Removing method and system for radar fuze fixed floor noise, electronic equipment and storage medium

Abstract

The invention relates to a radar fuze fixed floor noise elimination method and system, electronic equipment and a storage medium, and the method comprises the steps: S1, enabling a radar to be powered on, reading analog signal data through an analog-to-digital converter, and converting the analog signal data into digital signal data; s2, performing module value calculation on the digital signal data processed in the step S1 by adopting an FFT (Fast Fourier Transform) algorithm, processing according to a module value result to obtain a reference signal containing a fixed interference signal, and subtracting the reference signal from a signal containing a target signal and the fixed interference signal to obtain a clean target signal so as to eliminate the fixed interference; and S3, performing CFAR processing on the clean target signal obtained in the step S2, and further eliminating noise interference to obtain an accurate target of the radar fuze. According to the method, the radar false alarm phenomenon caused by fixed interference of the environment, the system interior and the like of the radar is effectively reduced, the false alarm rate caused by fuze is further reduced, and the accuracy of fuze detonation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of radar fuze interference rejection, and more specifically, to a method, system, electronic device and storage medium for rejecting the fixed background noise of a radar fuze. Background Art

[0002] Due to the characteristics of the fuze working environment, when powered on, it is generally in the air. Theoretically, the interference in the air environment is small and should be close to the designed background noise level. However, due to the interference of some other factors (such as the fixed interference frequency of the system, the fixed interference frequency of the environment, etc.), there are often fixed interference frequencies in the echo signal. If the interference signal frequency is within the band, it may affect the subsequent detection, resulting in false alarm interference, and even causing a fuze accident such as premature detonation. Moreover, in the field of fuzes, the logic of rejecting fixed background noise is rarely seen. In the prior art, in the radar field, rejecting fixed background noise generally starts from the ADC data end or from the point cloud result end. The former has a large amount of calculation and is prone to distortion, while the latter can reject the interference at fixed positions but may cause data truncation.

[0003] Therefore, in the present invention, a method for rejecting the fixed background noise of a radar fuze is proposed to solve the problems such as the fuze accident of premature detonation caused by the radar false alarm phenomenon due to fixed interference in the prior art. Summary of the Invention

[0004] The present invention aims to overcome at least one defect (shortcoming) of the above prior art, and provides a method, system, electronic device and storage medium for rejecting the fixed background noise of a radar fuze, which is used to reduce the radar false alarm phenomenon caused by fixed interferences such as the environment and the system interior, thereby reducing the false alarm rate caused by the fuze and improving the accuracy of fuze detonation.

[0005] In a first aspect, the technical solution adopted by the present invention is a method for rejecting the fixed background noise of a radar fuze, and the method includes the following steps:

[0006] Step S1: After powering on the radar, read the analog signal data through an analog-to-digital converter and convert the analog signal data into digital signal data;

[0007] Step S2: Use the FFT algorithm to calculate the modulus value of the digital signal data processed in Step S1, and process according to the modulus value result to obtain a reference signal containing the fixed interference signal. Then subtract the reference signal from the signal containing the target signal and the fixed interference signal to obtain a clean target signal, thereby rejecting the fixed interference;

[0008] Step S3: Perform CFAR processing on the clean target signal obtained in Step S2 to further reject the noise interference and obtain the accurate target of the radar fuze.

[0009] In a radar system, fixed interference signals are usually generated due to the hardware noise of the system itself or constant interference sources in the external environment (such as power supply noise, background clutter, etc.). These interference signals will affect the accuracy of near - burst target detection of the radar fuse. Therefore, in this application, the FFT algorithm is used to calculate the modulus value, and then based on the modulus value result, a reference signal containing the fixed interference signal is obtained, so that the interference components in the actual target signal can be effectively distinguished. Then, the original signal containing the target signal and the fixed interference signal is used to subtract the reference signal to eliminate the fixed interference in the fuse system and obtain a clean target signal. Finally, the CFAR algorithm is used for processing to obtain an accurate radar fuse target. Thus, the method of eliminating interference from the signal - processing end after the FFT algorithm and before the CFAR algorithm has obvious advantages compared with the method of eliminating interference from the result end. It can retain the detection ability of the signal at the interference position, ensure the continuity of the detection data while reducing the false - alarm rate. At the same time, compared with the method of eliminating fixed interference from the ADC end, the calculation amount of this application is less and it is not easy to cause signal distortion. Therefore, it effectively reduces the radar false - alarm phenomenon caused by fixed interferences such as the environment and the system itself, further reduces the false - alarm rate caused by the fuse, and improves the accuracy of fuse detonation.

