Interference suppression method and device based on multi-dimensional domain feature analysis

Abstract

The application discloses a kind of based on multi-dimensional domain feature analysis interference suppression method and device, it is related to radar signal processing technical field, wherein, the method includes: different airspace multi-beam carries out frequency domain, time-frequency domain feature extraction, adaptive threshold calculation, interference mask positioning, interference time domain cancellation, engineering integrated application;It uses single pulse level processing, does not change the original signal processing procedure of radar, can be embedded in radar signal processing link in real time;The application is mainly used to solve the detection and suppression of radar main lobe interference, especially in radar game anti-interference field, real-time is high, interference cancellation effect is good, and it is very easy to engineering integration, suitable for different interference countermeasure scene such as narrow pulse, deception false target, dense false target.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, and in particular to an interference suppression method and an interference suppression device based on multidimensional domain feature analysis. Background Technology

[0002] In the complex electromagnetic environment faced by modern radar systems, main lobe interference is one of the core bottlenecks restricting radar detection performance. Main lobe interference sources (such as deceptive jamming and suppression jamming) emit interference signals in the direction of the radar main lobe, which can directly intrude into the radar receiving channel, causing the target echo to be masked, the accuracy of target parameter estimation to decrease, and even causing radar detection failure, seriously threatening the operational effectiveness of radar in key scenarios such as air defense, guidance, and battlefield reconnaissance.

[0003] Among existing radar anti-jamming technologies, methods such as sidelobe cancellation and sidelobe concealment mainly target sidelobe interference, with limited effectiveness in suppressing mainlobe interference. The industry has developed multi-dimensional anti-jamming paths in the spatial, frequency, polarization, and time-coding domains, but all have significant limitations: Spatial domain algorithms such as Digital Beam Forming (DBF) and Minimum Variance Distortionless Response (MVDR) have strong directional suppression capabilities, but are sensitive to Direction of Arrival (DOA) errors and array consistency, requiring complex engineering calibration and consuming significant computational resources, and are prone to target cancellation phenomena; Frequency domain adaptive filtering and frequency agility technologies are mature in principle and have acceptable adaptability, but have limited suppression of broadband interference and are constrained by RF front-end switching speed; Polarization domain methods do not require additional time / frequency domain resources but rely on dedicated hardware, resulting in high cost and complexity, and insufficient robustness; Time-coding domain schemes such as orthogonal pulse coding have good anti-spoofing interference suppression effects, but the algorithms have high computational load and real-time performance is difficult to guarantee. While multi-domain joint solutions offer superior performance, they face challenges such as complex collaboration, difficulties in hardware integration, and poor engineering feasibility.

[0004] In summary, existing methods struggle to balance anti-jamming performance with engineering practicality. As jamming technologies evolve towards broadband, intelligent, and collaborative approaches, the patterns of main lobe jamming become increasingly complex, placing higher demands on the real-time performance, robustness, and engineering feasibility of radar main lobe jamming mitigation. Therefore, there is an urgent need to develop a radar main lobe jamming mitigation method that balances performance and engineering feasibility. Summary of the Invention

[0005] This invention aims to at least partially solve one of the technical problems in the aforementioned technologies. Therefore, one objective of this invention is to propose an interference suppression method based on multi-dimensional domain feature analysis, which can improve the suppression effect of radar main lobe interference, enhance engineering feasibility, reduce hardware time overhead, and does not alter the original radar signal processing flow, making it very easy to integrate into engineering projects.

[0006] The second objective of this invention is to propose an interference suppression device based on multidimensional domain feature analysis.

[0007] To achieve the above objectives, a first aspect of the present invention proposes an interference suppression method based on multi-dimensional domain feature analysis, comprising: acquiring baseband echo data of a radar multibeam; performing frequency domain and time-frequency domain transformations on the baseband echo data, and performing spectral analysis on the result after frequency domain transformation and time-frequency domain transformation to obtain frequency domain energy peaks, time-frequency map energy values, and energy frequency statistics; performing adaptive label calculation based on the frequency domain energy peaks, time-frequency map energy values, and energy frequency statistics to obtain adaptive label values, and performing threshold calculation based on the adaptive label values ​​to obtain time-frequency map thresholds; comparing the time-frequency map energy values ​​with the time-frequency map thresholds, marking the positions where the time-frequency map energy values ​​are greater than the time-frequency map thresholds as mask positions corresponding to the interference region, and retaining the data within the mask positions to obtain the time-frequency data of the interference; transforming the time-frequency data of the interference into a time-domain interference signal, and subtracting the time-domain interference signal from the baseband echo data to obtain the time-domain echo data after interference suppression.

