CN116679275A - FMCW millimeter wave automobile anti-collision radar signal processing board based on FPGA - Google Patents
FMCW millimeter wave automobile anti-collision radar signal processing board based on FPGA Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/414—Discriminating targets with respect to background clutter
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
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Abstract
The invention discloses an FMCW millimeter wave automobile anti-collision radar signal processing board based on an FPGA, which belongs to the technical field of automobile anti-collision, and comprises a signal board module and an algorithm module which is built in the signal board module; the algorithm module processes the signals through a time-frequency analysis method; at the same time, the algorithm module employs a modified GO-CFAR detector to suppress interference. Through the mode, the method reduces the cost by using the hardware structure based on the FPGA, and enhances the robustness in the complex road environment by suppressing the hidden interference and noise in the echo signal through time-frequency analysis and a large constant false alarm rate (GO-CFAR) algorithm; the radar echo signal parameter extraction method can accurately extract parameters of radar echo signals, can accurately detect moving and static targets of all vehicles in a radar scanning area, and has the functions of distance and speed measurement.
Description
Technical Field
The invention relates to the technical field of automobile anti-collision, in particular to an FMCW millimeter wave automobile anti-collision radar signal processing board based on an FPGA.
Background
Millimeter wave radars have a wide application potential in civilian fields, particularly in traffic fields. In recent decades, millimeter wave radar has become a hotspot for research due to its perfect performance in target detection, such as high resolution, micro power consumption, small volume, almost all-weather operation, etc.
The automobile anti-collision radar can reduce the occurrence probability of traffic accidents and can be widely applied to improving the safety of vehicles. As early as the 80 s of the 20 th century, seehausenG proposed a 24ghz fmcw radar system for transmitting traffic information. There have also been studies to propose a 77GHz radar for automotive Auto Cruise Control (ACC), russelme et al propose a design to make the radar more robust in complex road environments.
Over the years, methods have been developed to provide high probability of detection (Pd) of a detection target, as well as high resolution and high accuracy of estimating parameters. For example, there have been studies to design an algorithm to improve path and trajectory prediction of target vehicles in collision warning and avoidance systems. HanJ et al propose a road boundary and obstacle detection method using a joint vision detection and ranging sensor.
Despite the extensive research accumulation, it is still difficult to achieve millimeter wave radar systems that provide powerful performance at low cost in the automotive anti-collision application market.
Based on the problems, the invention designs an FMCW millimeter wave automobile anti-collision radar signal processing board based on an FPGA to solve the problems.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an FMCW millimeter wave automobile anti-collision radar signal processing board based on an FPGA.
In order to achieve the above purpose, the invention is realized by the following technical scheme:
an FMCW millimeter wave automobile anti-collision radar signal processing board based on an FPGA comprises a signal board module and an algorithm module which is built in the signal board module; the algorithm module processes the signals through a time-frequency analysis method;
the algorithm module performs the same processing on the rising period and the falling period of the FMCW triangular wave respectively, and then performs pairing processing on the results of the two processes to obtain target parameters (A, R and V);
meanwhile, the algorithm module adopts the improved GO-CFAR detector to inhibit interference, and comprises the following steps:
(1) In the process of summing the data in the front M/2 unit and the rear M/2 unit of the input data, selecting the largest one for elimination;
(2) Then selecting the largest Q of the summation results V1 and U1, multiplying the largest Q by the attenuation factor T to obtain TQ, and adding the TQ and the input data Q k And (3) comparing the central data of the data to obtain a judgment result.
Still further, the signal board module includes a low pass filter LPF, a direct digital frequency synthesizer DDS, a programmable gain amplifier PGA, an analog-to-digital converter ADC, a bat selectable amplifier, a field programmable gate array FPGA, an electrified erasable programmable read only memory E2PROM, an RS-232 standard interface, an ethernet interface, a button, and a power supply.
Furthermore, the low pass filter LPF is connected to the field programmable gate array FPGA through a direct digital frequency synthesizer DDS.
Furthermore, the two paths of programmable gain amplifier PGA are respectively connected with the field programmable gate array FPGA through the analog-digital converter ADC.
Furthermore, the two paths of the bean selectable amplifiers are respectively connected with the field programmable gate array FPGA through the analog-digital converter ADC.
Furthermore, the charged erasable programmable read-only memory E2PROM, the RS-232 standard interface, the Ethernet interface and the button are all connected with the field programmable gate array FPGA.