[0010] Preferably, in the step S2, it includes judging the frame number and calculating the reference signal and the clean target signal according to the judgment result;

[0011] If the frame number ≤ N, perform FFT modulus accumulation until the frame number equals N, and then calculate the mean value of the FFT modulus of the first N frames to obtain a reference signal containing the fixed interference signal;

[0012] If the frame number > N, skip the accumulation, calculate the FFT modulus of the (N + 1) - th frame to obtain a signal containing the target signal and the fixed interference signal, and then subtract the reference signal from this signal to recalculate the FFT modulus, so as to obtain a clean target signal.

[0013] In this application, a fixed background noise elimination for a more accurate and adaptive radar fuse system is achieved through a frame number judgment mechanism. During the stage where the frame number ≤ N, the FFT modulus values are accumulated and the average value of the first N frames is calculated to generate a reference signal, making full use of the scene characteristics of the radar fuse. For example, the first N frames physically isolate the target signal, ensuring that the reference signal only contains fixed interference. This statistical method based on multi-frame accumulation can more comprehensively and stably characterize the characteristics of the fixed background noise compared with single-frame or random sampling, providing a reliable reference for subsequent interference elimination. Then, when the frame number > N, the accumulation is skipped and the new frame signal is directly processed. By subtracting the reference signal to recalculate the FFT modulus value, the fixed background noise in each frame signal can be stripped in real time. This method adapts to the processing requirements of the N + 1 frame and subsequent signals, ensuring that the target signal always maintains a high purity during dynamic updates, avoiding the continuous impact of fixed interference on subsequent analysis, so that the fixed interference is eliminated more thoroughly, greatly reducing the interference to subsequent CFAR processing, reducing both the false alarm rate and increasing the detection probability of real targets, thus effectively improving the accuracy of fuse detonation.

[0014] Preferably, the method further includes determining the amount of the first N frame data required for background noise statistics based on the physical motion characteristics and operating frame period of the fuse radar, specifically including the following steps:

[0015] Step S21: When the airborne motion trajectory of the fuse is a parabolic trajectory, determine the position of the fuse at each time point, obtain the power-on time of the fuse and the over-the-top time from the power-on time to the peak position, and calculate the time window in the radar echo where there is only noise and fixed interference and no effective target echo based on the power-on time and the over-the-top time;

[0016] Step S22: Calculate the value of N based on the time window obtained in Step S21 and the operating frame period.

[0017] Therefore, in this application, by analyzing the physical motion characteristics of the fuse radar and the operating frame period, the accurate determination of the amount of the first N frames of data required for noise floor statistics is achieved. Using the parabolic motion trajectory of the fuse, the position information of the fuse from power-on to over-the-top can be determined. During this time window, the state of the fuse is to emit electromagnetic wave signals into the air, ensuring that the main lobe direction of the radiation pattern is towards the air, and the position of the fuse at the power-on moment of the radar fuse is also in the air. Furthermore, it can also ensure that ground targets cannot be detected by the side lobes. In this way, the detection of ground targets of interest can be avoided only at the physical level, achieving the isolation of target signals at the physical level and effectively avoiding the interference of target signals on noise floor statistics. At the same time, by leveraging the physical motion characteristics of the fuse in this way to determine the value of N in a relatively simple manner, not only the requirement for the hardware computing power is reduced, the consumption of computing resources is decreased, but also the system design and debugging process is simplified, the real-time performance of the system is improved, providing a strong guarantee for the rapid deployment and stable operation of the radar fuse in practical applications.

[0018] Preferably, in the step S22, the calculation formula of N is:

[0019]

[0020] where Time_summit represents the over-the-top time; Time_on represents the power-on time of the fuse; T_frame represents the operating frame period of the fuse radar.

[0021] In this application, the method of directly calculating the value of N through the operating frame period and the target-free echo time window can effectively improve the accuracy of noise floor rejection. And for different fuse radars, there may be differences in their operating frame periods. The method described in this application can be adaptively adjusted according to specific parameters to ensure that the data required for noise floor statistics can be accurately obtained in various fuse radar systems. This can not only enhance the reliability of the entire radar fuse system in complex environments, but also reduce the false alarm and missed detection probabilities caused by inaccurate noise floor statistics.

[0022] Preferably, the calculation formula of the FFT modulus value is:

[0023]

[0024] where FFT_M_i represents the modulus value of the FFT, a_i represents the real part of the FFT calculation result at the corresponding frequency point position; b_i represents the imaginary part of the FFT calculation result at the corresponding frequency point position.

