Radar weak target detection method based on improved CFAR

Abstract

The invention relates to a radar weak target detection method based on improved CFAR, and the method comprises the following steps: carrying out the two-dimensional FFT processing of radar echoes, and obtaining a distance-Doppler graph; respectively carrying out CFAR calculation in a Doppler dimension and a distance dimension of the RD diagram, and determining a target unit as a target when the target unit is detected in two dimensions and the power is higher than that of an adjacent unit by optimizing setting of a reference unit and a protection unit and adjusting an SNR threshold value; for a special Doppler index and a zero-Doppler-dimension edge distance unit, calculating a power difference value to further improve the detection capability of a weak target; according to the method, the weak target can be stably detected in a radar direct current area and a large-angle sidelobe area, the problems of complex front-end signal processing and parameter setting in the prior art are effectively solved, and the detection rate and precision of the weak target in a complex scene are remarkably improved.

Description

Technical Field

[0001] The invention relates to the field of radar technology, and in particular to a radar weak target detection method based on improved CFAR. Background Art

[0002] Constant false alarm rate (CFAR) detection technology is a common method in radar signal processing. It is used to detect targets in complex noise and clutter environments. CFAR technology dynamically adjusts the detection threshold to keep the false alarm rate constant, so that targets can be effectively detected in different environments. Millimeter wave radar is often used in scenarios such as autonomous driving, drones, and security monitoring due to its high resolution and anti-interference ability. In these applications, CFAR technology is used to extract target signals from complex background noise. Therefore, CFAR technology is widely used in millimeter wave radar, airborne radar and other fields. Although CFAR detection technology has been widely used in radar target detection, it still has shortcomings in weak target detection: Complex front-end signal processing: Existing weak target detection mainly focuses on the front-end RF signal processing part. The weak target detection performance is improved by enhancing the signal processing capability, such as increasing the signal-to-noise ratio (SNR) and increasing the signal processing bandwidth. However, these methods are complex and limited by hardware costs and computing resources. Limited weak target detection capability: CFAR detection relies on the prominent peak of the target signal, while the signal strength of weak targets is low and is easily submerged by noise or clutter, resulting in missed detection. Especially at the two ends of the radar ranging range (the closest and farthest points), the detection of weak targets is more difficult due to the influence of the DC component. Parameter settings have a significant impact on detection results: The effect of CFAR detection is highly dependent on the settings of parameters such as reference units and protection units. Different application scenarios require different parameter configurations, and improper parameter settings can lead to reduced detection performance, especially in weak target detection. Slight changes in parameter settings may lead to missed targets or increased false alarm rates. Difficulty in detecting large-angle sidelobe areas: When the target is in the sidelobe area of ​​the radar beam, the signal strength is weak, and the signal in the sidelobe area is usually masked by noise or clutter. Conventional CFAR technology is difficult to effectively detect the target signal, resulting in missed target detection. Summary of the invention

[0003] In view of this, the present invention provides a radar weak target detection method based on improved CFAR by improving the CFAR algorithm in the back-end signal processing, which can stably detect weak targets in the radar DC region and large-angle sidelobe region, and effectively solve the complex front-end signal processing and parameter setting problems in the prior art.

[0004] To achieve the above object, the present invention provides a radar weak target detection method based on improved CFAR, comprising the following steps: S1, perform two-dimensional fast Fourier transform (FFT) processing on the radar echo to obtain a range-Doppler map; S2, performing CFAR calculation on the Doppler dimension and the distance dimension of the range-Doppler image respectively; S201, starting from the Doppler dimension, taking each unit in the range-Doppler map as a target unit in turn by row, and calculating the power of the target unit; S202, a units adjacent to the target unit on the left and right are used as protection units, and b units adjacent to the protection unit on the left and right are used as reference units; S203, respectively calculating the power averages of the reference units on the left and right sides, wherein the smaller power average is used as the background power; S204, comparing the target unit power with the sum of the background power and the preset signal-to-noise ratio SNR. If the target unit power is greater than the sum of the background power and the preset signal-to-noise ratio, and greater than the power of the two adjacent units on the left and right, it is determined that there is a target in the target unit and detected; S205, repeat steps S201-S204, and perform CFAR calculation from the distance dimension; S206, if the target unit is detected in both the Doppler dimension and the range dimension and the power of the target unit is higher than that of the left and right adjacent units, it is determined that the target unit has a target, otherwise, it is determined that the target unit does not have a target; S3, performing step S2 for Doppler indexes 2, 3, N-1, and N using a lower preset signal-to-noise ratio, where N represents the number of radar chirps; S4, zero-Doppler processing; S5. Output the detected target unit.