[0008] The interference suppression method based on multi-dimensional domain feature analysis according to embodiments of the present invention achieves precise interference localization by combining features from the frequency domain and time-frequency domain. It fully mines the features in the time and frequency domains before and after interference suppression, and feeds back the results of initial interference suppression for feature analysis to adjust the suppression threshold in real-time closed-loop. This reduces the algorithm complexity in the frequency and time-frequency domains, thereby reducing hardware resource consumption. It ensures both rapid perception of the interference environment and real-time evaluation of the anti-interference effect, thus improving the algorithm's anti-interference capability and engineering feasibility.

[0009] In addition, the interference suppression method based on multidimensional domain feature analysis proposed in the above embodiments of the present invention may also have the following additional technical features: Optionally, the baseband echo data of the radar multi-beam includes searching multi-beams and tracking sum and difference multi-beams. When searching multi-beams, each beam adopts the same processing procedure; when tracking sum and difference multi-beams, the sum and difference beams adopt different processing procedures. After completing the interference mask positioning with the sum beam as a reference, the difference beam is used to assist in interference suppression.

[0010] Optionally, when performing spectral analysis on the results after frequency domain transformation, the process includes: performing spectral analysis on the baseband echo data to extract the frequency domain energy peak; performing spectral analysis on the data after interference suppression to extract the frequency domain energy peak of the first pulse echo after interference suppression; and performing spectral analysis on the frequency domain energy peak of the echo after interference suppression to evaluate the interference suppression result.

[0011] Optionally, when performing time-frequency domain transformation on the result, the analysis includes: performing a short-time Fourier transform on the baseband echo data and storing the result, obtaining the energy value of the time-frequency graph and normalizing it, and counting the frequency of the energy value to obtain the energy frequency statistics result.

[0012] Optionally, when performing adaptive tag calculation, the proportion of strong energy echoes in the time-frequency graph energy value is found and converted into adaptive tag values, and the presence of interference is detected in the energy domain of the frequency domain and time-frequency domain.

[0013] Optionally, the threshold can be calculated by multiplying the adaptive label value and the energy frequency statistics.

[0014] To achieve the above objectives, a second aspect of the present invention proposes an interference suppression device based on multi-dimensional domain feature analysis, comprising: an acquisition module for acquiring baseband echo data of a radar multibeam; an analysis module for performing frequency domain and time-frequency domain transformations on the baseband echo data, and performing spectral analysis on the result after frequency domain transformation and time-frequency domain transformation on the result after time-frequency domain transformation to obtain frequency domain energy peak value, time-frequency map energy value, and energy frequency statistics; and a calculation module for performing adaptive tag counting based on the frequency domain energy peak value, time-frequency map energy value, and energy frequency statistics. The system calculates an adaptive label value and performs a threshold calculation based on the adaptive label value to obtain a time-frequency map threshold. An extraction module compares the time-frequency map energy value with the time-frequency map threshold, marks the location where the time-frequency map energy value is greater than the time-frequency map threshold as the mask location corresponding to the interference region, and retains the data within the mask location to obtain the time-frequency data of the interference. An interference cancellation module transforms the time-frequency data of the interference into a time-domain interference signal and subtracts the time-domain interference signal from the baseband echo data to obtain the time-domain echo data after interference suppression. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the interference suppression method based on multidimensional domain feature analysis according to an embodiment of the present invention. Figure 2This is a block diagram illustrating the principle of interference detection and suppression according to an embodiment of the present invention. The diagram shows the details and corresponding connections of modules such as spatial beam splitting, feature extraction in the frequency and time-frequency domains, adaptive label and threshold calculation, interference mask localization and extraction, and interference time-domain cancellation. Figure 3 This is a schematic diagram of airspace beam splitting processing according to an embodiment of the present invention. The figure illustrates the beam splitting methods for two radar systems: search and tracking, as shown below. Figure 3 (a) and Figure 3 As shown in (b), the same processing procedure is used for searching each beam, while different processing procedures are used for tracking the sum and difference beams. The interference mask positioning is completed with the sum beam as a reference, and then the difference beam is used to suppress interference. Figure 4 This is a block diagram of spectrum analysis according to an embodiment of the present invention; Figure 5 This is a block diagram of time-frequency analysis according to an embodiment of the present invention; Figure 6 This is a block diagram of adaptive labeling and interference detection according to an embodiment of the present invention; Figure 7 This is a block diagram of interference mask localization and extraction according to an embodiment of the present invention; Figure 8 This is a block diagram of interference time-domain cancellation according to an embodiment of the present invention; Figure 9 This is a block diagram for engineering integration applications. The diagram shows the input data module, interference detection and suppression module, and includes bypass and interference suppression completion indicators. Figure 10 This is a schematic diagram of the instantiation of the input data module in an FPGA; Figure 11 This is a schematic diagram of an instantiation of the interference detection and suppression module in an FPGA; Figure 12 The diagram shows the actual effect of narrow pulse interference suppression. Figure 13 The diagram shows the effect of suppressing interference from deceiving false targets at the measured distance. Figure 14 The diagram shows the effect of suppressing dense false target interference as measured in the experiment; Figure 15 This is a block diagram of an interference suppression device based on multidimensional domain feature analysis according to an embodiment of the present invention. Detailed Implementation

