receive millimeter-wave signals, including echoes transmitted by the transmitting unit and reflected by a target. The mixing unit 330 is coupled to the transmitting unit 310 and the receiving unit 320, and is configured to mix the millimeter-wave signal received by the receiving unit 320 with the continuous wave signal transmitted by the transmitting unit 310 to generate a radar signal. The FFT unit 340 is coupled to the mixing unit 330, and is configured to perform a two-dimensional fast Fourier transform on the radar signal to obtain a range-Doppler spectrum, the range-Doppler spectrum including a range dimension, a velocity dimension, and an energy dimension. The histogram generation unit 350 is coupled to the FFT unit 340 and configured to: perform energy distribution statistics on the range-Doppler spectrum according to a preset range gate velocity dimension to obtain the number of samples corresponding to multiple first energy values; and generate a statistical histogram based on the number of samples corresponding to the multiple first energy values. The interference determination unit 360 is coupled to the histogram generation unit 350 and configured to: perform interference detection or constant false alarm rate (CFAR) processing on the radar signal based on the statistical histogram.

[0155] According to one embodiment of the present invention, such as Figure 13As shown, the millimeter-wave radar 300 further includes a target detection unit 370. The target detection unit 370 is coupled to the FFT unit 340 and the interference determination unit 360, respectively, and configured such that when the interference determination unit 360 determines that the radar signal does not contain interference signals, the target detection unit 370 obtains the range and velocity of the target object in the range-Doppler spectrum based on the interference detection threshold after constant false alarm rate processing.

[0156] The millimeter-wave radar provided by this invention integrates an interference detection device including a histogram generation unit and an interference determination unit. It performs interference detection simultaneously with target detection. When the interference determination unit outputs a signal indicating interference in the current frame of data, the millimeter-wave radar discards that frame or retransmits a continuous wave signal with a frequency that changes linearly with time, and then re-detects the target. The interference detection device, including the histogram generation unit and the interference determination unit, has a simple structure, small size, and is easy to integrate. Its internal computational program has low complexity, enabling it to quickly and in real-time complete interference signal detection and data processing.

[0157] In an optional embodiment, the integrated circuit in this application embodiment can be a millimeter-wave radar chip. The types of digital functional modules in the integrated circuit can be determined according to actual needs. For example, in a millimeter-wave radar chip, the data processing module can be used for range Vidoff transformation, velocity Vidoff transformation, constant false alarm rate detection, direction of arrival detection, point cloud processing, etc., to acquire information such as the target's distance, angle, velocity, shape, size, surface roughness, and dielectric properties.

[0158] Optionally, the integrated circuit may be an AiP (Antenna-In-Package) chip structure, an AoP (Antenna-On-Package) chip structure, or an AoC (Antenna-On-Chip) chip structure.

[0159] In an optional embodiment, the integrated circuit may be equivalent to the radar chip described in any embodiment of this application, that is, they may have the same structure and function, and may be combined with each other to form a cascaded structure. For the sake of simplicity, it will not be described in detail here, but it should be understood that the technology that those skilled in the art should know based on the content described in this application should be included within the scope of this application.

[0160] In one embodiment, this application also provides a wireless device, comprising: a carrier; an integrated circuit as described in any of the above embodiments, wherein the integrated circuit may be disposed on the carrier; and an antenna disposed on the carrier, or integrated with the integrated circuit as a single device disposed on the carrier (i.e., the antenna may be an antenna disposed in an AiP, AoP, or AoC structure); wherein the integrated circuit is connected to the antenna (i.e., the sensing chip or integrated circuit does not integrate an antenna, such as a conventional SoC), and is used to transmit and receive radio signals. The carrier may be a printed circuit board (PCB), and the first transmission line may be a PCB trace.

[0161] In one embodiment, this application also provides a wireless device, which may include: a carrier; an integrated circuit as described in any of the above embodiments; and an antenna disposed on the carrier, or integrated with the sensing chip or the integrated circuit as a single device disposed on the carrier (i.e., the antenna may be an antenna disposed in an AiP or AoC structure); wherein the sensing chip or the integrated circuit is connected to the antenna via a first transmission line (i.e., the integrated circuit does not have an integrated antenna, and may be a SoC chip, etc.), for transmitting and receiving radio signals. The carrier may be a printed circuit board (PCB) (such as a development board, data acquisition board, or the motherboard of a device, etc.).