[0005] Preferably, when the target cell with a Doppler index of 3 is compared in power with adjacent cells on the left and right sides, it is not compared with the cell with a Doppler index of 2, but only compared with the cell with a Doppler index of 4.

[0006] Preferably, when the target cell with Doppler index N-1 performs power comparison with adjacent cells on the left and right sides, it is not compared with the cell with Doppler index N, but only compared with the cell with Doppler index N-2.

[0007] Preferably, the zero-Doppler processing comprises the following steps: Calculate the power difference between the first and second range units in zero Doppler range, denoted as , calculate the power difference between the second and third distance units in zero Doppler range, recorded as , calculate the power difference between the zero-Doppler M-1th distance unit and the Mth distance unit, recorded as , calculate the power difference between the M-2th distance unit and the M-1th distance unit of zero Doppler spectrum, recorded as , where M represents the number of ADC sampling points; Will , , and Compare with the preset threshold value TD respectively. If only one power difference satisfies , then the distance unit that is subtracted from the power difference is detected; If there are two or more power differences satisfying , then the distance unit with higher power among the distance units will be detected, but the first distance unit and the last distance unit cannot be used as detection units.

[0008] Compared with the prior art, the present invention has the following beneficial effects: The present invention utilizes the characteristic that target energy will diffuse in adjacent distance units, improves the detection rate of weak targets at the closest and farthest points of the radar ranging range in a complex environment, and successfully detects weak targets in the sidelobe area of ​​the radar beam by optimizing the CFAR comparator logic, reducing the problem of missed detection of targets caused by noise or clutter; The present invention aims at special areas such as the two ends of the radar ranging range and the sidelobe area. The present invention adopts a targeted optimization processing method to reduce the SNR and adjust the power comparison rule, thereby avoiding misjudgment caused by DC influence, so that weak targets can be accurately detected in the sidelobe area. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] FIG1 is a range-Doppler diagram obtained by performing two-dimensional FFT processing on the radar echo signal in step S1 of the present invention; Figure 2 It is a schematic diagram of target detection by the CFAR algorithm of the present invention; Figure 3 This is a one-dimensional range image comparison diagram of a near weak target and an empty scene in the present invention. DETAILED DESCRIPTION

[0010] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0011] In order to ensure that weak targets are stably detected and not missed in the radar DC area and the large-angle sidelobe area, the present invention provides the following technical solution: a radar weak target detection method based on improved CFAR, in which the maximum measurement distance is 100 meters, the number of ADC sampling points is 256, the number of chirps is 64, the number of reference units is 8, the number of protection units is 4, the Doppler dimension signal-to-noise ratio SNR is 10dB, the distance dimension signal-to-noise ratio SNR is 10dB, and the unit power difference threshold value TD is 1500, comprising the following steps: S1, such as Figure 1 As shown, the radar echo is processed by two-dimensional fast Fourier transform FFT to obtain the range-Doppler diagram. Figure 1 Each square of the RD diagram shown represents a unit; S2. Perform CFAR calculations on the Doppler dimension and the distance dimension of the range-Doppler graph respectively: S201, starting from the Doppler dimension, taking each unit in a row of the range-Doppler map as a target unit in turn, and calculating the power of the target unit; S202, four cells adjacent to the target cell on the left and right are used as protection cells, and eight cells adjacent to the protection cell on the left and right are used as reference cells; S203, respectively calculating the power averages of the reference units on the left and right sides, wherein the smaller power average is used as the background power; S204, comparing the target unit power with the sum of the background power and the preset signal-to-noise ratio SNR. If the target unit power is greater than the sum of the background power and the preset signal-to-noise ratio, and greater than the power of the two adjacent units on the left and right, it is determined that there is a target in the target unit and detected; S205, repeat steps S201-S204, and perform CFAR calculation from the distance dimension; S206, if the target unit is detected in both the Doppler dimension and the range dimension and the power of the target unit is higher than the left and right adjacent units, it is determined that the target unit has a target, otherwise, it is determined that the target unit does not have a target; The cells at both ends are selected in a loop when selecting left and right cells. For example, if there is no cell to the left of the first cell, the four cells at the rightmost end, i.e., cell indexes 61-64, are used as protection cells during the calculation process, and cells with indexes 53-60 are used as reference cells. S3, after searching the targets in the RD image from the distance dimension and the Doppler dimension, the detected targets are supplemented to avoid missed detection; For Doppler indexes of 2, 3, N-1, and N, a lower preset signal-to-noise ratio is used to perform step S2 processing, and the preset signal-to-noise ratio SNR is reduced by 3 dB respectively, where N represents the number of radar chirps (in this embodiment, the maximum value of the Doppler index is 64, that is, the number of radar chirps is 64); When the unit in the third column is used as the target unit and the power is compared with the adjacent units on the left and right sides, it is not compared with the previous unit, that is, the unit with Doppler index 2, but only with the next unit, that is, the unit with Doppler index 4; When the unit in the 63rd column is used as the target unit and the power is compared with the adjacent units on the left and right sides, it is not compared with the unit with Doppler index 64, but only with the unit with Doppler index 62; S4, zero-Doppler processing, comprising the following steps: Calculate the power difference between the first three and last three range units in the first column of the RD diagram, that is, the power difference between the first and second range units in zero Doppler dimension, and record it as , calculate the power difference between the second and third distance units in zero Doppler range, recorded as , calculate the power difference between the 256th distance unit and the 255th distance unit in zero Doppler dimension, recorded as , calculate the power difference between the 255th range unit and the 254th range unit in zero Doppler dimension, recorded as ; Will , , and Compare with the preset threshold value TD respectively. If only one power difference satisfies , then detect the distance unit that is subtracted from the power difference, for example: , then detect the second distance unit; if , then the 255th distance unit is detected; If there are two or more power differences satisfying , then the distance unit with higher power among the distance units is detected, but the first distance unit and the last distance unit cannot be used as detection units, for example , If both conditions are met, the distance unit with higher power among the two units for difference is selected for detection; like Figure 3 As shown in the figure, a schematic diagram of the power of the first few range units of the zero Doppler one-dimensional range image when there is a weak target at a distance of 0.4 meters is given. It can be seen that when there is a target, the power of the second range unit is significantly higher than that of the empty scene. However, because the first range unit is affected by DC and has a higher power than the second range unit, the conventional CFAR algorithm cannot detect it, but it can be successfully detected through this step. S5. Output all target units detected in the above steps.