[0016] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0017] To better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the invention to those skilled in the art.

[0018] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0019] Figure 1 This is a flowchart illustrating the interference suppression method based on multidimensional domain feature analysis according to an embodiment of the present invention, as shown below. Figure 1 As shown, the interference suppression method based on multidimensional domain feature analysis includes the following steps: S101, acquires baseband echo data of radar multibeams.

[0020] As an example, the baseband echo data of the radar multi-beam includes searching multi-beams and tracking sum-difference multi-beams. During the searching multi-beam processing, each beam adopts the same processing procedure; during the tracking sum-difference multi-beam processing, the sum and difference beams adopt different processing procedures. After completing the interference mask positioning with the sum beam as a reference, the difference beam is used to assist in interference suppression.

[0021] S102 performs frequency domain and time-frequency domain transformation on the baseband echo data, performs spectrum analysis on the result after frequency domain transformation, and performs time-frequency spectrum analysis on the result after time-frequency domain transformation to obtain frequency domain energy peak value, time-frequency graph energy value, and energy frequency statistics.

[0022] As an example, when performing spectral analysis on the results after frequency domain transformation, the process includes: performing spectral analysis on the baseband echo data to extract the frequency domain energy peak; performing spectral analysis on the data after interference suppression to extract the frequency domain energy peak of the echo after interference suppression of the first pulse; and performing spectral analysis on the frequency domain energy peak of the echo after interference suppression to evaluate the interference suppression result.

[0023] As an example, when performing time-frequency domain transformation on the result, the process includes: performing a short-time Fourier transform on the baseband echo data and storing the result, obtaining the energy value of the time-frequency graph and normalizing it, and counting the frequency of the energy value to obtain the energy frequency statistics result.

[0024] In other words, by combining the different beam spatial coverage characteristics of radar, each beam is processed independently, and the baseband echo data of the corresponding beam is transformed in the frequency domain and time-frequency domain. The results after frequency domain transformation are subjected to spectrum analysis, and the results after time-frequency domain transformation are subjected to time-spectrum analysis.

[0025] S103. Based on the frequency domain energy peak, time-frequency graph energy value, and energy frequency statistics, adaptive label calculation is performed to obtain the adaptive label value. Based on the adaptive label value, threshold calculation is performed to obtain the time-frequency graph threshold.

[0026] As an example, when performing adaptive tag calculation, the process includes finding the proportion of strong energy echoes in the time-frequency graph energy values ​​and converting them into adaptive tag values, and detecting the presence of interference in the energy domain of the frequency domain and time-frequency domain.

[0027] As an example, the time-frequency map threshold is calculated by multiplying the adaptive label value and the energy frequency statistics.

[0028] In other words, when calculating the adaptive tag, the peak value of the echo frequency domain energy after interference suppression is calculated, the proportion of strong energy echoes in the time-frequency graph is found and converted into a tag value, and the presence of interference is detected in the energy domain of the frequency domain and time-frequency domain; when calculating the threshold, it is calculated using the adaptive tag value and the statistical frequency of the energy in the time-frequency graph.

