Rotary platform radar target detection method and system based on multi-channel coherent accumulation

Abstract

The embodiment of the invention provides a rotating platform radar target detection method and system based on multi-channel coherent accumulation, and belongs to the technical field of target detection. The method comprises the following steps: performing target modeling on a rotating platform radar working scene to obtain target modeling data; analyzing the radar echo signal according to the target modeling data to obtain a rotation disturbance matrix; analyzing the Doppler dimension offset to obtain offset analysis data; obtaining improved data of coherent accumulation according to the rotation disturbance matrix and the offset analysis data; and rotating platform radar target detection is completed according to the improved data of phase-coherent accumulation. According to the invention, the target detection performance can be optimized in a specific scene, and the improvement of the target detection performance is verified through a simulation experiment.

Description

Technical Field

[0001] The present application relates to the technical field of target detection, and in particular to a rotating platform radar target detection method and system based on multi-channel coherent accumulation. Background Art

[0002] In the application of automotive radar, vehicle turning is a very critical scenario. There are few studies on target detection in vehicle turning scenarios. Traditional coherent accumulation can solve the problem of fixed platform radar target detection very well, but it does not take into account the situation of platform rotation, so it cannot solve the Doppler broadening and diffusion problems caused by platform rotation. Doppler broadening and diffusion will have an adverse effect on the target energy focusing of the rotating platform radar system. Low-frequency modulated continuous wave radar used for vehicles must cope with the challenges of target detection in various scenarios. Summary of the invention

[0003] The main purpose of the embodiments of the present application is to provide a rotating platform radar target detection method and system based on multi-channel coherent integration.

[0004] The technical solution adopted by the present invention is:

[0005] On the one hand, an embodiment of the present invention provides a rotating platform radar target detection method based on multi-channel coherent accumulation, the method comprising the following steps:

[0006] Perform target modeling on the rotating platform radar working scene to obtain target modeling data;

[0007] Analyzing the radar echo signal according to the target modeling data to obtain a rotation disturbance matrix;

[0008] Analyze the Doppler dimension shift to obtain shift analysis data;

[0009] Acquire coherently accumulated improved data according to the rotation disturbance matrix and the offset analysis data;

[0010] According to the coherently accumulated improved data, the rotating platform radar target detection is completed.

[0011] Furthermore, the target modeling of the rotating platform radar working scene to obtain the target modeling data includes the following steps:

[0012] According to the target speed, obtain the speed in the rotating scene;

[0013] Get the phase that needs to be compensated;

[0014] Get the distance change caused by the corner;

[0015] Acquiring the time delay caused by the target's distance relative to the radar;

[0016] According to the carrier frequency, the transmission signal is obtained;

[0017] Acquire a received signal according to the time delay;

[0018] Obtaining intermediate frequency signal;

[0019] The speed in the rotation scene, the compensated phase, the distance change, the time delay, the transmitted signal, the received signal, and the intermediate frequency signal are used as target modeling data.

[0020] Furthermore, the formula used to obtain the phase that needs to be compensated includes:

[0021]

[0022] Where ΔΦ is the phase to be compensated; N is the number of channels; d c is the channel spacing; ω is the platform speed where the channel is located; λ is the signal wavelength; t is the global time variable; Δθ is the angle between the target angle and the main beam direction of the antenna; T c is the Chirp cycle.

[0023] Furthermore, the formula used to obtain the intermediate frequency signal includes:

[0024]

[0025] Among them, S IF (t f ,t s ) is the intermediate frequency signal; j is the imaginary unit; S is the frequency modulation slope; R0 is the original distance without angular motion; c is the speed of light; f c is the carrier frequency; v is the channel speed; v0 is the target speed; t f Fast time; t s For slow time.

[0026] Furthermore, the step of analyzing the radar echo signal according to the target modeling data to obtain the rotation disturbance matrix includes the following steps:

[0027] Analyzing the radar echo signal according to the target modeling data to obtain speed difference data caused by the rotation;

[0028] A rotation disturbance matrix is ​​obtained according to the speed difference data.