Still further, the algorithm module is built into the programmable gain amplifier PGA.
Furthermore, the algorithm module performs the same processing on the rising period and the falling period of the FMCW triangular wave respectively, and then performs pairing processing on the results of the two processes to obtain target parameters (A, R, V); the method comprises the following specific steps:
(1) The ZIF signals are sampled and quantized by an analog-to-digital converter ADC to obtain digital signals, and the digital signals are sent to a field programmable gate array FPGA for further processing;
the method comprises the following steps: using complex signal expression, for a suspected target, the signal is expressed as:
Ae j[2πfb+p]
wherein A represents the amplitude of the target reflected signal, specifically A (f); p is the phase, specifically P (f); fb is the frequency of the reflected signal;
(2) After the fast Fourier transform processing, extracting the amplitude and phase information of the suspected target, and carrying out two-dimensional fast Fourier transform analysis on the fast Fourier transform output slow-change signal, and carrying out moving target detection in the Doppler domain to obtain the speed information of the suspected target;
(3) Pairing the two identical processing results of the frequency-modulated triangular wave, and comparing the suspected target information with standard thresholds (Aref, vref, vdr) to obtain target (A, R, V) parameters;
(4) Carrying out correlation processing on the multi-frame parameters in a decision domain to obtain a final decision result;
(5) And finally framing according to a certain mode to form radar data, and transmitting the radar data to an upper computer for display.
Further, an improved GO-CFAR detector is employed to suppress interference, comprising the steps of:
(1) In the input data q k Front M/2 and rear M/2 unitsIn the process of data summation, the largest one is selected for rejection;
(2) Then selecting the largest Q of the summation results V1 and U1, multiplying the largest Q by the attenuation factor T to obtain TQ, and adding the TQ and the input data Q k The center data of the data are compared to obtain a judgment result;
wherein q k Representing amplitude data a (f) after the FFT processing, and TQ corresponding thereto represents an amplitude threshold (Aref).
Advantageous effects
According to the invention, the cost is reduced by using a hardware structure based on an FPGA, and the robustness in a complex road environment is enhanced by suppressing the hidden interference and noise in an echo signal through time-frequency analysis and a large constant false alarm rate (GO-CFAR) algorithm; parameters of radar echo signals can be accurately extracted; the FMCW millimeter wave automobile anti-collision radar signal processing board based on the FPGA can accurately detect the moving and static targets of all vehicles in a radar scanning area and has the functions of distance and speed measurement; for example, the target and the estimated parameters can be detected well in a highway environment.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is evident that the drawings in the following description are only some embodiments of the present invention and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a block diagram of a signal board module in an FMCW millimeter wave automobile anti-collision radar signal processing board based on an FPGA of the present invention;
FIG. 2 is a block diagram of an algorithm module in an FMCW millimeter wave automobile anti-collision radar signal processing board based on an FPGA;
FIG. 3 is a schematic diagram of the GO-CFAR algorithm in the algorithm module;
FIG. 4 is a graph showing the performance detection of the GO-CFAR algorithm;
fig. 5 is a field test result of the FMCW millimeter wave automotive anti-collision radar signal processing board based on the FPGA of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention is further described below with reference to examples.