[0012] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A radar weak target detection method based on improved CFAR, characterized in that: The following steps are involved: S1, perform two-dimensional fast Fourier transform (FFT) processing on the radar echo to obtain a range-Doppler map; S2, performing CFAR calculation on the Doppler dimension and the distance dimension of the range-Doppler image respectively; S201, starting from the Doppler dimension, taking each unit in the range-Doppler map as a target unit in turn by row, and calculating the power of the target unit; S202, a units adjacent to the target unit on the left and right are used as protection units, and b units adjacent to the protection unit on the left and right are used as reference units; S203, respectively calculating the power averages of the reference units on the left and right sides, wherein the smaller power average is used as the background power; S204, comparing the target unit power with the sum of the background power and the preset signal-to-noise ratio SNR. If the target unit power is greater than the sum of the background power and the preset signal-to-noise ratio, and greater than the power of the two adjacent units on the left and right, it is determined that there is a target in the target unit and detected; S205, repeat steps S201-S204, and perform CFAR calculation from the distance dimension; S206, if the target unit is detected in both the Doppler dimension and the range dimension and the power of the target unit is higher than that of the left and right adjacent units, it is determined that the target unit has a target, otherwise, it is determined that the target unit does not have a target; S3, performing step S2 for Doppler indexes 2, 3, N-1, and N using a lower preset signal-to-noise ratio, where N represents the number of radar chirps; S4, zero-Doppler processing; S5. Output the detected target unit.

2. The radar weak target detection method based on improved CFAR according to claim 1 is characterized in that: When the target cell with the Doppler index of 3 performs power comparison with the adjacent cells on the left and right sides, it is not compared with the cell with the Doppler index of 2, but only compared with the cell with the Doppler index of 4.

3. The radar weak target detection method based on improved CFAR according to claim 2 is characterized in that: When the target cell with the Doppler index of N-1 performs power comparison with the adjacent cells on the left and right sides, it is not compared with the cell with the Doppler index of N, but only with the cell with the Doppler index of N-2.

4. The radar weak target detection method based on improved CFAR according to claim 1 is characterized in that: The zero-Doppler processing comprises the following steps: Calculate the power difference between the first and second range units in zero Doppler range, denoted as , calculate the power difference between the second and third range units in zero-Doppler spectrum, recorded as , calculate the power difference between the zero-Doppler M-1th distance unit and the Mth distance unit, recorded as , calculate the power difference between the M-2th distance unit and the M-1th distance unit of zero Doppler spectrum, recorded as , where M represents the number of ADC sampling points; Will , , and Compare with the preset threshold value TD respectively. If only one power difference satisfies , then the distance unit that is subtracted from the power difference is detected; If there are two or more power differences satisfying , then the distance unit with higher power among the distance units will be detected, but the first distance unit and the last distance unit cannot be used as detection units.

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