[0029] S104, compare the energy value of the time-frequency map with the threshold of the time-frequency map, mark the position where the energy value of the time-frequency map is greater than the threshold of the time-frequency map as the mask position corresponding to the interference area, and retain the data within the mask position to obtain the time-frequency data of the interference.

[0030] In other words, when locating interference using a mask, the energy value of the time-frequency image is compared with the threshold value of the time-frequency image, and the positions in the time-frequency image that are greater than the threshold value are marked as mask positions. When extracting interference, the data in the time-frequency image that are inside the mask are retained, and the data outside the mask are cleared to zero.

[0031] S105 transforms the time-frequency data of the interference into a time-domain interference signal, and subtracts the time-domain interference signal from the baseband echo data to obtain the time-domain echo data after interference suppression.

[0032] In other words, during interference recovery, the data within the mask in the time-frequency diagram is restored to the time domain; during interference cancellation, the suppression result is obtained by subtracting the interference restored to the time domain from the input baseband echo.

[0033] It should be noted that, in the engineering implementation of the programmable device, the input data module is designed as follows: According to the actual radar data format requirements, the input parallel multi-beam baseband echo data is converted into the serial multi-beam data required by the interference detection and suppression module of this application; simultaneously, considering the radar's pulse repetition period and processing time overhead, the number of beams participating in interference suppression is set, and a bypass flag is generated. An interference suppression completion flag is designed: when the interference detection and suppression module of this application outputs the interference suppression results for each beam, a current beam interference suppression completion flag is generated to guide the next beam sequential input to the input data module.

[0034] To better understand the above technical solution, this application proposes a specific embodiment, such as... Figure 2 As shown, it includes the following steps: (1) Multi-beam feature extraction in different spatial domains in the frequency and time-frequency domains; (2) Adaptive label and threshold calculation; (3) Interference mask localization and extraction; (4) Interference time-domain cancellation; (5) Engineering integration application.

[0035] As a preferred implementation scheme of this application, refer to Figure 2 In step (1), the process of extracting features in the frequency domain and time-frequency domain from multiple beams in different spatial domains is as follows: Step (1-1) Spatial beam splitting: Refer to Figure 3 When considering the airspace coverage characteristics of different radar beams, each beam is processed independently. If searching multiple beams, each beam adopts the same processing procedure. If tracking multiple beams and difference beams, the sum and difference beams adopt different processing procedures. The sum beam is used as a reference to complete the interference mask positioning and then the difference beam is used to assist in interference suppression.

[0036] Step (1-2) Spectrum Analysis: Refer to Figure 4 First, spectral analysis is performed on the baseband echo data to extract the peak frequency domain energy, which is used for subsequent adaptive tag calculation. Then, spectral analysis is performed on the interference-suppressed data to calculate the peak frequency domain energy of the suppressed echo. This is used both to calculate the initial signal energy and to evaluate the interference suppression results. (Peak frequency domain energy) As shown below:

[0037]

[0038] Here, the peak value of the frequency domain energy is used. This represents frequency domain energy. Among them, It is the time-domain real and imaginary part echo sequence before pulse compression. yes The discrete Fourier transform.

[0039] Spectrum analysis during steps (1-3): Refer to Figure 5 First, the baseband echo data Perform a 32-point Short Time Fourier Transform (STFT) to obtain the peak energy value of the time-frequency map, and normalize it to the range of 0~255. Then, count the frequency of the time-frequency domain energy within the quantization range for subsequent calculation of the interference suppression threshold.

[0040] Time-frequency energy As shown below:

[0041] in, The time frame number, The frame shift step size, These are discrete frequency points.

[0042] As a preferred embodiment of this application, the adaptive label and threshold calculation process in step (2) is as follows: Step (2-1) Adaptive Label Calculation: Refer to Figure 6 The label value represents the proportion of interference indirectly eliminated. First, the peak spectral energy after interference suppression is obtained from (1-2). This value is the expected spectral energy value of the interference-free echo calculated from the first pulse out of 32 pulses. The smaller this value, the more subsequent interference is suppressed, and the lower the calculated threshold value. Then, combined with the frequency of energy occurrence in the time-frequency domain, the proportion of stronger energy echoes in the time-frequency graph is found, i.e., the label value.