Example 1
Referring to fig. 1-3 of the specification, an FMCW millimeter wave automobile anti-collision radar signal processing board based on an FPGA comprises a signal board module and an algorithm module built in the signal board module;
the signal board module includes:
a low pass filter LPF (Low Pass Filter);
a direct digital frequency synthesizer DDS (Direct Digital Synthesizer);
a programmable gain amplifier PGA (Programmable Gain Amplifier);
analog-to-digital converter ADC (Analog-to-digital converter);
the bean amplifier is a bean Amp with selectable bean amplifiers, can form double-path complex signal receiving during selection to form a one-transmitting double-receiving three-antenna system, and has an angle measuring function; when not selected, a transmitting-receiving double-antenna system is formed;
a field programmable gate array FPGA (Field Programmable Gate Array);
charged erasable programmable read-Only Memory E2PROM (Electrically Erasable Programmable Read-Only Memory);
RS-232 standard interface;
an ethernet (earth) interface;
buttons for start, time, end, etc.;
a power supply for supplying power to the above structure;
the low pass filter LPF is connected with the field programmable gate array FPGA through a direct digital frequency synthesizer DDS;
the two paths of programmable gain amplifier PGAs are respectively connected with the field programmable gate array FPGA through an analog-digital converter ADC;
the two paths of the bean selectable amplifiers are respectively connected with the field programmable gate array FPGA through an analog-digital converter ADC;
the charged erasable programmable read-only memory E2PROM, the RS-232 standard interface, the Ethernet (Earth) interface and the button are all connected with the field programmable gate array FPGA;
a direct digital frequency synthesizer DDS is configured through a field programmable gate array FPGA to form a continuous triangular wave sweep signal with a sweep frequency Fm, and the continuous triangular wave sweep signal is sent to a radio frequency front end after passing through a low pass filter LFP to form an FMCW signal with a certain frequency; mixing a target transmitting signal through a front end to form Fb (one or two paths of I/Q signals), and entering a Field Programmable Gate Array (FPGA) for further signal processing after passing through a Programmable Gain Amplifier (PGA) and an analog-digital converter (ADC); the system provides two interfaces, namely RS232 and Ethernet (Earth), to communicate with the upper computer for transmitting radar data (Radar data);
the front end can select an antenna with a transmitter and a receiver for angle measurement, the azimuth angle of the target can be measured by adopting a phase-contrast mode by using two receiving antennas, and the horizontal position of the target can be determined together with the distance parameter; for coherent demodulation of the front end and ZIF radar echo signals, the rear end finishes the digitization and parameter extraction of radar targets; meanwhile, the rear end provides a required time-frequency triangular wave scanning signal for the front end, the signal is converted into a millimeter wave frequency band through phase locking and a plurality of frequency chips and then sent out, and the rear end can be ensured to directly generate high-precision synchronous information;
the algorithm module is built in the programmable gain amplifier PGA; the algorithm module processes the signals through a time-frequency analysis method;
because targets at different distances have different echo heterodyning frequencies, targets at different speeds have the same Doppler frequency shift; pairing the results after analyzing the positive slope and the negative slope on the triangular wave; in this way, the speed and distance of the radar target can be calculated; the correlation of multiple frames of scan data can reduce the floating effect of Radar Cross Section (RCS);
the millimeter wave FMCW signal is generated by a VCO that is excited by the modulated signal from the back end; a part of the millimeter wave signal is transmitted by an antenna, and the other part is taken as a local oscillation signal and is directly coupled to a mixer of a receiver; when an advancing transmitted signal encounters a target, the signal is partially reflected as an echo signal; the echo signal is received by an antenna and enters a mixer, then is mixed with a local oscillator signal, and a high-frequency part is removed by a low-pass filter, so that a Zero Intermediate Frequency (ZIF) signal is output; since the amplitude of ZIF signals is typically small, pre-processing, such as amplification and filtering, is required to eliminate unnecessary interference outside the bandwidth; the digitized ZIF signal is then sent to a subsequent signal processing section; the distance and the speed of the target can be determined through FFT and related processing; the same processing is carried out on the rising period and the falling period of the FMCW triangular wave respectively, and then the results of the two processes are paired to obtain target parameters (A, R, V);
the method comprises the following specific steps:
(1) The ZIF signals are sampled and quantized by an analog-to-digital converter ADC to obtain digital signals, and the digital signals are sent to a field programmable gate array FPGA for further processing;
the method comprises the following steps: using complex signal expression, for a suspected target, the signal is expressed as:
Ae j[2πfb+p]
