Pulse doppler radar seeker signal processing method and system

Abstract

The application discloses a pulse Doppler radar seeker signal processing method and system, and relates to the technical field of signal processing.The method comprises the following steps: acquiring a radar detection environment, constructing a thermal map by analyzing an environmental interference frequency band, performing wave frequency processing constraint on a detection fundamental wave, and generating a fundamental frequency electromagnetic detection wave; deploying a parallel detection mode, performing parallel emission and echo reception of the fundamental frequency electromagnetic detection wave under a time sequence, performing main lobe interference filtering and multi-dimensional tensor decomposition on a received echo signal group, and determining a target signal group; and importing the target signal group into a signal processor, performing parallel processing of static dimensions and dynamic dimensions and result fitting, and outputting a radar detection result.The application solves the technical problems of insufficient anti-interference performance of a radar seeker in a complex strong interference environment and low target detection precision in the prior art, and achieves the technical effects of improving target recognition capability and anti-interference performance, improving radar detection accuracy and reliability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of signal processing, in particular to a pulse Doppler radar seeker signal processing method and system. BACKGROUND

[0002] The existing pulse Doppler radar seeker often faces complex combat electromagnetic environment when performing long-distance target detection tasks, and is easily affected by multi-source interference signals such as main lobe interference, side lobe interference and Doppler deception. The traditional seeker usually adopts a fixed transmission waveform and a single-channel echo processing mode, which is difficult to effectively suppress strong interference noise in the case of limited spectrum resources and dense clutter, resulting in unstable echo signal feature extraction, low target detection probability and high false alarm rate. At the same time, since the conventional signal processing procedure mainly performs static processing on single frame echo, it lacks dynamic fusion modeling capability for multiple frames of continuous signals, making it difficult to accurately capture small and weak moving targets, and restricting the improvement of the anti-interference detection performance and guidance accuracy of the seeker in complex environments. SUMMARY

[0003] The present application provides a pulse Doppler radar seeker signal processing method and system, which is used to solve the technical problems of insufficient anti-interference performance and low target detection accuracy of the radar seeker in complex strong interference environment in the prior art.

[0004] In view of the above problems, the present application provides a pulse Doppler radar seeker signal processing method and system.

[0005] In a first aspect of the present application, a pulse Doppler radar seeker signal processing method is provided, which comprises:

[0006] Obtaining a radar detection environment, constructing a heat map by analyzing the environment interference frequency band, performing wave frequency processing constraint of the detection fundamental wave, generating a fundamental frequency electromagnetic detection wave; deploying a parallel detection mode, performing parallel transmission and echo reception under time sequence on the fundamental frequency electromagnetic detection wave, performing main lobe interference filtering and multi-dimensional tensor decomposition on the received echo signal group, determining a target signal group, wherein the parallel detection mode contains at least four times of parallel detection; introducing the target signal group into a signal processor, performing parallel processing of static dimension and dynamic dimension and result fitting, and outputting a radar detection result, wherein the static dimension is processed with continuous frame signals, and the dynamic dimension is processed with step frame signals.

[0007] In a second aspect of the present application, a pulse Doppler radar seeker signal processing system is provided, which comprises:

[0008] The heat map construction module is used for acquiring a radar detection environment, constructing a heat map by analyzing an environmental interference frequency band, performing wave frequency processing constraint on a detection fundamental wave, and generating a fundamental frequency electromagnetic detection wave.

[0009] The one or more technical solutions provided in the application have at least the following technical effects or advantages:

[0010] The application acquires a radar detection environment, constructs a heat map by analyzing an environmental interference frequency band, performs wave frequency processing constraint on a detection fundamental wave, and generates a fundamental frequency electromagnetic detection wave. A parallel detection mode is deployed, parallel emission and echo reception under a time sequence are performed on the fundamental frequency electromagnetic detection wave, main lobe interference filtering and multi-dimensional tensor decomposition are performed on a received echo signal group, a target signal group is determined, wherein the parallel detection mode contains at least four times of parallel detection. The target signal group is introduced into a signal processor, parallel processing of static dimensions and dynamic dimensions and result fitting are performed, and radar detection results are output, wherein continuous frame signals are used for static dimension processing, and step frame signals are used for dynamic dimension processing. The application solves the technical problems of insufficient anti-interference performance of a radar seeker in a complex strong interference environment and low target detection precision in the prior art, constrains a fundamental wave by constructing an environmental interference heat map, performs multiple emission and reception under a parallel detection mode and tensor decomposition to screen target signals, and adopts parallel processing of static and dynamic dimensions, so that the technical effects of improving target recognition capability and anti-interference performance, improving radar detection accuracy and reliability are achieved. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0012] Figure 1 A pulse Doppler radar seeker signal processing method flowchart is provided for the embodiments of the application.