[0043] Step (2-2) Threshold Calculation: Calculated from the adaptive label and the frequency of occurrence of time-frequency domain energy. Assume the adaptive label is... The frequency of energy occurrence in the time-frequency domain is Then the threshold for:

[0044] Among them, the energy values ​​on the time-frequency graph They are different; the specific values ​​are set according to the proportions displayed on the label.

[0045] Step (2-3) Interference Detection: Refer to Figure 6 The comparison is made using the energy domain. If both the frequency domain energy and the time domain energy exceed the reference energy after interference suppression of a pulse, then interference is considered to exist; otherwise, there is no interference.

[0046] Temporal energy before interference suppression As shown below:

[0047] Temporal reference energy after interference suppression As shown below:

[0048] in, , These are the time-domain sequences before and after interference suppression, respectively.

[0049] As a preferred implementation scheme of this application, refer to Figure 7 In step (3), the interference mask localization and extraction includes the following steps: Step (3-1) Interference Mask Location: Compare the energy value of the time-frequency map with the threshold. The positions in the time-frequency map that are greater than the threshold are marked as the mask positions corresponding to the interference areas, and the positions that are not greater than the threshold are the non-interference areas.

[0050] Step (3-2) Interference Extraction: Data within the mask position in the time-frequency graph is retained, and data outside the mask position is cleared to zero, thus obtaining the time-frequency data of the interference.

[0051] As a preferred implementation scheme of this application, refer to Figure 8 In step (4), the interference time-domain cancellation includes the following steps: Step (4-1) Interference Recovery: The data within the mask in the time-frequency plot is recovered to the time domain using the Inverse Short-Time Fourier Transform (ISTFT). The following formula is used:

[0052] in, To recover the discrete-time signal in the time domain, It is the time spectrum of the discrete short-time Fourier transform. For window functions, The length of the window.

[0053] Step (4-2) Interference cancellation: The interference recovered to the time domain is subtracted from the input baseband echo to obtain the suppression result.

[0054] As a preferred embodiment of this application, in step (5), refer to Figure 9 The engineering integration application includes the following steps: Step (5-1) Input Data Module Design: In the Field Programmable Gate Array (FPGA), firstly, the header of the baseband echo data stream is intercepted and buffered; secondly, the parallel multi-beam data of the baseband echo data stream body is written into the Dual Port Random Access Memory (DPRAM); thirdly, based on the pulse repetition period of the actual radar and the processing time overhead of the interference detection and suppression module of this invention, the number of beams that can participate in interference suppression is calculated; finally, the starting beam number and ending beam number for participating in interference suppression processing are set, and beams not within the processing range are directly output serially.

[0055] The number of beams that can participate in interference suppression in the above steps The following formula must be satisfied:

[0056] in, This is the total number of radar receiving beams, a known value. The number of beams that do not participate in interference suppression. The repetition period of one pulse; The processing time overhead of the interference detection and suppression module in this application is 51. ; The beam serial output time that does not participate in interference suppression is a known value, determined by the number of sampling points within the radar repetition frequency and the FPGA processing clock rate, i.e., derived from the following formula.

[0057]

[0058] According to the above formula, for example, if the number of sampling points within the radar repetition frequency is 1000 and the FPGA processing clock is 200MHz, then... equals 5 .

[0059] Step (5-2) generates the bypass flag: In the FPGA, the input data module sets the bypass flag based on the start beam number and the end beam number. That is, the bypass flag is set for beams within the start and end beam numbers. Set to 0 for the other beams and to 1 for the others.

[0060] Step (5-3) Generate interference suppression completion flag: In the FPGA, when the interference detection and suppression module of this invention outputs the interference suppression result of the current beam, it generates the current beam interference suppression completion flag at the end of the suppression result output. This flag is connected to the input data module, which uses it to initiate the DPRAM reading action and complete the sequential output of the next beam data, thereby ensuring that all beams are connected to the interference detection and suppression module for corresponding processing in the processing sequence.

[0061] In summary, the interference suppression method based on multi-dimensional domain feature analysis according to embodiments of the present invention comprehensively utilizes multi-dimensional domain feature information to solve the problem of real-time reliable perception of main lobe interference and improve the detection capability of main lobe interference; it fully utilizes the interference distribution characteristics in the time and frequency domain to solve the problem of real-time accurate separation of main lobe interference and improves the suppression capability of main lobe interference; it is implemented in real-time embedded in a field-programmable gate array, solving the problems of difficult hardware integration and poor engineering feasibility of conventional multi-dimensional domain anti-interference methods and improving the engineering feasibility of main lobe interference detection and suppression; it is applicable to various radar systems, including search, tracking, and phased array radars, and adopts single-pulse level processing without changing the original signal processing flow of the radar, and can be embedded in the signal processing link in real time.