[0025] The FFT magnitude value calculated by this formula provides a reliable data basis for this solution, enabling the accurate extraction of the characteristics of fixed interference signals. When subtracting the signal containing the target signal and the fixed interference signal from the reference signal, the operation based on the magnitude value can clearly highlight the characteristics of the target signal, thereby more effectively removing the fixed interference and improving the purity of the target signal.

[0026] Preferably, in the step S3, it includes: dynamically adjusting the threshold of target detection according to the intensity of the clean target signal. When the signal intensity exceeds the threshold, it is determined as a real target; otherwise, it is determined as noise or clutter, thereby further removing noise interference to obtain the accurate target of the radar fuse.

[0027] Thus, through the pre - processing of removing the background noise, a clean target signal is obtained. The threshold is dynamically adjusted through CFAR processing, and the intensity of the obtained clean target signal is compared with the threshold, so as to further distinguish the target from the interference, more accurately identify the real target, reduce the misjudgment probability caused by the fuse, and improve the detonation accuracy of the fuse.

[0028] In a second aspect, the present application also provides a system for removing the fixed background noise of a radar fuse according to the method for removing the fixed background noise of a radar fuse described above. The system includes:

[0029] A data acquisition unit, configured to read analog signal data through an analog - to - digital converter after powering on the radar, and convert the analog signal data into digital signal data;

[0030] An interference removal unit, configured to calculate the magnitude value of the digital signal data processed by the data acquisition unit by using the FFT algorithm, and process it according to the magnitude value result to obtain a reference signal containing fixed interference signals, and then subtract the reference signal from the signal containing the target signal and the fixed interference signal to obtain a clean target signal, thereby removing the fixed interference;

[0031] A target detection unit, configured to perform CFAR processing on the clean target signal obtained by the interference removal unit to further remove noise interference and obtain the accurate target of the radar fuse.

[0032] In this system, the data after the radar is powered on is acquired and processed by the data acquisition unit, and then the interference rejection unit is used to reject interference from the signal processing end after the FFT algorithm and before the CFAR algorithm. This method has obvious advantages compared with the method of rejecting interference from the result end, which can retain the detection ability of the signal at the interference position, reduce the false alarm rate while ensuring the continuity of the detection data. At the same time, compared with the method of rejecting fixed interference from the ADC end, the calculation amount of this system is less and it is not easy to cause signal distortion, thus effectively reducing the radar false alarm phenomenon caused by fixed interference such as the environment and the system itself, further reducing the false alarm rate caused by the fuse, and improving the accuracy of the fuse detonation.

[0033] Preferably, in the interference rejection unit, it includes:

[0034] A frame number calculation component, which is used to determine the amount of the first N frames of data required for background noise statistics according to the physical motion characteristics and the operating frame period of the fuse radar, so as to calculate the value of N. The calculation formula of N is:

[0035]

[0036] where Time_summit represents the over-the-top time; Time_on represents the power-on time of the fuse; T_frame represents the operating frame period of the fuse radar;

[0037] A frame number judgment component, which is used to calculate the reference signal and the clean target signal according to the frame number judgment result, including:

[0038] If it is judged that the frame number ≤ N, perform FFT modulus accumulation until the frame number is equal to N, and then calculate the average value of the FFT moduli of the first N frames to obtain a reference signal containing fixed interference signals;

[0039] If it is judged that the frame number > N, skip the accumulation, calculate the FFT modulus of the (N + 1)-th frame to obtain a signal containing the target signal and the fixed interference signal, and then subtract the reference signal from this signal to recalculate the FFT modulus, so as to obtain a clean target signal.

[0040] In this application, by using the frame number calculation component to analyze the physical motion characteristics of the fuze radar and the operating frame period, the amount of the first N frames of data required for accurate background noise statistics is determined. By using the parabolic motion trajectory of the fuze, the position information of the fuze from power-on to over-the-top is clarified. During this time window, the state of the fuze is to emit electromagnetic wave signals into the air, ensuring that the main lobe direction of the radiation pattern is towards the air, and the position of the fuze at the power-on moment of the radar fuze is also in the air. Furthermore, it can also ensure that ground targets cannot be detected by the side lobes. In this way, detecting ground targets of interest can be avoided only from the physical level, achieving target signal isolation at the physical level and effectively avoiding the interference of target signals on background noise statistics. At the same time, the frame number judgment component is also used to judge the frame number, and corresponding calculations are performed according to the frame number judgment result to obtain clean target signals, thereby realizing the fixed background noise rejection of a more accurate and adaptive radar fuze system.

[0041] In a third aspect, the present application also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the method for rejecting the fixed background noise of the radar fuze as described above is implemented.

[0042] The present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for rejecting the fixed background noise of the radar fuze as described above is implemented.