[0029] Further, the analysis of the Doppler dimension shift to obtain shift analysis data includes the following steps:

[0030] Construct a three-dimensional data block containing distance, speed and rotation speed;

[0031] Setting radar parameters; the radar parameters include carrier frequency, bandwidth, chirp time, number of chirps, maximum sampling frequency of intermediate frequency signal, turning speed, turning radius, rotation angular velocity, channel spacing, and vehicle width;

[0032] According to the three-dimensional data block and the radar parameters, a simulation experiment analysis is performed on the Doppler dimension shift to obtain shift analysis data.

[0033] Further, the obtaining of coherently accumulated improved data according to the rotation disturbance matrix and the offset analysis data comprises the following steps:

[0034] The rotation disturbance matrix is ​​compensated in the Doppler dimension according to the offset analysis data to obtain coherently accumulated improved data.

[0035] On the other hand, an embodiment of the present invention further provides a rotating platform radar target detection system based on multi-channel coherent accumulation, the system comprising:

[0036] The first module is used to perform target modeling on the rotating platform radar working scene and obtain target modeling data;

[0037] The second module is used to analyze the radar echo signal according to the target modeling data to obtain a rotation disturbance matrix;

[0038] The third module is used to analyze the Doppler dimension shift and obtain the shift analysis data;

[0039] A fourth module is used to obtain coherently accumulated improved data according to the rotation disturbance matrix and the offset analysis data;

[0040] The fifth module is used to complete the rotating platform radar target detection according to the improved data accumulated by the coherent.

[0041] On the other hand, an embodiment of the present invention also provides a rotating platform radar target detection device based on multi-channel coherent integration, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the rotating platform radar target detection method based on multi-channel coherent integration as described above is implemented.

[0042] On the other hand, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the rotating platform radar target detection method based on multi-channel coherent accumulation as described above.

[0043] The embodiments of the present application include at least the following beneficial effects: The present application provides a rotating platform radar target detection method and system based on multi-channel coherent accumulation. The present invention performs target modeling on the rotating platform radar working scene to obtain target modeling data; analyzes the radar echo signal based on the target modeling data to obtain the rotation disturbance matrix; analyzes the Doppler dimension offset to obtain the offset analysis data; obtains the improved data of coherent accumulation based on the rotation disturbance matrix and the offset analysis data; completes the rotating platform radar target detection based on the improved data of coherent accumulation. The present invention can optimize the target detection performance in a specific scenario, and verify the improvement of the target detection performance through simulation experiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flow chart of a rotating platform radar target detection method based on multi-channel coherent accumulation provided by an embodiment of the present invention;

[0045] Figure 2 is a schematic diagram of a vehicle-mounted rotating platform radar target detection method by improving coherent accumulation provided by an embodiment of the present invention;

[0046] Figure 3 is a schematic diagram of geometric modeling of a vehicle-mounted rotating radar platform provided by an embodiment of the present invention;

[0047] FIG4( a ) is a schematic diagram of a three-dimensional speed-range-rotation speed data block provided by an embodiment of the present invention;

[0048] FIG4( b ) is a schematic diagram of a rotation speed-speed portion in a three-dimensional speed-range-rotation speed data block provided by an embodiment of the present invention;

[0049] Figure 5 is a schematic diagram of angle search within the main beam range provided by an embodiment of the present invention;

[0050] Figure 6 is a schematic diagram of a speed search experiment when the speed is 0.7 rad / s provided by an embodiment of the present invention;

[0051] Figure 7 is a schematic diagram of a speed search experiment when the speed is 1.1 rad / s provided by an embodiment of the present invention;

[0052] Figure 8 is a schematic diagram of a speed search experiment when the speed is 1.71 rad / s provided by an embodiment of the present invention;

[0053] Fig. 9 It is a schematic diagram comparing the rotation speed compensation method based on multi-channel search provided by an embodiment of the present invention, the original method and the idealized multi-channel compensation method. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

[0055] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0056] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0058] The present invention takes into account that there are few studies on target detection in vehicle turning scenarios. In this scenario, the speed difference between channels caused by the vehicle's rotational angular velocity cannot be ignored in the multi-channel coherent accumulation of target detection. Therefore, the present invention proposes signal modeling and theoretical derivation for this actual scenario, optimizes the target detection performance in a specific scenario, and verifies the improvement of target detection performance through simulation experiments.

[0059] Before describing the embodiments of the present application in detail, some nouns and terms involved in the embodiments of the present application are first described. The nouns and terms involved in the embodiments of the present application are subject to the following explanations.