[0013] Figure 2 A pulse Doppler radar seeker signal processing system structure diagram is provided for the embodiments of the application.

[0014] Reference signs: heat map construction module 11, target signal group determination module 12, detection result acquisition module 13. DETAILED DESCRIPTION

[0015] The present application provides a pulse Doppler radar seeker signal processing method and system, which solves the technical problems of insufficient anti-interference performance and low target detection precision of the radar seeker in a complex strong interference environment. The environment interference heat map is constructed to constrain the fundamental wave, the multiple emission and reception in the parallel detection mode and the tensor decomposition are used to screen the target signal, and the static and dynamic dimensions are processed in parallel, so as to improve the target recognition ability and anti-interference performance, and improve the radar detection accuracy and reliability.

[0016] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0017] It should be noted that any variation of the terms "comprise" and "have" is intended to cover non-exclusive inclusion, for example, a process, method, system, product or server comprising a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or modules not clearly listed or inherent to the process, method, product or device.

[0018] Embodiment one, as shown in the present application provides a pulse Doppler radar seeker signal processing method, which comprises: Figure 1

[0019] Step S100: Acquire the radar detection environment, construct the heat map by analyzing the environment interference frequency band, perform the wave frequency processing constraint of the detection fundamental wave, and generate the base frequency electromagnetic detection wave.

[0020] In the embodiments of the present application, before starting detection, the radar seeker first performs frequency domain scanning on the target airspace, collects the power spectral density and frequency band occupation of electromagnetic signals in the target airspace, and acquires the radar detection environment.

[0021] Next, real-time spectrum sensing is performed on the radar detection environment to determine the environment interference frequency band. Then, the interference heat map is constructed based on the environment interference frequency band to represent the interference distribution. Then, the wave frequency processing engine in the radar control center is triggered to perform orthogonal fundamental wave matching and interference avoidance frequency modulation processing on the detection fundamental wave, and generate the base frequency electromagnetic detection wave. ​

[0022] Further, the method provided by the application embodiment further comprises:

[0023] The method comprises the following steps: performing real-time spectrum sensing on a radar detection environment to determine an environmental interference frequency band; establishing a heat map based on the interference frequency band; and triggering a wave frequency processing engine deployed in a radar control center to perform orthogonal base wave matching and interference avoidance frequency modulation processing to generate a base frequency electromagnetic detection wave, with the generation of the heat map.

[0024] In the application embodiment, first, the power of echo signals in the working frequency band of a seeker is detected in sections for the current radar detection environment, and each frequency point is monitored in real time by setting a power judgment threshold (for example, the interference judgment threshold is−45 dBm). When the continuous sampling power value of a frequency band is higher than the threshold, the frequency band is determined as an environmental interference frequency band with interference characteristics.

[0025] Then, based on the identified environmental interference frequency band, a two-dimensional data mapping algorithm is applied to coordinate the environmental interference frequency band information according to the frequency (horizontal axis) and power (vertical axis), and map the intensity of each interference frequency band into a corresponding power value. A heat map is generated by using a color mapping technology (for example, red represents strong interference, and blue represents weak interference).

[0026] Subsequently, after the heat map is generated, a wave frequency processing engine deployed in the radar control center is triggered to perform orthogonal base wave matching and interference avoidance frequency modulation processing. In this process, a waveform database is first established, which contains multiple orthogonal base waves and interacts with the wave frequency processing engine. When the wave frequency processing engine is triggered for processing, the wave frequency processing engine matches the base waves in the waveform database according to the generated heat map, and selects the optimal detection base wave. If the matching result is empty, it indicates that the selected optimal detection base wave does not overlap with the interference frequency band, and the optimal detection base wave is directly used as the base frequency electromagnetic detection wave for emission. If the matching result is not empty, the wave frequency processing engine identifies the interference frequency band and performs directional frequency modulation processing, such as frequency hopping or spread spectrum, to adjust the frequency characteristics of the optimal detection base wave, so as to ensure that the generated base frequency electromagnetic detection wave can avoid the interference frequency band, thereby ensuring the effectiveness of the radar signal.