wherein A represents the amplitude of the target reflected signal, specifically A (f); p is the phase, specifically P (f); fb is the frequency of the reflected signal;
because the amplitude and the phase of the target echo are functions of the frequency f, the whole radar digital signal processing is based on the fast Fourier transform FFT (Fast Fourier Transformation) of the frequency domain so as to extract the target parameters;
(2) Extracting amplitude (A (f)) and phase (P (f)) information of a suspected target through Fast Fourier Transform (FFT), performing two-dimensional Fast Fourier Transform (FFT) analysis on a slow-change signal output by the Fast Fourier Transform (FFT), and performing Moving Target Detection (MTD) in a Doppler domain to obtain speed information of the suspected target;
(3) Pairing the two identical processing results of the frequency-modulated triangular wave, and comparing the suspected target information with standard thresholds (Aref, vref, vdr) to obtain target (A, R, V) parameters;
(Aref, vref, vdr), amplitude, speed, distance, etc. reference thresholds;
(A, R, V), parameters of the extracted target amplitude, distance, speed and the like;
(4) Carrying out correlation processing on multi-frame parameters (Nc frames) in a decision domain to obtain a final decision result, wherein the final decision result comprises information of whether targets exist or not, the distance, the speed, the angle and the like of each target;
(5) Finally framing according to a certain mode to form radar data (Radar data), and transmitting the radar data to an upper computer for display;
preferably, in the step (3), during the process of comparing the suspected target information with the standard threshold, the false alarm probability may be affected by various interference and noise levels; the CA-CFAR detector is an algorithm (i.e., a method of adjusting the threshold) that maximizes the correct detection rate Pd while maintaining a constant false alarm probability to provide high reliability detection of radar targets; it is known that the severe degradation of the correct detection rate Pd in existing CA-CFAR detectors is caused by the presence of interference targets in the reference cell set; thus, the present invention employs an improved GO-CFAR detector to suppress interference, comprising the steps of:
(1) In the input data q k In the process of summing data in the front M/2 unit and the rear M/2 unit, selecting the largest one for rejection; meaning of M: the number of data units;
(2) Then selecting the largest Q of the summation results V1 and U1, multiplying the largest Q by the attenuation factor T to obtain TQ, and adding the TQ and the input data Q k The central data (data of the detected unit) are compared to obtain a judgment result, so that the influence of interference on the judgment result is effectively reduced; v1, U1 meaning: v and U are respectively picked outA value after dividing the respective maximum ones; v and U are the sum of the front M/2 and rear M/2 units, respectively;
wherein q k Representing amplitude data a (f) after processing of the fast fourier transform FFT (Fast Fourier Transformation), the TQ corresponding thereto representing an amplitude threshold (Aref);
the influence of interference noise on target detection can be reduced by adaptively adjusting a decision threshold through a GO-CFAR algorithm, so that constant false alarm probability detection is realized;
in the FMCW system radar, the frequency f is directly related to the distance, and the signal in a certain frequency range is taken for performing GO-CFAR calculation, namely the reflected signal in a certain distance range is taken for performing GO-CFAR calculation; q k The method is characterized in that the method comprises the steps of taking signals of a suspected target (vehicle and pedestrian) before and after a certain distance range to perform average operation, buckling out the largest signal (possibly a strong interference signal), selecting the largest summation signal, weighting (multiplying by T) to obtain a proper threshold TQ, reducing the influence of interference noise on a judgment (comparison) result, and effectively improving the correct detection rate (Pd).
Experimental example 1 Performance experiment of GO-CFAR algorithm
GO-CFAR at false alarm probability pf=10 -3 Signal-to-noise ratio snr= -5: 20. the performance under the conditions of data unit number m=16 and data length l=40000 is shown in fig. 4;
results: at m=16 and SNR > 0dB, the GO-CFAR algorithm has very high Pd (greater than 0.95).
Experimental example 2 in-situ detection
The measured scene and radar display interface is shown in fig. 5. Wherein, the index of front end is as follows: the center frequency is 24.15GHz, the scanning bandwidth is 200MHz, the scanning period is 1ms, and the maximum measurable target distance is 150m. The right side of the area is a measured scene, and the upper left area displays a display interface of the upper computer. From the figure it can be derived that the test environment has two target vehicles at 44-48 meters and 120 meters. Each concentric circle on the radar user interface represents a measured target distance plus 15 meters, so the measured target is located around the third concentric circle (about 45 meters) and near the eighth concentric circle (about 120 meters). The test structure shows that the actual position of the target and the measured value thereof are highly consistent, which verifies the correctness and the accuracy of the FMCW millimeter wave automobile anti-collision radar signal processing board based on the FPGA.