[0060] 1) MIMO, which stands for Multiple Input Multiple Output, is a communication technology.

[0061] 2) LFMCW, which stands for "Low Frequency Chirp Modulated Continuous Wave", is a radar signal processing method, usually used for ranging and speed measurement.

[0062] 3) Chirp Period refers to the time length of a frequency modulated continuous wave (Chirp) signal from the lowest frequency to the highest frequency or vice versa. A Chirp signal is a signal whose frequency changes over time.

[0063] 4) Chirp time refers to the total time it takes for a chirp signal to complete a frequency scan.

[0064] 5) Chirp Count refers to the number of Chirp signals sent in a radar system within a certain period of time.

[0065] 6) SIMO, which stands for Single Input Multiple Output, is a system configuration.

[0066] 7) FFT Speed. FFT stands for Fast Fourier Transform, which is a mathematical algorithm. FFT speed refers to the processing speed of FFT calculation.

[0067] 8) IFFT (Inverse Fast Fourier Transform), which stands for "Inverse Fast Fourier Transform", is the inverse operation of FFT, converting the frequency domain signal back to the time domain signal.

[0068] 9) FOV, which stands for "Field of View", is usually used to describe the area of ​​space that a radar, camera or other sensor can cover.

[0069] 10) CFAR, which stands for Constant False Alarm Rate, is a technique used in radar signal processing.

[0070] 11) SNR, which stands for "Signal-to-Noise Ratio", is the ratio of signal strength to background noise strength.

[0071] The embodiments of the present invention are further described below in conjunction with the accompanying drawings.

[0072] On the one hand, an embodiment of the present invention provides a rotating platform radar target detection method based on multi-channel coherent accumulation, referring to Figure 1 , the method comprises the following steps:

[0073] S100, performing target modeling on the rotating platform radar working scene to obtain target modeling data;

[0074] S200, analyzing the radar echo signal according to the target modeling data to obtain a rotation disturbance matrix;

[0075] S300, analyzing the Doppler dimension shift to obtain shift analysis data;

[0076] S400, obtaining coherently accumulated improved data according to the rotation disturbance matrix and the offset analysis data;

[0077] S500, completing rotating platform radar target detection according to the coherently accumulated improved data.

[0078] The embodiment of the present invention discloses step S100 of performing target modeling on the rotating platform radar working scene to obtain target modeling data, including the following steps:

[0079] S110, obtaining the speed in the rotating scene according to the target speed;

[0080] S120, obtaining a phase that needs to be compensated;

[0081] S130, obtaining a distance change caused by a turning angle;

[0082] S140, obtaining the time delay caused by the distance of the target relative to the radar;

[0083] S150, acquiring a transmission signal according to a carrier frequency;

[0084] S160, obtaining a received signal according to the time delay;

[0085] S170, obtaining an intermediate frequency signal;

[0086] S180, using the speed, compensated phase, distance change, delay, transmitted signal, received signal, and intermediate frequency signal in the rotating scene as target modeling data.

[0087] The embodiment of the present invention discloses that step S120 obtains the phase to be compensated, and the formula used includes:

[0088]

[0089] Where ΔΦ is the phase to be compensated; N is the number of channels; d cis the channel spacing; ω is the platform speed where the channel is located; λ is the signal wavelength; t is the global time variable; Δθ is the angle between the target angle and the main beam direction of the antenna; T c is the Chirp cycle.

[0090] The embodiment of the present invention discloses step S170 to obtain an intermediate frequency signal, and the formula used includes:

[0091]

[0092] Among them, S IF (t f ,t s ) is the intermediate frequency signal; j is the imaginary unit; S is the frequency modulation slope; R0 is the original distance without angular motion; c is the speed of light; f c is the carrier frequency; v is the channel speed; v0 is the target speed; t f Fast time; t s For slow time.

[0093] The embodiment of the present invention discloses that step S200 analyzes the radar echo signal according to the target modeling data to obtain the rotation disturbance matrix, including the following steps:

[0094] S210, analyzing the radar echo signal according to the target modeling data to obtain speed difference data caused by the rotation;

[0095] S220. Obtain a rotation disturbance matrix according to the speed difference data.