[0027] Further, the method provided by the application embodiment further comprises:

[0028] A waveform database is established, wherein the waveform database is integrated with a plurality of orthogonal basis waves, and the waveform database is interacted with the wave frequency processing engine; the wave frequency processing engine is triggered to match in the waveform database according to the heat map to determine an optimal detection basis wave; the optimal detection basis wave is identified to perform wave frequency matching according to the heat map, if the matching result is empty, the optimal detection basis wave is taken as the base frequency electromagnetic detection wave; if the matching result is not empty, a matching frequency band in the optimal detection basis wave is located, directional frequency modulation processing is performed to determine the base frequency electromagnetic detection wave, wherein the frequency modulation mode at least includes frequency hopping and spread spectrum.

[0029] In the embodiments of the present application, a waveform database is first established, which contains a plurality of orthogonal basis waves. These basis waves are designed according to different radar detection requirements and have different frequency, bandwidth and phase characteristics. Each orthogonal basis wave is an independent signal waveform, which can be orthogonally separated in the same frequency bandwidth to avoid interference. The waveform database is interacted with the wave frequency processing engine, and the wave frequency processing engine can retrieve the most suitable basis wave from the database according to real-time requirements for radar signal transmission.

[0030] After triggering the wave frequency processing engine, matching is performed in the waveform database according to the heat map. Specifically, the heat map reflects the interference intensity in different frequency bands, and the interference intensity is usually distinguished by color depth. The deeper the color, the stronger the interference. According to the heat map, the wave frequency processing engine starts to match the basis wave in the waveform database. The matching process is to compare the interference frequency band in the heat map with the frequency characteristics of the basis wave in the waveform database, and select the optimal detection basis wave with the smallest overlap with the interference frequency band.

[0031] After determining the optimal detection basis wave, the wave frequency processing engine continues to perform wave frequency matching according to the heat map. At this time, the selected optimal detection basis wave is matched and compared with the interference frequency band identified in the heat map to ensure that the basis wave and the interference frequency band do not overlap. If the wave frequency matching result is empty, it means that the selected optimal detection basis wave does not overlap with any interference frequency band, and it is directly taken as the base frequency electromagnetic detection wave for transmission.

[0032] If the result of the wave frequency matching is not empty, it indicates that the selected optimal probe fundamental wave still overlaps with some interference frequency band. At this time, the wave frequency processing engine locates and identifies the specific frequency band where the interference region overlaps with the fundamental wave, and then performs directional frequency modulation processing. In the process of directional frequency modulation processing, frequency modulation methods such as frequency hopping or spread spectrum are used for adjustment. Frequency hopping is to avoid the interference frequency band by quickly switching the signal between multiple frequency bands. For example, if the selected fundamental wave is 9.4 GHz, and this frequency band overlaps with the interference region, the signal frequency is switched from 9.4 GHz to 9.35 GHz or 9.45 GHz to avoid the interference frequency band. Spread spectrum is to expand the bandwidth of the signal so that the signal propagates in a wider frequency band, reducing the power density in the interference frequency band, thereby reducing the overlap with the interference signal. Finally, the signal after directional frequency modulation processing will be used as the new fundamental electromagnetic probe wave, and it is ensured to avoid the interference region.

[0033] Step S200: Deploy a parallel detection mode, perform parallel emission and echo reception of the base frequency electromagnetic probe wave in a time sequence, perform main lobe interference filtering and multi-dimensional tensor decomposition on the received echo signal group, and determine the target signal group, wherein the parallel detection mode includes at least four parallel detections.

[0034] In the embodiments of the present application, when deploying the parallel detection mode, first, the time sequence constraints are set to ensure that the emitted frame frequency signals are organized in a specific time order. Specifically, the first frame frequency wave and the second frame frequency wave are adjacent frame frequencies, and the third frame frequency wave and the fourth frame frequency wave are adjacent frame frequencies. The second frame frequency wave and the third frame frequency wave have a preset time interval, which is used to adjust the detection period and improve the target recognition accuracy. Next, according to these time sequence constraints, the time sequence coding of the parallel detection of the base frequency electromagnetic probe wave is performed, and the parallel detection mode is initialized through this coding process. The mode includes at least four parallel detections, that is, the emission and reception of signals are alternately performed at multiple time points.