[0043] The present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the method for rejecting the fixed background noise of the radar fuze as described above is implemented.

[0044] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0045] The present invention patent relates to the technology for rejecting fixed background noise in a proximity fuze system, which can effectively reduce the influence of internal fixed-frequency interference or environmental fixed-frequency interference of the product on the radar fuze system. And the position of interference rejection is after the FFT algorithm and after the CFAR algorithm, which has obvious advantages compared with the method of rejecting interference from the result end, and can retain the detection ability of the signal at the interference position, while reducing the false alarm rate and ensuring the continuity of detection data. At the same time, compared with the method of rejecting fixed interference from the ADC end, the calculation amount of the present application is less and signal distortion is not easily caused, thereby effectively reducing the radar false alarm phenomenon caused by environmental and system internal fixed interferences, effectively improving the influence of fixed interference frequencies on effective signals, further reducing the false alarm rate caused by the fuze, and improving the detonation accuracy of the fuze. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1Schematic diagram of the method flow provided by this solution.

[0047] Figure 2 Schematic diagram of the method logic flow provided by this solution.

[0048] Figure 3 Schematic diagram of the air motion trajectory of the fuse provided by this solution.

[0049] Figure 4 Schematic diagram of the bottom noise statistics of the first N frames of signals provided by this solution.

[0050] Figure 5 Schematic diagram of the effect comparison before and after removing fixed interference provided by this solution.

[0051] Figure 6 Schematic diagram of the system structure provided by this solution.

[0052] Figure 7 Schematic diagram of the structure of the electronic device provided by this solution. Specific implementation manners

[0053] The attached drawings of the present invention are only for illustrative purposes and should not be construed as a limitation to the present invention. For better illustrating the following embodiments, some components in the drawings will be omitted, enlarged or reduced, which do not represent the dimensions of the actual products; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0054] Embodiment 1

[0055] As Figure 1 shown, this embodiment provides a method for removing the fixed bottom noise of a radar fuse. The method includes the following steps:

[0056] Step S1: After powering on the radar, read the analog signal data through an analog-to-digital converter and convert the analog signal data into digital signal data;

[0057] Step S2: Use the FFT algorithm to calculate the modulus value of the digital signal data processed in step S1, and process according to the modulus value result to obtain a reference signal containing the fixed interference signal. Then subtract the reference signal from the signal containing the target signal and the fixed interference signal to obtain a clean target signal, thereby removing the fixed interference;

[0058] Preferably, the method further includes determining the amount of data of the first N frames required for bottom noise statistics based on the physical motion characteristics and operating frame period of the fuse radar, ensuring that the signals statistically obtained in the first N frames do not contain effective target signals. Specifically, it includes the following steps:

[0059] Step S21: As Figure 3As shown in the figure, when the air motion trajectory of the fuse is a parabolic trajectory, determine the position of the fuse at each time point, obtain the power-on time of the fuse and the over-the-top time from the power-on time to the peak position, and calculate the time window in the radar echo where there is only noise and fixed interference and no effective target echo based on the power-on time and the over-the-top time;

[0060] Step S22: Calculate the value of N according to the time window calculated in step S21 and the operating frame period. The calculation formula of N is:

[0061]

[0062] where Time_summit represents the over-the-top time; Time_on represents the power-on time of the fuse; T_frame represents the operating frame period of the fuse radar.

[0063] Therefore, in this embodiment, by analyzing the physical motion characteristics of the fuse radar and the operating frame period, the accurate determination of the first N frame data volume required for background noise statistics is realized. Using the parabolic motion trajectory of the fuse, the position information of the fuse from power-on to over-the-top can be clarified. During this time window, the state of the fuse is to emit electromagnetic wave signals into the air, ensuring that the main lobe direction of the radiation pattern is towards the air, and the position of the fuse at the power-on moment of the radar fuse is also in the air. Furthermore, it can also ensure that the side lobes do not detect ground targets. In this way, only from the physical level, the detection of ground targets of interest can be avoided, realizing the isolation of target signals at the physical level and effectively avoiding the interference of target signals on background noise statistics. At the same time, by using the physical motion characteristics of the fuse in this way to determine the value of N in a relatively simple manner, not only the requirement for the hardware computing ability is reduced, the consumption of computing resources is reduced, but also the design and debugging process of the system is simplified, the real-time performance of the system is improved, and a strong guarantee is provided for the rapid deployment and stable operation of the radar fuse in practical applications. In addition, for different fuse radars, there may be differences in their operating frame periods. The method described in this embodiment can be adaptively adjusted according to specific parameters to ensure that the data required for background noise statistics can be accurately obtained in various fuse radar systems. This can not only enhance the reliability of the entire radar fuse system in complex environments, but also reduce the false alarm and missed detection probabilities caused by inaccurate background noise statistics.