[0096] The embodiment of the present invention discloses that step S300 analyzes the Doppler dimension shift to obtain shift analysis data, including the following steps:

[0097] S310, constructing a three-dimensional data block including distance, speed and rotation speed;

[0098] S320, setting radar parameters; radar parameters include carrier frequency, bandwidth, chirp time, number of chirps, maximum sampling frequency of intermediate frequency signal, turning speed, turning radius, rotation angular velocity, channel spacing, and vehicle width;

[0099] S330, performing simulation experimental analysis on Doppler dimension shift according to the three-dimensional data block and radar parameters to obtain shift analysis data.

[0100] The embodiment of the present invention discloses that step S400 obtains coherently accumulated improved data according to the rotation disturbance matrix and the offset analysis data, including the following steps:

[0101] S410. Compensate the rotation disturbance matrix in the Doppler dimension according to the offset analysis data to obtain coherently accumulated improved data.

[0102] As an optional implementation, the embodiments of the present invention include:

[0103] 1. Vehicle-mounted radar rotating platform scene target modeling:

[0104] 1. Generate a virtual array receive antenna from a single-channel MIMO module.

[0105] 2. Analyze the impact of channel spacing, antenna rotation speed and target angle on velocity measurement.

[0106] 3. Considering the dynamic environment of the vehicle-mounted radar, coherent accumulation is performed by compensating for the speed difference at the receiving end to achieve energy accumulation.

[0107] 2. Analyze the radar echo signal and extract the rotation disturbance matrix:

[0108] 1. Evaluate the velocity difference between channels and relate it to the angle at different target directions.

[0109] 2. Before Fourier transform, reduce signal distortion caused by rotation by compensating for phase deviation.

[0110] 3. Define channel speed for different speeds and target numbers to analyze and compensate the signal.

[0111] 3. Define multi-channel three-dimensional data blocks and conduct simulation experiment analysis:

[0112] 1. Set various parameters of the vehicle-mounted radar and simulate turning scenarios.

[0113] 2. Build a 3D data block of speed-distance-rotation speed to visualize the effect of rotation speed on target detection.

[0114] 3. Demonstrate how to achieve optimal speed focusing capability through data block analysis to support target detection at different rotation speeds.

[0115] 4. Compensation of the rotation disturbance matrix in the Doppler dimension:

[0116] 1. Perform an angular search within the main beam range to achieve the maximum signal-to-noise ratio.

[0117] 2. Improve the ability to accurately identify the target direction through angle traversal search, and improve detection performance by comparing with traditional methods.

[0118] 5. Improve target detection performance in rotating radar platform scenarios:

[0119] 1. Perform quantitative analysis and signal-to-noise ratio calculation to verify the effectiveness of the speed search.

[0120] 2. Compare the differences in signal-to-noise ratio among the multi-channel search compensation method, the original method and the idealized compensation method.

[0121] 3. Experiments have shown that the proposed method is superior to traditional target detection methods, showing strong robustness and application potential.

[0122] On the other hand, an embodiment of the present invention further provides a rotating platform radar target detection system based on multi-channel coherent accumulation, the system comprising:

[0123] The first module is used to perform target modeling on the rotating platform radar working scene and obtain target modeling data;

[0124] The second module is used to analyze the radar echo signal according to the target modeling data to obtain the rotation disturbance matrix;

[0125] The third module is used to analyze the Doppler dimension shift and obtain the shift analysis data;

[0126] The fourth module is used to obtain coherently accumulated improved data according to the rotation perturbation matrix and the offset analysis data;

[0127] The fifth module is used to complete the rotating platform radar target detection based on the improved data accumulated by coherent.

[0128] As an optional implementation, the present invention first models the rotating platform radar working scenario, analyzes the radar echo signal characteristics, and by comparing them with the signal characteristics of a conventional fixed platform radar, it is concluded that under the rotating condition, there will be an additional Doppler dimension disturbance matrix (rotation disturbance matrix) directly related to the rotation speed. The Doppler dimension disturbance matrix corresponding to the rotation speed is added to the target detection process for coherent accumulation, thereby improving the traditional target detection so that it can offset the influence of the rotation of the radar platform and better achieve target energy focusing.

[0129] refer to Figure 2 , by improving the coherent accumulation vehicle-mounted rotating platform radar target detection method, including the following steps:

[0130] Step 1: Vehicle-mounted radar rotating platform scene target modeling.