[0035] After deploying the parallel detection mode, the base frequency electromagnetic probe wave is subjected to parallel emission and echo reception in a time sequence. Specifically, in each preset time window, the radar alternately emits different probe signals according to the preset time sequence constraints, and simultaneously receives the corresponding echo signals. Each time the signal is emitted, the base frequency electromagnetic probe wave is emitted at the frame frequency specified in the time sequence, and at the same time, the echo signals from different directions and different targets are received in these time intervals, thereby forming multiple echo signal groups at different time points.

[0036] Subsequently, main-lobe interference filtering and multi-dimensional tensor decomposition are performed on the received echo signal groups. In performing main-lobe interference filtering on the received echo signal groups, a joint filter is first constructed by combining spatial information (from the antenna array) and time-domain information (determined by the pulse repetition interval (PRI)). The filter functions to suppress main-lobe interference signals and ensure that only effective target signals are retained. Then, when the antenna array receives the echo signal groups, the joint filter is triggered for processing. In the filtering process, the joint filter takes the undistorted response as the criterion to ensure that the original characteristics of the echo signals are retained as much as possible while the interference is removed. After this processing, the effective signal groups are determined.

[0037] Subsequently, multi-dimensional tensor decomposition is performed. In this process, a first effective signal is first identified from the effective signal groups, which is any one of the effective signal groups. Next, for the first effective signal, tensor decomposition is performed according to the distance dimension, the Doppler dimension, and the angle dimension. Finally, the signals obtained from the tensor decomposition are integrated to form a target signal corresponding to the first effective signal, which is added to the target signal groups. By repeating the foregoing steps for the four effective signals in the effective signal groups, the target signal groups are finally obtained.

[0038] Further, the method provided by the application embodiment further comprises:

[0039] A time sequence constraint is set, wherein the first frame frequency wave and the second frame frequency wave are adjacent frame frequency waves, the third frame frequency wave and the fourth frame frequency wave are adjacent frame frequency waves, and the second frame frequency wave and the third frame frequency wave have a preset time interval; the time sequence coding of the parallel detection of the base frequency electromagnetic detection wave is performed according to the time sequence constraint, and the parallel detection mode is initialized.

[0040] In the application embodiment, first, a time sequence constraint is set, and different frame frequencies are arranged according to a predetermined rule. The first frame frequency wave and the second frame frequency wave are adjacent frame frequency waves, that is, their frequencies are very close (such as 9.4 GHz and 9.41 GHz), to ensure that the signals are transmitted and the echoes are received in continuous time. The third frame frequency wave and the fourth frame frequency wave are adjacent frame frequency waves, that is, their frequencies are different (such as 9.42 GHz and 9.44 GHz), but still within the same frequency range of radar detection, to ensure that multiple frequency bands can be detected at the same time. A preset time interval (such as 10 ms) is set between the second frame frequency wave and the third frame frequency wave, which is used to ensure that there is enough time between signal transmission and echo reception, to avoid signal interference and ensure high-quality echo signal reception.

[0041] Next, according to the time sequence constraint, the time sequence coding of the base frequency electromagnetic probe wave for parallel detection is performed. In this step, the time sequence constraint is converted into actual transmission and reception arrangement, ensuring that each probe signal is transmitted within a specified time window and the echo is received within the corresponding time window. For example, the first frame frequency wave is transmitted within a certain time period, followed by the transmission of the second frame frequency wave, and so on. Each frame frequency signal works independently in different time windows, avoiding signal overlap or interference.

[0042] After the time sequence coding is completed, the initialization of the parallel detection mode is completed, which includes at least four parallel detections, i.e., signal transmission and echo reception are alternately performed in different time windows. When each signal is transmitted, the base frequency electromagnetic probe wave is transmitted according to the preset time sequence and the echo signal is received within the corresponding time window.

[0043] Further, the method provided by the application embodiment further comprises:

[0044] The spatial domain information is an antenna array, and the time domain information is a pulse repetition interval. After the antenna array receives the echo signal group, the joint filter is triggered to perform filtering processing based on the criterion of distortionless response, and an effective signal group is determined.