[0064] Further preferably, in step S2, it includes judging the frame number and calculating the reference signal and the clean target signal according to the judgment result; as Figure 2 shown,

[0065] If the frame number ≤ N, perform FFT modulus accumulation until the frame number is equal to N, and then calculate the mean value of the FFT moduli of the first N frames to obtain the reference signal containing the fixed interference signal;

[0066] Among them, the calculation formula for the FFT modulus value is as follows:

[0067]

[0068] In the above formula, FFT_M_i represents the modulus value of the FFT, a_i represents the real part of the FFT calculation result at the corresponding frequency point position; b_i represents the imaginary part of the FFT calculation result at the corresponding frequency point position.

[0069] Next, accumulate the FFT modulus values of the first N frames, and its formula is:

[0070]

[0071] In the above formula, FFT_List_i represents the cumulative value of the FFT modulus value of the i-th frequency point from the first frame to the N-th frame;

[0072] Next, calculate the average value of FFT_List_i to obtain a reference signal containing fixed interference signals.

[0073] FFT_List_i_ave = FFT_List_i / N

[0074] Among them, FFT_List_i_ave represents the average value of the cumulative value of the FFT modulus value of the i-th frequency point from the first frame to the N-th frame.

[0075] Thus, the reference signal containing fixed interference signals is calculated through the above formula, providing a reliable data basis for this solution, enabling the accurate extraction of the characteristics of fixed interference signals. When subtracting the reference signal from the signal containing the target signal and fixed interference signals, the operation based on the modulus value can clearly highlight the characteristics of the target signal, thereby more effectively removing the fixed interference and improving the purity of the target signal.

[0076] If the frame number > N, then skip the accumulation, calculate the FFT modulus value of the (N + 1)-th frame to obtain the signal containing the target signal and fixed interference signals, and then subtract the reference signal from this signal to recalculate the FFT modulus value, thereby obtaining a clean target signal. Its calculation formula is as follows:

[0077] FFT_M_i_new = FFT_M_i - FFT_List_i_ave

[0078] Among them, FFT_M_i_new represents the updated FFT modulus value corresponding to the i-th frequency point, that is, the clean target signal.

[0079] Thus, in this embodiment, a more accurate and adaptive fixed background noise elimination for the radar fuse system is achieved through the frame number judgment mechanism. By accumulating the FFT modulus values and calculating the average value of the first N frames to generate a reference signal during the stage where the frame number ≤ N, the scene characteristics of the radar fuse are fully utilized. For example, the physical isolation of the target signal in the first N frames ensures that the reference signal only contains fixed interference. This statistical method based on multi-frame accumulation can more comprehensively and stably characterize the characteristics of the fixed background noise compared to single-frame or random sampling, providing a reliable reference for subsequent interference elimination. Then, when the frame number > N, the accumulation is skipped and the new frame signal is directly processed. By subtracting the reference signal to recalculate the FFT modulus value, the fixed background noise in each frame signal can be stripped in real time. This method is adapted to the processing requirements of the N+1 frame and subsequent signals, ensuring that the target signal always maintains a high purity during dynamic updates, avoiding the continuous impact of fixed interference on subsequent analysis, thus making the fixed interference eliminated more thoroughly, greatly reducing the interference to subsequent CFAR processing, reducing both the false alarm rate and increasing the detection probability of real targets, thereby effectively improving the accuracy of fuse detonation.

[0080] As Figure 4 shown, Figure 4 Figure 1 is a schematic diagram of the background noise statistics of the first N frame signals provided by this solution. It can be seen from this figure that there are complex interferences in the current environment of the radar system. To solve the influence of this interference, the method mentioned in this embodiment is used to eliminate this interference, and its effect is as Figure 5 shown, Figure 5 The left data in Figure 2 is the original signal spectrum in the presence of the target signal. If CFAR processing is directly performed on the left data, then a lot of invalid interference signals will be obtained, which will further affect the subsequent algorithm and increase the false alarm rate of the radar. However, the right data obtained after using the method described in this embodiment can largely eliminate the fixed interference signals. Thus, it can be seen that the method described in this embodiment can effectively improve the influence of the fixed interference frequency on the effective signal, and can improve the detonation rate and accuracy of the fuse system.