[0131] Step 2: Analyze the radar echo signal and extract the rotation disturbance matrix by comparing it with the traditional coherent accumulation.

[0132] Step 3: Define the multi-channel three-dimensional data block for rotating platform radar target detection and perform simulation experimental analysis on Doppler dimension shift.

[0133] Step 4: Compensate the rotation disturbance matrix in the Doppler dimension to improve the traditional coherent accumulation.

[0134] Step 5: Improve the target detection performance in the rotating radar platform scenario, and compare simulation experiments to illustrate the effectiveness of the method of the present invention.

[0135] As an optional implementation, refer to Figure 3 , step 1 of the present invention, vehicle-mounted radar rotating platform scene target modeling:

[0136] According to the virtual array receiving antenna generated by the MIMO module in a single channel, there will be an offset point according to the number of antennas when measuring speed. In the Doppler dimension, the offset distance is related to the channel spacing, the rotation speed of the antenna platform, and the angle of the target. The micro-Doppler migration caused by the angular velocity is ignored like the ordinary velocity measurement in the LFMCW system, but the speed difference between channels due to the angular velocity cannot be ignored. Energy accumulation can be achieved by compensating the speed difference on each channel at the receiving end of the corresponding channel and then performing coherent accumulation of all channels.

[0137] Channel spacing and angular velocity are factors affecting the speed difference, and the number of channels increases the speed offset accordingly. In high-speed scenarios, it will cause speed diffusion, while in vehicle turning scenarios, the angular velocity is constant within the frame time T. frame The change in time is not large, only the linear velocity ωd of the additional channel width rx N i The angle influence factor cos(ωt+θ) causes an offset in the velocity measurement.

[0138] The speed difference between channels takes into account the angle of the target and maps the speed of the target in the radial direction. The direction of the target is θ, and the speed in the rotation scene is defined as:

[0139] v rot =v0-(N-1)d c ωcos(ωt+Δλ)

[0140] Where v0 is the target real speed, N is the number of channels, d c is the channel spacing, ω is the platform speed where the channel is located, λ is the signal wavelength, and its relationship with the speed of light c and the signal frequency f is c=λf, Δλ is the angle between the target real angle and the direction of the main beam emitted by the antenna, and its range is

[0141] The second speed difference will bring about a two-way change in phase, so the phase that needs to be compensated is:

[0142]

[0143] R0 is the original distance without turning motion. The exact expression of the distance change caused by the turning in distance estimation is:

[0144]

[0145] Define a global time variable t=t f +t s It consists of slow time and fast time, where t f is the fast time, the slow time t s =iT c , B is the bandwidth of a chirp of the linear frequency modulation signal, T c is the Chirp cycle, is the frequency modulation slope, f c is the carrier frequency, A T is the signal transmission amplitude factor, j is an imaginary unit. The signal S is transmitted in the i-th frequency sweep cycle T (t f ,t s ) is expressed as:

[0146]

[0147] A R is the signal receiving amplitude factor, and the corresponding received signal is expressed as:

[0148]

[0149] Among them, the time delay caused by the target relative to the radar distance is:

[0150]

[0151] Pulse compression is achieved by de-skewing, that is, the received signal and the transmitted signal are input into the mixer, and the doubled frequency signal is filtered out by the filter to retain the intermediate frequency signal:

[0152]

[0153] in represents the conjugate of the amplitude factor, and substituting the relationship between delay, distance, and fast and slow time into the equation:

[0154]

[0155] The first exponential term is a constant phase term, the second exponential term is a frequency component related to the fast time dimension, the third exponential term is a frequency component related to the slow time dimension, and the fourth exponential term includes the coupling frequency term between the fast time dimension and the slow time dimension. Ignore the amplitude term, the constant phase term, and the denominator c 2 The higher-order terms of can be simplified to:

[0156]

[0157] The fast time dimension phase of the intermediate frequency signal is f Take the derivative to get the corresponding frequency Denote the frequency deviation caused by the target distance and the frequency deviation caused by the relative velocity Distance and speed affect frequency in the fast time dimension at the same time, resulting in distance-speed coupling. In practical application scenarios, f v <<f R , so it is considered that the fast time frequency f F ≈f R .