In summary, the invention reduces the cost by using the hardware structure based on the FPGA, and enhances the robustness in the complex road environment by suppressing the hidden interference and noise in the echo signal through the time-frequency analysis and the large constant false alarm rate (GO-CFAR) algorithm; parameters of radar echo signals can be accurately extracted; the FMCW millimeter wave automobile anti-collision radar signal processing board based on the FPGA can accurately detect the moving and static targets of all vehicles in a radar scanning area and has the functions of distance and speed measurement; for example, the target and the estimated parameters can be detected well in a highway environment.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. The utility model provides a FMCW millimeter wave car anticollision radar signal processing board based on FPGA, includes signal board module, its characterized in that:
the system also comprises an algorithm module which is built in the signal board module; the algorithm module processes the signals through a time-frequency analysis method;
the algorithm module performs the same processing on the rising period and the falling period of the FMCW triangular wave respectively, and then performs pairing processing on the results of the two processes to obtain target parameters (A, R and V);
meanwhile, the algorithm module adopts the improved GO-CFAR detector to inhibit interference, and comprises the following steps:
(1) In the process of summing the data in the front M/2 unit and the rear M/2 unit of the input data, selecting the largest one for elimination;
(2) Then selecting the largest Q of the summation results V1 and U1, multiplying the largest Q by the attenuation factor T to obtain TQ, and adding the TQ and the input data Q k And (3) comparing the central data of the data to obtain a judgment result.
2. The FPGA-based FMCW millimeter wave automotive anti-collision radar signal processing board of claim 1, wherein the signal board module includes a low pass filter LPF, a direct digital frequency synthesizer DDS, a programmable gain amplifier PGA, an analog-to-digital converter ADC, a bat-selectable amplifier, a field programmable gate array FPGA, a charged erasable programmable read only memory E2PROM, an RS-232 standard interface, an ethernet interface, a button, and a power supply.
3. The FPGA-based FMCW millimeter wave automotive anti-collision radar signal processing board of claim 2, wherein the low pass filter LPF is connected to the field programmable gate array FPGA through a direct digital frequency synthesizer DDS.
4. The FMCW millimeter wave automobile anti-collision radar signal processing board based on FPGA of claim 3, wherein the two programmable gain amplifiers PGA are connected to the field programmable gate array FPGA through analog-to-digital converters ADC, respectively.
5. The FPGA-based FMCW millimeter wave automotive anti-collision radar signal processing board of claim 4 wherein the two-way bean selectable amplifier are each connected to the field programmable gate array FPGA through an analog to digital converter ADC.
6. The FPGA-based FMCW millimeter wave automobile anti-collision radar signal processing board of claim 5, wherein the charged erasable programmable read-only memory E2PROM, the RS-232 standard interface, the Ethernet interface and the button are all connected with a field programmable gate array FPGA.
7. The FPGA-based FMCW millimeter wave automotive anti-collision radar signal processing board of claim 6, wherein the algorithm module is built into a programmable gain amplifier PGA.
8. The FPGA-based FMCW millimeter wave automobile anti-collision radar signal processing board of claim 7, wherein the algorithm module performs the same processing on the rising period and the falling period of the FMCW triangle wave respectively, and then performs the pairing processing on the results of the two processing to obtain the target parameters (A, R, V); the method comprises the following specific steps:
(1) The ZIF signals are sampled and quantized by an analog-to-digital converter ADC to obtain digital signals, and the digital signals are sent to a field programmable gate array FPGA for further processing;
the method comprises the following steps: using complex signal expression, for a suspected target, the signal is expressed as:
Ae j[2πfb+p]
wherein A represents the amplitude of the target reflected signal, specifically A (f); p is the phase, specifically P (f); fb is the frequency of the reflected signal;
(2) After the fast Fourier transform processing, extracting the amplitude and phase information of the suspected target, and carrying out two-dimensional fast Fourier transform analysis on the fast Fourier transform output slow-change signal, and carrying out moving target detection in the Doppler domain to obtain the speed information of the suspected target;
(3) Pairing the two identical processing results of the frequency-modulated triangular wave, and comparing the suspected target information with standard thresholds (Aref, vref, vdr) to obtain target (A, R, V) parameters;
(4) Carrying out correlation processing on the multi-frame parameters in a decision domain to obtain a final decision result;
(5) And finally framing according to a certain mode to form radar data, and transmitting the radar data to an upper computer for display.
9. The FPGA-based FMCW millimeter wave automotive anti-collision radar signal processing board of claim 8, employing a modified GO-CFAR detector to suppress interference, comprising the steps of:
(1) At the input number of pairsAccording to q k In the process of summing data in the front M/2 unit and the rear M/2 unit, selecting the largest one for rejection;
(2) Then selecting the largest Q of the summation results V1 and U1, multiplying the largest Q by the attenuation factor T to obtain TQ, and adding the TQ and the input data Q k The center data of the data are compared to obtain a judgment result;
wherein q k Representing amplitude data a (f) after the FFT processing, and TQ corresponding thereto represents an amplitude threshold (Aref).
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