[0081] Step S3: Perform CFAR processing on the clean target signal obtained in step S2 to perform accurate radar fuse target detection, specifically including: dynamically adjusting the threshold value of target detection according to the intensity of the clean target signal. When the signal intensity exceeds the threshold value, it is determined as a real target; otherwise, it is determined as noise or clutter, so as to further eliminate noise interference and obtain the accurate target of the radar fuse.

[0082] Thus, through the pre-processing of background noise elimination, a clean target signal is obtained. By performing CFAR processing to dynamically adjust the threshold value, and comparing the intensity of the obtained clean target signal with the threshold value, the target and interference can be further distinguished to eliminate noise interference, realizing more accurate identification of real targets, reducing the misjudgment probability caused by the fuse, and improving the accuracy of fuse detonation.

[0083] In a radar system, fixed interference signals are usually generated by the hardware noise of the system itself or constant interference sources in the external environment (such as power supply noise, background clutter, etc.). These interference signals will affect the accuracy of proximity fuse target detection in the radar. Therefore, in this application, the FFT algorithm is used to calculate the modulus value, and then a reference signal containing the fixed interference signal is obtained according to the modulus value result, so that the interference components in the actual target signal can be effectively separated. Then, the original signal containing the target signal and the fixed interference signal is used to subtract the reference signal to eliminate the fixed interference in the fuse system and obtain a clean target signal. Finally, the CFAR algorithm is used for processing to obtain an accurate radar fuse target. Therefore, the method of eliminating interference from the signal processing end after the FFT algorithm and before the CFAR algorithm has obvious advantages compared with the method of eliminating interference from the result end. It can retain the detection ability of the signal at the interference position, ensure the continuity of the detection data while reducing the false alarm rate. At the same time, compared with the method of eliminating fixed interference from the ADC end, the calculation amount of this application is less and it is not easy to cause signal distortion, thus effectively reducing the radar false alarm phenomenon caused by fixed interferences such as the environment and the system itself, further reducing the false alarm rate caused by the fuse, and improving the accuracy of fuse detonation.

[0084] Embodiment 2

[0085] As Figure 6 shown, this embodiment provides an elimination system for the fixed background noise of a radar fuse according to the elimination method described in Embodiment 1. The system includes:

[0086] A data acquisition unit 610, configured to read analog signal data through an analog-to-digital converter after powering on the radar, and convert the analog signal data into digital signal data;

[0087] An interference elimination unit 620, configured to use the FFT algorithm to calculate the modulus value of the digital signal data processed by the data acquisition unit, and process it according to the modulus value result to obtain a reference signal containing the fixed interference signal, and then subtract the reference signal from the signal containing the target signal and the fixed interference signal to obtain a clean target signal, so as to eliminate the fixed interference;

[0088] A target detection unit 630, configured to perform CFAR processing on the clean target signal obtained by the interference elimination unit, so as to perform accurate radar fuse target detection.

[0089] In the system described in this embodiment, the data after the radar is powered on is acquired and processed by the data acquisition unit, and then the interference rejection unit is used to reject interference from the signal processing end after the FFT algorithm and before the CFAR algorithm. This method has obvious advantages compared with the method of rejecting interference from the result end. It can retain the detection ability of the signal at the interference position, reduce the false alarm rate while ensuring the continuity of the detection data. At the same time, compared with the method of rejecting fixed interference from the ADC end, the calculation amount of this system is less and it is not easy to cause signal distortion, thus effectively reducing the radar false alarm phenomenon caused by fixed interference such as the environment and the system itself, further reducing the false alarm rate caused by the fuse, and improving the accuracy of the fuse detonation.

[0090] Preferably, in the interference rejection unit, it includes:

[0091] A frame number calculation component, which is used to determine the amount of the first N frames of data required for background noise statistics according to the physical motion characteristics and the running frame period of the fuse radar, so as to calculate the value of N. The calculation formula of N is:

[0092]

[0093] where Time_summit represents the over-the-top time; Time_on represents the power-on time of the fuse; T_frame represents the running frame period of the fuse radar;

[0094] A frame number judgment component, which is used to calculate the reference signal and the clean target signal according to the frame number judgment result, including:

[0095] If it is judged that the frame number ≤ N, perform FFT modulus accumulation until the frame number is equal to N, and then calculate the mean value of the FFT moduli of the first N frames to obtain the reference signal containing the fixed interference signal;

[0096] If it is judged that the frame number > N, skip the accumulation, calculate the FFT modulus of the (N + 1)-th frame to obtain the signal containing the target signal and the fixed interference signal, and then subtract the reference signal from this signal to recalculate the FFT modulus, so as to obtain the clean target signal.