[0062] To achieve the above embodiments, such as Figure 15 As shown, this embodiment of the invention also proposes an interference suppression device based on multidimensional domain feature analysis, including an acquisition module 10, an analysis module 20, a calculation module 30, an extraction module 40, and an interference cancellation module 50.

[0063] The system comprises the following modules: Acquisition module 10 acquires baseband echo data from a multi-beam radar; Analysis module 20 performs frequency-domain and time-frequency-domain transformations on the baseband echo data, performs spectral analysis on the frequency-domain transformation result, and performs time-frequency-domain spectral analysis on the time-frequency-domain transformation result to obtain frequency-domain energy peaks, time-frequency map energy values, and energy frequency statistics; Calculation module 30 performs adaptive label calculation based on the frequency-domain energy peaks, time-frequency map energy values, and energy frequency statistics to obtain adaptive label values, and performs threshold calculation based on the adaptive label values ​​to obtain time-frequency map thresholds; Extraction module 40 compares the time-frequency map energy values ​​with the time-frequency map thresholds, marks the positions where the time-frequency map energy values ​​are greater than the time-frequency map thresholds as mask positions corresponding to the interference area, and retains the data within the mask positions to obtain the time-frequency data of the interference; Interference cancellation module 50 transforms the time-frequency data of the interference into a time-domain interference signal, and subtracts the time-domain interference signal from the baseband echo data to obtain the time-domain echo data after interference suppression.

[0064] As a specific embodiment, the hardware implementation is as follows: The relevant modules in this application are implemented using FPGA, including an input data module and an interference detection and suppression module.

[0065] (1) Input data module It consists of sub-modules such as baseband echo data stream header interception and caching, baseband echo data stream body parallel-to-serial multi-beam read and write, and bypass flag generation.

[0066] Reference Figure 10 RX_VLD, RX_SOF, RX_EOF, and RX_D are the frame valid, frame start, frame end, and frame data signal lines for the baseband echo data stream in the FPGA, respectively; aj_rcb_valid, aj_rcb_sof, and aj_rcb are the frame valid, frame start, and frame data signal lines for the header of the baseband echo data stream output from the FPGA, respectively; echo_din0_vld_200M and echo_din0_200M are the frame valid and frame data signal lines for the serial multibeam of the baseband echo data stream message body output from the FPGA, respectively; and bypass is the bypass flag signal line output from the FPGA.

[0067] (2) Interference detection and suppression module It consists of sub-modules such as 32-point STFT, STFT storage, finding the maximum value of the time-frequency graph, time-frequency graph quantization, time-frequency graph statistics, threshold calculation, FFT analysis, adaptive labeling, interference masking, interference recovery, interference detection, and interference time-domain cancellation.

[0068] Reference Figure 11 anti_jamming_dout0_vld_200M and anti_jamming_dout0_200M are the frame valid, frame start, frame end, and frame data signal lines output by the FPGA, respectively; beam_process_done is the interference suppression completion flag signal line output by the FPGA.

[0069] Based on field anti-jamming tests conducted with a certain radar, the implementation results of this application are as follows: (1) Narrow pulse interference Reference Figure 12 By processing the measured data with Matrix Laboratory (Matlab) software, it was found that 10 randomly occurring narrow pulse interferences in the baseband echo could be detected and suppressed, and the average interference-to-signal suppression ratio was calculated to be 18.3dB.

[0070] (2) Distance deception and interference with false targets Reference Figure 13 Through real-time processing using FPGA, it can detect and suppress three range-deception false target interferences in the baseband echo, and the calculated average interference-to-signal suppression ratio is 19.2dB.

[0071] (3) Dense decoy interference Reference Figure 14Through real-time processing using FPGA, dense false target interference in baseband echo can be detected and suppressed, and the average interference suppression ratio is calculated to be 20.2dB.

[0072] It should be noted that the above description and examples of the interference suppression method based on multidimensional domain feature analysis are also applicable to the interference suppression device based on multidimensional domain feature analysis in this embodiment, and will not be repeated here.