[0045] In the application embodiment, first, the joint filter is constructed by combining the spatial domain information and the time domain information. The spatial domain information comes from the antenna array, which is composed of multiple array elements, each of which receives echo signals in different directions. By analyzing the spatial domain information of the antenna array, the direction of the echo signal can be determined. The main lobe interference comes from the maximum radiation direction of the antenna, and the filter suppresses the interference signals from the main lobe direction by identifying the direction characteristics of these signals.

[0046] The time domain information comes from the pulse repetition interval (PRI), which is the time interval between radar pulse transmissions, determines the sampling period of the signal and the timing of the echo signal. The time domain information helps the joint filter to determine whether the echo signal comes from the target or the interference source. By analyzing the distribution of the echo signal in the time domain, the filter can identify and reduce the influence of the interference signal on the target signal, especially when the echo signals overlap in time, the filter can effectively distinguish the interference from the target signal.

[0047] When the antenna array receives the set of echo signals, the joint filter triggers and starts performing filtering processing according to the spatial information and the time information. Through adaptive weighting, the joint filter gives lower weights to the interference signals from the main lobe direction, reducing their impact on the effective echo. While the target echo signals from other directions retain higher weights. In addition, the joint filter utilizes time information to strengthen the suppression of interference signals in the time domain. Especially when the signals have timing overlap, the filter effectively suppresses these overlapping signals, ensuring that the target echo signals are preserved.

[0048] When performing filtering processing, the joint filter follows the distortionless response criterion. This criterion ensures that the joint filter removes interference signals while preserving the original frequency, phase, and amplitude characteristics of the target echo signals as much as possible, thereby ensuring the effectiveness and accuracy of the signals. By following the distortionless response criterion, the joint filter maximizes the suppression of interference signals without distorting the target signals.

[0049] After the above steps, the joint filter finally outputs a set of effective signals after interference suppression.

[0050] Further, the method provided by the application embodiment further comprises:

[0051] identifying a first effective signal, wherein the set of effective signals contains four signals, and the first effective signal is any one of the set of effective signals; performing tensor decomposition on the first effective signal in the distance dimension, the Doppler dimension, and the angle dimension to determine a multi-dimensional decomposition signal; and integrating the multi-dimensional decomposition signal as a target signal corresponding to the first effective signal and adding it to the set of target signals.

[0052] In the application embodiment, first, a signal is selected from the set of effective signals as the first effective signal. The set of effective signals contains four signals, which are effective echo signals representing reflections from the target after interference suppression processing. The first effective signal is a signal selected from these effective signals.

[0053] Then the first effective signal is tensor decomposed in distance dimension, Doppler dimension and angle dimension. The distance dimension represents the physical distance between the target and the radar. This dimension is determined by measuring the time of signal propagation. Specifically, after the radar transmits a signal, the signal propagates from the radar to the target and returns, and after receiving the echo signal, the distance of the target is calculated according to the time delay of the echo and the known speed of light. Using the formula distance = signal propagation time x speed of light, the physical distance between the target and the radar can be calculated. The Doppler dimension represents the speed of the target relative to the radar. This dimension determines the relative speed of the target by measuring the frequency shift of the echo signal. According to the Doppler effect, when the target approaches the radar, the frequency of the echo signal increases, and when the target moves away from the radar, the echo frequency decreases. By comparing the frequency difference between the transmitted signal and the received echo signal, the speed of the target can be calculated. The specific calculation method is to compare the frequency change of the echo signal with the known radar signal frequency to obtain the relative speed of the target. The angle dimension represents the direction of the target relative to the radar. This dimension is determined by the phase difference of the signals received by the antenna array. The antenna array is composed of multiple elements, and the relative positions of the elements make the received echo signals have certain phase differences. By analyzing these phase differences, the azimuth and elevation angles of the target can be calculated. The specific calculation method is to use beamforming technology to analyze the phase of the signals received by different elements in the array, and thus calculate the direction of the target relative to the radar.

[0054] Through tensor decomposition, the signals in the distance dimension, Doppler dimension and angle dimension of the first effective signal are independently extracted to obtain multi-dimensional decomposition signals. Each decomposition signal represents the distance, speed and direction of the target, and these signals reflect the independent characteristics of the target in each dimension.

[0055] Finally, the multi-dimensional decomposition signals are integrated into a complete target signal, which contains information such as the position, speed and direction of the target, and is added to the target signal group.