[0097] In this embodiment, by using the frame number calculation component to analyze the physical motion characteristics of the fuze radar and the operating frame period, the amount of the first N frames of data required for accurate background noise statistics is determined. The position information of the fuze from power-on to over-the-top is clarified by using the parabolic motion trajectory of the fuze. During this time window, the state of the fuze is to emit electromagnetic wave signals into the air, ensuring that the main lobe direction of the radiation pattern is into the air, and the position of the fuze at the power-on moment of the radar fuze is also in the air. Furthermore, it can also ensure that ground targets cannot be detected by the side lobes. In this way, the detection of ground targets of interest can be avoided only from the physical level, realizing the isolation of target signals at the physical level and effectively avoiding the interference of target signals on background noise statistics. At the same time, the frame number judgment component is also used to judge the frame number, and corresponding calculations are performed according to the frame number judgment result to obtain clean target signals, thereby realizing the fixed background noise rejection of a more accurate and adaptive radar fuze system.

[0098] Specifically, the system for rejecting the fixed background noise of the radar fuze provided in the embodiment of this solution is used to execute the method for rejecting the fixed background noise of the radar fuze described above in this solution. Its implementation manner is consistent with the implementation manner of the method for rejecting the fixed background noise of the radar fuze provided in this solution and can achieve the same beneficial effects, which will not be elaborated here.

[0099] The system for rejecting the fixed background noise of the radar fuze is used for the method for rejecting the fixed background noise of the radar fuze in the foregoing embodiments. Therefore, the descriptions and definitions in the method for rejecting the fixed background noise of the radar fuze in the foregoing embodiments can be used for the understanding of each execution module in the embodiment of this solution.

[0100] Figure 7 is the structural schematic diagram of the electronic device provided in this solution. As Figure 7As shown in the figure, the electronic device may include: a processor 710, a communications interface 720, a memory 730, and a communication bus 740. Among them, the processor 710, the communications interface 720, and the memory 730 complete mutual communication through the communication bus 740. The processor 710 can call the logical instructions in the memory 730 to execute the method for eliminating the fixed background noise of the radar fuse. The method includes: Step S1: After powering on the radar, read the analog signal data through an analog-to-digital converter and convert the analog signal data into digital signal data; Step S2: Use the FFT algorithm to calculate the modulus value of the digital signal data processed in Step S1, and process the modulus value result to obtain a reference signal containing the fixed interference signal. Then, subtract the reference signal from the signal containing the target signal and the fixed interference signal to obtain a clean target signal, thereby eliminating the fixed interference; Step S3: Perform CFAR processing on the clean target signal obtained in Step S2 to further eliminate noise interference and obtain the accurate target of the radar fuse.

[0101] In addition, when the logical instructions in the above-mentioned memory 730 can be implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this solution, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this solution. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0102] On the other hand, this solution also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for eliminating the fixed background noise of the radar fuse provided by the above-mentioned various methods. The method includes: Step S1: After powering on the radar, read analog signal data through an analog-to-digital converter and convert the analog signal data into digital signal data; Step S2: Use the FFT algorithm to calculate the modulus value of the digital signal data processed in Step S1, and process according to the modulus value result to obtain a reference signal containing a fixed interference signal. Then, subtract the reference signal from the signal containing the target signal and the fixed interference signal to obtain a clean target signal, thereby eliminating the fixed interference; Step S3: Perform CFAR processing on the clean target signal obtained in Step S2 to further eliminate noise interference and obtain the accurate target of the radar fuse.

[0103] On another aspect, this solution also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the method for eliminating the fixed background noise of the radar fuse provided by the above-mentioned various methods. The method includes: Step S1: After powering on the radar, read analog signal data through an analog-to-digital converter and convert the analog signal data into digital signal data; Step S2: Use the FFT algorithm to calculate the modulus value of the digital signal data processed in Step S1, and process according to the modulus value result to obtain a reference signal containing a fixed interference signal. Then, subtract the reference signal from the signal containing the target signal and the fixed interference signal to obtain a clean target signal, thereby eliminating the fixed interference; Step S3: Perform CFAR processing on the clean target signal obtained in Step S2 to further eliminate noise interference and obtain the accurate target of the radar fuse.

[0104] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0105] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0106] Obviously, the above embodiments of the present invention are only examples for clearly illustrating the technical solutions of the present invention, rather than limitations on the specific implementation manners of the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the claims of the present invention shall be included in the protection scope of the claims of the present invention.