[0158] Substituting the speed and distance expressions in the rotation model, the intermediate frequency signal can be approximately expressed as:

[0159]

[0160] Step 2: Analyze the radar echo signal and extract the rotation disturbance matrix by comparing it with the traditional coherent accumulation:

[0161] The speed difference between channels is expressed as:

[0162] v rot =[0,-d c ωcos(ωt+θ),…,-(N-1)d c ωcos(ωt+θ)] T

[0163] Where d is the channel spacing, N is equivalent to R in SIMO system x (Receiver) Number of channels, speed of each channel is:

[0164] v=v0+v rot

[0165] Since different targets have different angles, a dimension is added to represent the number of targets. d is the channel spacing, and the speed difference caused by rotation is:

[0166]

[0167] N is the number of channels and M is the number of targets.

[0168] Speed ​​difference will cause phase deviation. The compensation on one channel is not only related to the rotation speed, but also to the target angle:

[0169]

[0170] Perform phase offset compensation in the corresponding channel, X n Represents the received signal of the nth channel. According to the frequency shift characteristic of Fourier transform, the phase offset is offset and the exponential term is compensated before Fourier transform:

[0171]

[0172] On the other hand, according to the principle of FFT velocity measurement, the multi-channel velocity offset value can be used to translate the coordinates on the image after IFFT. According to the derivation in the previous article, the phase change is ΔΦ, n is the velocity dimension coordinate, and the coordinate transformation of the i-th channel in the slow time dimension is:

[0173]

[0174] The speed resolution N c is the number of chirps in a frame. From this aspect, it can be seen that the requirement that the minimum channel offset can also be significantly reflected is to satisfy the expression:

[0175]

[0176] Step 3: Define the multi-channel three-dimensional data block for rotating platform radar target detection and perform simulation experimental analysis on Doppler dimension shift.

[0177] Table 1

[0178]

[0179]

[0180] Typical parameters of vehicle-mounted radar are shown in the table above, and common vehicle turning scenarios are set.

[0181] Since the cosine function decreases with the change of θ near the value of 0, in order to highlight the phase difference caused by the additional target angle, the array is rotated by the initial angle θ0 = 30°, where the main beam points to θ Δ The maximum value can be considered as the maximum FOV of the vehicle-mounted forward-looking radar, that is, ±60° (the angle with the center of the main beam). In physical terms, it is equivalent to an array located on a plane at a certain moment during the turn, rather than at the beginning of the turn. The performance gap can be more clearly reflected. This gap is positively correlated with the main beam width and the initial rotation angle θ0. Therefore, the array main beam pointing angle is set to 30°, and an angle search is performed within the main beam range. Here, the main beam 3dB range is determined by the main beam pointing:

[0182]

[0183] The target offset angle Δθ relative to the main beam is set to 5°, and this angle is searched for within the main beam range.

[0184] Construct a speed-distance-rotation speed three-dimensional data block to reflect the compensation effect of the rotation speed on the original two-dimensional parameter detection in a spatial coordinate system. The rotation speed dimension is the result obtained by traversal search, and the slice on the rotation speed dimension is the result plane obtained after speed-distance CFAR detection.

[0185] Referring to Figures 4(a) and 4(b), the stacking of speed-distance CFAR detection slices under the speed search condition is shown in the form of a point cloud in the spatial coordinate system. In the distance dimension, due to insufficient distance resolution, the CFAR processing may overlap some adjacent range gates, but in practical applications, this is within an acceptable error range. The multi-channel velocity offset caused by platform rotation is clearly visible in the figure and cannot be ignored. According to the method proposed in this paper, the speed search range is from 0 to twice the set speed. In theory, the slice corresponding to the median speed in this search range can accurately compensate for the speed effect caused by rotation. The actual experimental results in the figure show that by analyzing this three-dimensional data block, the best speed focusing capability can be achieved within the set speed slice, which is consistent with the theoretical analysis.

[0186] Observing the view from the positive direction of the distance dimension more clearly demonstrates the ability of speed focusing under speed search. Since the search range extends from 0 to twice the set speed, the speed detection image shows a central symmetric characteristic around the set speed. In addition, CFAR detection along the speed dimension may encounter coverage issues of multiple adjacent speed detection units, but in practical applications this is within an acceptable error range and is mainly used to compensate for speed offsets between channels.