[0073] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0074] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0075] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0076] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0077] It should be noted that any reference signs placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0078] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0079] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0080] In the description of this invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0081] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0082] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0083] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms should not be construed as necessarily referring to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0084] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. An interference suppression method based on multidimensional domain feature analysis, characterized in that, Includes the following steps: Acquire baseband echo data from radar multibeams; The baseband echo data is transformed into the frequency domain and time-frequency domain, and the results of the frequency domain transformation are subjected to spectrum analysis, and the results of the time-frequency domain transformation are subjected to time-frequency spectrum analysis, so as to obtain the frequency domain energy peak value, time-frequency graph energy value, and energy frequency statistics. Adaptive label calculation is performed based on the frequency domain energy peak, time-frequency graph energy value, and energy frequency statistics to obtain an adaptive label value. Threshold calculation is then performed based on the adaptive label value to obtain a time-frequency graph threshold. The time-frequency map energy value is compared with the time-frequency map threshold, and the position where the time-frequency map energy value is greater than the time-frequency map threshold is marked as the mask position corresponding to the interference region. The data within the mask position is retained to obtain the time-frequency data of the interference. The time-frequency data of the interference is transformed into a time-domain interference signal, and the time-domain interference signal is subtracted from the baseband echo data to obtain the time-domain echo data after interference suppression.

2. The interference suppression method based on multidimensional domain feature analysis as described in claim 1, characterized in that, The baseband echo data of the radar multi-beam includes search multi-beam and tracking sum-difference multi-beam. During search multi-beam processing, each beam adopts the same processing procedure; during tracking sum-difference multi-beam processing, the sum and difference beams adopt different processing procedures. After completing the interference mask positioning with the sum beam as a reference, the difference beam is used to assist in interference suppression.

3. The interference suppression method based on multidimensional domain feature analysis as described in claim 1, characterized in that, When performing spectral analysis on the results after frequency domain transformation, the following are included: Spectral analysis is performed on the baseband echo data to extract the frequency domain energy peak. Spectral analysis is also performed on the data after interference suppression to extract the frequency domain energy peak of the first pulse echo after interference suppression. Spectral analysis is then performed on the frequency domain energy peak of the echo after interference suppression to evaluate the interference suppression results.

4. The interference suppression method based on multidimensional domain feature analysis as described in claim 1, characterized in that, When performing time-frequency domain transformation on the result, the following is included: Perform a short-time Fourier transform on the baseband echo data and store the results. Calculate the energy value of the time-frequency graph and normalize it. Statistically count the frequency of the energy value to obtain the energy frequency statistics.

5. The interference suppression method based on multidimensional domain feature analysis as described in claim 1, characterized in that, When performing adaptive tag calculation, the proportion of strong energy echoes in the time-frequency energy value is identified and converted into adaptive tag values. Interference is then detected in the energy domain of the frequency domain and time-frequency domain.

6. The interference suppression method based on multidimensional domain feature analysis as described in claim 1, characterized in that, The threshold for time-frequency maps is calculated by multiplying the adaptive label value and the energy frequency statistics.

7. The interference suppression device based on multidimensional domain feature analysis as described in claim 1, characterized in that, include: The acquisition module is used to acquire baseband echo data of the radar multibeams; The analysis module is used to perform frequency domain and time-frequency domain transformation on the baseband echo data, and to perform spectrum analysis on the result after frequency domain transformation and time-frequency domain transformation to obtain frequency domain energy peak value, time-frequency graph energy value, and energy frequency statistics. The calculation module is used to perform adaptive label calculation based on the frequency domain energy peak, time-frequency graph energy value, and energy frequency statistics to obtain an adaptive label value, and to perform threshold calculation based on the adaptive label value to obtain a time-frequency graph threshold. The extraction module is used to compare the energy value of the time-frequency map with the threshold value of the time-frequency map, mark the position where the energy value of the time-frequency map is greater than the threshold value of the time-frequency map as the mask position corresponding to the interference region, and retain the data within the mask position to obtain the time-frequency data of the interference; The interference cancellation module is used to transform the time-frequency data of the interference into a time-domain interference signal, and to subtract the time-domain interference signal from the baseband echo data to obtain the time-domain echo data after interference suppression.

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