Claims

1. A method for eliminating the fixed background noise of a radar fuse, characterized in that, The method includes the following steps: Step S1: After powering on the radar, read analog signal data through an analog-to-digital converter and convert the analog signal data into digital signal data; Step S2: Use the FFT algorithm to calculate the modulus value of the digital signal data processed in Step S1, and process according to the modulus value result to obtain a reference signal containing a fixed interference signal. Then subtract the reference signal from the signal containing the target signal and the fixed interference signal to obtain a clean target signal, thereby eliminating the fixed interference; Step S3: Perform CFAR processing on the clean target signal obtained in Step S2 to further eliminate noise interference and obtain the accurate target of the radar fuse.

2. A method for eliminating the fixed background noise of a radar fuse according to claim 1, characterized in that, In Step S2, it includes judging the frame number and calculating the reference signal and the clean target signal according to the judgment result; If the frame number ≤ N, perform FFT modulus accumulation until the frame number equals N, and calculate the mean value of the FFT modulus of the first N frames to obtain a reference signal containing a fixed interference signal; If the frame number > N, skip the accumulation, calculate the FFT modulus of the (N + 1)-th frame to obtain a signal containing the target signal and the fixed interference signal, and then subtract the reference signal from this signal to recalculate the FFT modulus, thereby obtaining a clean target signal.

3. A method for eliminating the fixed background noise of a radar fuse according to claim 2, characterized in that, The method also includes determining the amount of the first N frames of data required for background noise statistics based on the physical motion characteristics and operating frame period of the fuse radar, specifically including the following steps: Step S21: When the airborne motion trajectory of the fuse is a parabolic trajectory, determine the position of the fuse at each time point, obtain the power-on time of the fuse and the over-the-top time when the fuse reaches the peak position from the power-on time, and calculate the time window in which there is only noise and fixed interference and no effective target echo in the radar echo according to the power-on time and the over-the-top time; Step S22: Calculate the value of N according to the time window calculated in Step S21 and the operating frame period.

4. A method for eliminating the fixed background noise of a radar fuse according to claim 3, characterized in that, In Step S22, the calculation formula of N is: where, Time_summit represents the over-the-top time; Time_on represents the power-on time of the fuse; T_frame represents the operating frame period of the fuse radar.

5. A method for eliminating the fixed background noise of a radar fuse according to any one of claims 1 to 4, characterized in that, The calculation formula of the FFT modulus is: where, FFT_M_i represents the modulus value of the FFT, a_i represents the real part of the FFT calculation result at the corresponding frequency point position; b_i represents the imaginary part of the FFT calculation result at the corresponding frequency point position.

6. A method for eliminating the fixed background noise of a radar fuse according to any one of claims 1 to 4, characterized in that In Step S3, it includes: dynamically adjusting the threshold value of target detection according to the intensity of the clean target signal. When the signal intensity exceeds the threshold value, it is determined as a real target, otherwise it is determined as noise or clutter, and further eliminate noise interference to obtain the accurate target of the radar fuse.

7. A rejection system for the fixed background noise of a radar fuse, which is based on the rejection method for the fixed background noise of a radar fuse according to any one of claims 1-6, characterized in that, The system includes: A data acquisition unit, which is used to read analog signal data through an analog-to-digital converter after powering on the radar and convert the analog signal data into digital signal data; An interference elimination unit, which is used to use the FFT algorithm to calculate the digital signal data processed by the data acquisition unit to obtain a reference signal containing a fixed interference signal, and then subtract the reference signal from the signal containing the target signal and the fixed interference signal to obtain a clean target signal, thereby eliminating the fixed interference; The target detection unit is used to perform CFAR processing on the clean target signal obtained by the interference rejection unit, and further remove noise interference to obtain the accurate target of the radar fuse.

8. A rejection system for fixed background noise of a radar fuse according to claim 7, characterized in that, In the interference rejection unit, it includes: The frame number calculation component is used to determine the amount of the first N frame data required for background noise statistics through the physical motion characteristics and operating frame period of the fuse radar, so as to calculate the value of N. The calculation formula of N is: Among them, Time_summit represents the over-the-top time; Time_on represents the power-on time of the fuse; T_frame represents the operating frame period of the fuse radar; The frame number judgment component is used to calculate the reference signal and the clean target signal according to the frame number judgment result, including: If it is judged that the frame number ≤ N, perform FFT modulus accumulation until the frame number is equal to N, and then calculate the mean value of the FFT modulus of the first N frames to obtain the reference signal containing the fixed interference signal; If it is judged that the frame number > N, skip the accumulation, calculate the FFT modulus of the (N + 1)th frame to obtain the signal containing the target signal and the fixed interference signal, and then subtract the reference signal from this signal to recalculate the FFT modulus, so as to obtain the clean target signal.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for removing the fixed background noise of the radar fuse according to any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for removing the fixed background noise of the radar fuse according to any one of claims 1 to 6.

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