[0187] Step 4: Compensate the rotation disturbance matrix in the Doppler dimension to improve the traditional coherent accumulation:

[0188] refer to Figure 5 , perform angle search within the main beam range, with the main beam center as the starting point of the angle search 0°. The point that makes the detection performance reach the highest signal-to-noise ratio in this search is a more accurate judgment of the target's approach angle within the main beam range, and can also be one of the judgment bases in angle estimation.

[0189] Moreover, since it is a traversal search for angles, it has higher applicability than traditional angle estimation methods. When the performance of traditional angle estimation is poor, it is possible to consider traversing and searching the target's approach angle within the main beam range. On the other hand, the traditional angle estimation method can also be used as a priori knowledge for angle search within the main beam range to improve the performance of the target detection method proposed by the present invention, and can also verify and improve the accuracy of previous angle estimation values.

[0190] Next, we conduct a quantitative analysis of the rotation speed search and perform a signal-to-noise ratio calculation on the detection results of each slice corresponding to the rotation speed search. It can be seen that when the set rotation speed is searched, the detection image reaches the highest signal-to-noise ratio and the detection performance reaches the optimal level, that is, the offset speed of multiple channels has been compensated and accumulated.

[0191] In order to demonstrate the robustness of the proposed method in different scenarios, we performed generalization verification by changing some parameters in the parameter table. Unless otherwise specified, other parameters are simulated based on the parameters in the previous table. Figure 6 , Figure 7 and Figure 8 The simulation experiment was carried out at three different speeds (0.7, 1.11, 1.7) rad / s, and the proposed method was used to search the speed. It was observed that the peak points corresponding to the speed were all within the error range of the set speed. The signal-to-noise ratio (SNR) was improved by about 10log 10 N pulse , where N pulse = 32, the theoretical SNR gain achieved is 15.05 dB. The simulation results are very close to the theoretical values. In addition, by changing parameters such as target distance, speed, or channel spacing, the images obtained by the speed search remain similar. This shows that the proposed method can improve the SNR in different scenarios, thus demonstrating its robustness in various scenarios.

[0192] By comparing the multi-channel search speed compensation method with the original method and the idealized multi-channel compensation method, it can be seen that in terms of the evaluation index of the signal-to-noise ratio, the detection performance of the original method can be greatly improved due to the existence of the search method. The reason for breaking through the idealized multi-channel speed limit is that the reference system of the measurement index of the detection image is different. In general, the multi-channel search speed compensation method can compensate for the speed difference between channels when the speed is unknown, thereby achieving the goal of improving the detection performance.

[0193] Step 5: Improve the target detection performance in the rotating radar platform scenario, and compare simulation experiments to illustrate the effectiveness of the method of the present invention:

[0194] refer to Fig. 9, the proposed method, the traditional method and the idealized multi-channel compensation method based on multi-channel search were compared, and the results showed that the search-based method significantly improved the detection performance, which was reflected in the improvement of the signal-to-noise ratio (SNR) indicator. It can be observed that compared with the traditional target detection method, when compensating the rotation speed of the multi-channel platform, the detection performance reached an ideal state, and the signal-to-noise ratio gain could reach a maximum of . In the proposed method, the present invention uses speed search to improve the target detection performance, so the SNR change of the target detection is roughly between the traditional target detection performance and the ideal speed compensation. In addition, the SNR at the actual speed position can be close to the theoretical gain limit. In general, the speed compensation method based on multi-channel search achieves an improvement in detection performance by compensating for the speed difference between channels under unknown speed conditions.

[0195] The key points of the present invention are:

[0196] 1. Vehicle-mounted radar rotating platform scene target modeling.

[0197] 2. Analyze the radar echo signal and extract the rotation disturbance matrix by comparing it with the traditional coherent accumulation.

[0198] 3. Define the multi-channel three-dimensional data block for rotating platform radar target detection and conduct simulation experimental analysis on Doppler dimension offset.

[0199] 4. Compensate the rotation disturbance matrix in the Doppler dimension to improve the traditional coherent accumulation.

[0200] 5. Improve the target detection performance in the rotating radar platform scenario, and compare simulation experiments to illustrate the effectiveness of the method of the present invention.

[0201] On the other hand, an embodiment of the present invention also provides a rotating platform radar target detection device based on multi-channel coherent accumulation, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the rotating platform radar target detection method based on multi-channel coherent accumulation as described above.