[0162] In one embodiment, this application also provides a terminal device, including: a device body; and a wireless device disposed on the device body as described in any of the above embodiments; wherein the wireless device can be used to implement functions such as target detection and / or wireless communication.

[0163] Specifically, based on the above embodiments, in one optional embodiment of this application, the wireless device may be disposed outside the device body or inside the device body. In other optional embodiments of this application, the wireless device may be partially disposed inside the device body and partially disposed outside the device body. This application does not limit the specific implementation; it may be determined according to the circumstances.

[0164] In an optional embodiment, the aforementioned device body can be a component or product applied in fields such as smart cities, smart homes, transportation, smart homes, consumer electronics, security monitoring, industrial automation, in-cabin detection (such as smart cockpits), medical devices, and healthcare. For example, the device body can be intelligent transportation equipment (such as automobiles, bicycles, motorcycles, ships, subways, trains, etc.), security equipment (such as cameras), liquid level / flow rate detection equipment, smart wearable devices (such as wristbands, glasses, etc.), smart home devices (such as robot vacuum cleaners, door locks, televisions, air conditioners, smart lights, etc.), various communication devices (such as mobile phones, tablets, etc.), as well as devices such as barriers, intelligent traffic lights, intelligent signs, traffic cameras, and various industrial robotic arms (or robots). It can also be various instruments for detecting vital signs parameters and various devices equipped with such instruments, such as in-cabin vital sign detection in automobiles, indoor personnel monitoring, smart medical devices, and consumer electronic devices.

[0165] The wireless device may be any of the wireless devices described in any embodiment of this application. The structure and working principle of the wireless device have been described in detail in the above embodiments, and will not be repeated here.

[0166] It should be noted that wireless devices can transmit and receive radio signals to achieve functions such as target detection and / or communication, thereby providing the device body with target detection information and / or communication information, and thus assisting or even controlling the operation of the device body.

[0167] For example, when the aforementioned device is applied to an advanced driver assistance system (ADAS), wireless devices (such as millimeter-wave radar) used as vehicle sensors can assist the ADAS system in realizing application scenarios such as adaptive cruise control, automatic braking assist (AEB), blind spot detection warning (BSD), lane change assist warning (LCA), rear cross traffic alert (RCTA), parking assist, rear vehicle warning, collision avoidance, and pedestrian detection.

[0168] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0169] The above-described embodiments merely illustrate preferred embodiments of the present invention and the technical principles employed. While the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. Those skilled in the art can make various obvious changes, readjustments, and substitutions without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments. Many other equivalent embodiments may be included without departing from the inventive concept, and the scope of protection of this patent is determined by the appended claims.

Claims

1. A method for interference detection, characterized in that, The method includes: A two-dimensional fast Fourier transform is performed on the received signal to obtain the range-Doppler spectrum, which includes a range dimension, a velocity dimension, and an energy dimension. In the range-Doppler spectrum, for a preset range gate, the distribution statistics of the energy dimension are performed along the velocity dimension to obtain an energy statistical histogram; Based on the statistical characteristics of the energy statistical histogram, interference detection is performed on the preset distance gate, including: The energy value interval with the largest number of samples in the energy statistical histogram is taken as the noise floor interval; The sum of the energy values ​​in the noise floor range and the peak energy range is obtained as the first energy sum; and, Based on the first energy, it is determined whether the preset distance gate is subject to interference.

2. The method of claim 1, wherein the method further comprises: Constant false alarm rate (CFAR) detection is performed based on the statistical characteristics of the energy statistical histogram.

3. The method of claim 1 or 2, wherein the distance-Doppler spectrum has discrete distance gates on the distance dimension, and the preset distance gates include at least one of the distance gates.

4. The method as described in claim 1 or 2, wherein energy dimension distribution statistics are performed on the velocity dimension along a preset distance gate to obtain an energy statistical histogram; comprising: The energy values ​​in the energy dimension are discretized to obtain multiple energy value intervals that are continuously distributed at equal intervals according to their energy magnitude. The number of samples located in each energy value interval within the preset distance gate is counted to generate the energy statistical histogram.

5. The method of claim 4, wherein energy distribution statistics are performed on the velocity dimension along the preset distance gate to obtain an energy statistics histogram; further comprising: After preprocessing the energy values ​​in the energy dimension, the values ​​are discretized to obtain the multiple energy value intervals that are continuously distributed at equal intervals. Preprocessing includes normalization or logarithmic operations.

6. The method of claim 5, further comprising: Obtain the sum of the energy values ​​of all energy value intervals located between the noise floor interval and the peak energy value interval, and add the first energy sum to obtain the second energy sum; Based on the second energy, it is determined whether the preset distance gate is subject to interference.

7. The method of claim 5, wherein the noise floor interval may further be the energy value interval in which the median value of the energy value in the statistical histogram is located.

8. The method of any one of claims 5-7, further comprising: For any energy value range, determine the effective energy value of that energy value range, and multiply the number of samples by the effective energy value to obtain the energy sum corresponding to that energy value range.

9. The method of claim 6, wherein determining whether the preset distance gate is interfered with based on the second energy includes: When the second energy is greater than a preset first threshold, it is determined that the radar signal includes an interference signal.

10. The method of claim 6, wherein determining whether the preset distance gate is interfered with based on the second energy includes: Calculate the difference between the sum of energy in the current frame and the adjacent frames. When the difference is greater than a second threshold, it is determined that the radar signal in the current frame is interfered with.

11. An interference detection device, characterized in that, The interference detection device includes: The FFT module is configured to perform two-dimensional fast Fourier transform on pairs of received signals to obtain a range-Doppler spectrum, which includes a range dimension, a velocity dimension, and an energy dimension. The histogram generation module, coupled to the FFT module, is configured as follows: In the range-Doppler spectrum, for a preset range gate, the distribution statistics of the energy dimension are performed along the velocity dimension to obtain an energy statistical histogram; The interference determination module, coupled to the histogram generation module, is configured as follows: Based on the statistical characteristics of the energy statistical histogram, interference detection is performed on the preset distance gate, including: The energy value interval with the largest number of samples in the energy statistical histogram is taken as the noise floor interval; The sum of the energy values ​​of all energy value intervals from the noise floor interval to the peak energy value interval is obtained as the second energy sum; When the sum of the second energy and the first threshold is greater than the first threshold, it is determined that there is interference; or, Calculate the difference between the second energy sum of the current frame and the adjacent frames. When the difference is greater than the second threshold, it is determined that the current frame is interfered with.

12. A method for interference detection, characterized in that, The method includes: Discretized spectrum analysis is performed on the received signal to obtain spectrum data that includes the energy dimension; Based on the aforementioned spectrum data, for preset data points in a specific dimension, energy distribution statistics are performed along the velocity dimension to obtain an energy statistical histogram; and Based on the statistical characteristics of the energy statistical histogram, interference detection is performed on the received signal; The interference detection of the received signal includes: The energy value interval with the largest number of samples in the energy statistical histogram is taken as the noise floor interval; The sum of the energy values ​​in the noise floor range and the peak energy range is obtained as the first energy sum; and, Based on the first energy, it is determined whether the preset data points on the specific dimension are subject to interference.

13. An integrated circuit, characterized in that, It includes a radio frequency module, an analog signal processing module, and a digital signal processing module connected in sequence; The radio frequency module is used to generate radio frequency transmission signals and receive radio frequency reception signals; The analog signal processing module is used to down-frequency the received radio frequency signal to obtain an intermediate frequency signal; The digital signal processing module is used to perform analog-to-digital conversion on the intermediate frequency signal to obtain a digital signal; as well as A data processing module is used to process the digital signal to achieve target detection and / or wireless communication; The data processing module also performs interference detection using the method described in any one of claims 1-10 and 12.

14. The integrated circuit according to claim 13, characterized in that, The integrated circuit is a millimeter-wave radar chip.

15. A wireless device, characterized in that, include: Carrier; The integrated circuit as described in claim 13 or 14 is disposed on the carrier. An antenna is disposed on the carrier, or the antenna and the integrated circuit are integrated into a single device and disposed on the carrier. The integrated circuit is connected to the antenna and is used to transmit the radio frequency transmission signal and / or receive the radio frequency reception signal.

16. A terminal device, characterized in that, include: Equipment body; as well as The wireless device as described in claim 15 is disposed on the device body; The wireless device is used for target detection and / or communication to provide reference information for the operation of the device body.

Images