[0202] The processor and the memory can be connected via a bus or other means. The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0203] On the other hand, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the rotating platform radar target detection method based on multi-channel coherent accumulation as mentioned above.

[0204] It will be appreciated by those skilled in the art that all or some of the steps and systems in the disclosed method above may be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that may be used to store desired information and may be accessed by a computer. In addition, it is well known to those skilled in the art that communication media generally contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and may include any information delivery media.

[0205] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A rotating platform radar target detection method based on multi-channel coherent integration, characterized in that: The method comprises the following steps: Perform target modeling on the rotating platform radar working scene to obtain target modeling data; Analyzing the radar echo signal according to the target modeling data to obtain a rotation disturbance matrix; Analyze the Doppler dimension shift to obtain shift analysis data; Acquire coherently accumulated improved data according to the rotation disturbance matrix and the offset analysis data; According to the coherently accumulated improved data, the rotating platform radar target detection is completed.

2. The method according to claim 1, characterized in that The target modeling of the rotating platform radar working scene to obtain target modeling data includes the following steps: According to the target speed, obtain the speed in the rotating scene; Get the phase that needs to be compensated; Get the distance change caused by the corner; Acquiring the time delay caused by the target's distance relative to the radar; According to the carrier frequency, the transmission signal is obtained; Acquire a received signal according to the time delay; Obtaining intermediate frequency signal; The speed in the rotation scene, the compensated phase, the distance change, the time delay, the transmitted signal, the received signal, and the intermediate frequency signal are used as target modeling data.

3. The method according to claim 2, characterized in that The formula used to obtain the phase that needs to be compensated includes: Where ΔΦ is the phase to be compensated; N is the number of channels; d c is the channel spacing; ω is the platform speed where the channel is located; λ is the signal wavelength; t is the global time variable; Δλ is the angle between the target angle and the main beam direction of the antenna; T c is the Chirp cycle.

4. The method according to claim 2, characterized in that: The formula used to obtain the intermediate frequency signal includes: Among them, S IF (t f ,t s ) is the intermediate frequency signal; j is the imaginary unit; s is the frequency modulation slope; R0 is the original distance without angular motion; c is the speed of light; f c is the carrier frequency; v is the channel speed; v0 is the target speed; t f Fast time; t s For slow time.

5. The method according to claim 1, characterized in that The step of analyzing the radar echo signal according to the target modeling data to obtain the rotation disturbance matrix comprises the following steps: Analyzing the radar echo signal according to the target modeling data to obtain speed difference data caused by the rotation; A rotation disturbance matrix is ​​obtained according to the speed difference data.

6. The method according to claim 1, characterized in that The step of analyzing the Doppler dimension shift to obtain shift analysis data comprises the following steps: Construct a three-dimensional data block containing distance, speed and rotation speed; Setting radar parameters; the radar parameters include carrier frequency, bandwidth, chirp time, number of chirps, maximum sampling frequency of intermediate frequency signal, turning speed, turning radius, rotation angular velocity, channel spacing, and vehicle width; According to the three-dimensional data block and the radar parameters, a simulation experiment analysis is performed on the Doppler dimension shift to obtain shift analysis data.

7. The method according to claim 1, characterized in that The step of obtaining the coherently accumulated improved data according to the rotation disturbance matrix and the offset analysis data comprises the following steps: The rotation disturbance matrix is ​​compensated in the Doppler dimension according to the offset analysis data to obtain coherently accumulated improved data.

8. A rotating platform radar target detection system based on multi-channel coherent integration, characterized in that: The system comprises: The first module is used to perform target modeling on the rotating platform radar working scene and obtain target modeling data; The second module is used to analyze the radar echo signal according to the target modeling data to obtain a rotation disturbance matrix; The third module is used to analyze the Doppler dimension shift and obtain the shift analysis data; A fourth module is used to obtain coherently accumulated improved data according to the rotation disturbance matrix and the offset analysis data; The fifth module is used to complete the rotating platform radar target detection according to the improved data accumulated by the coherent.

9. A rotating platform radar target detection device based on multi-channel coherent integration, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the rotating platform radar target detection method based on multi-channel coherent integration as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the rotating platform radar target detection method based on multi-channel coherent integration as described in any one of claims 1 to 7.

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