[0056] Further, the method provided by the application embodiment further comprises:

[0057] A first static channel is deployed with neighborhood frame frequency as self-attention constraint and single-frame feature inspection and mutual inspection as underlying logic; a second dynamic channel is deployed with step frame frequency as self-attention constraint of dynamic feature capture; bidirectional side interaction of the first static channel and the second channel is established, and sample-driven training is performed to convergence, serving as the signal processor.

[0058] In the embodiments of the present application, first, the neighborhood frame frequency is used as self-attention constraint to analyze the feature relationship between adjacent time frames by using the self-attention mechanism. The neighborhood frame frequency helps to identify similar signal features in adjacent frames and performs weighted processing on these features to highlight key information. Through the self-attention mechanism, the correlation of the signal between multiple time frames is effectively captured, thereby extracting important features and reducing the influence of irrelevant parts. Then, single-frame feature detection and mutual verification are used as the bottom logic to evaluate each frame of signal. Single-frame feature detection independently checks the signal features of each frame to ensure that the quality of each frame of signal meets the predetermined standard. Through this process, low-quality or invalid signal frames are eliminated. Mutual verification verifies the consistency of the features between multiple frames in time to confirm the stability of the signal and ensure that the target signal is consistent in the entire time sequence.

[0059] After these processes are completed, the first static channel is deployed, which focuses on extracting static features in the signal. Static features refer to features that remain stable or change slowly over a long period of time, usually related to the long-term existence state or position of the target. For example, if the target has a small change in position over multiple time frames, the extracted signal features are static features. Through the self-attention constraint of the neighborhood frame frequency, the first static channel can extract these stable features to ensure that the long-term information of the target is accurately extracted and represented.

[0060] Next, the second dynamic channel is deployed, which focuses on capturing dynamic features in the signal and uses the step frame frequency as a self-attention constraint for dynamic feature capture. The step frame frequency reflects the rapidly changing part of the signal, usually indicating the instantaneous dynamic behavior of the target, such as speed change or direction adjustment. Through the self-attention mechanism, the second dynamic channel can accurately identify these rapidly changing signal features and ensure that important dynamic features are effectively captured during the mutation process of the signal. In this way, the dynamic channel can quickly respond to the instantaneous changes in target behavior and provide accurate dynamic descriptions.

[0061] After the deployment of the first static channel and the second dynamic channel is completed, a bidirectional side interaction between the two is established. This interaction mechanism enables the static channel and the dynamic channel to share information and cooperate with each other. The static channel provides the long-term stable features of the target, while the dynamic channel supplements and strengthens the changing features of the target in a short period of time. Through bidirectional interaction, static and dynamic information is effectively combined, enhancing the accuracy of target recognition and tracking.

[0062] Finally, the channel parameters are optimized by sample-driven training. By using a large number of labeled signal samples, these sample data reflect the behavior and characteristics of different targets in different scenarios. Through repeated training, the parameters of the channel are continuously adjusted according to these sample data, so as to ensure that the interaction mode of the static channel and the dynamic channel can maximize the extraction of target characteristics. The training process continues until convergence, and finally forms a signal processor that can accurately process target signals in complex environments.

[0063] Step S300: introducing the target signal group into the signal processor, performing parallel processing of static dimension and dynamic dimension and result fitting, and outputting radar detection results, wherein the static dimension processing is performed on continuous frame signals, and the dynamic dimension processing is performed on step frame signals.

[0064] In the embodiments of the present application, the target signal group is first introduced into the signal processor for processing. Then, parallel processing of static dimension and dynamic dimension is performed. The static dimension processing extracts stable characteristics in the target signal by analyzing continuous frame signals, which are related to the long-term existence state or position of the target and reflect the static behavior of the target. The first static channel analyzes the adjacent frame frequency signal pairs in the signal to perform signal characteristic detection and mutual verification, ensures that the extracted static characteristics are accurate, and finally obtains the first detection result.

[0065] At the same time, the dynamic dimension processing extracts dynamic characteristics of the target through step frame signals, especially the instantaneous changes or rapid movements of the target. The second dynamic channel analyzes the step frame frequency signal pairs in the signal to identify the rapid behavior or change of the target through signal characteristic capture, and finally obtains the second detection result.

[0066] Finally, the first detection result and the second detection result are integrated to form a comprehensive radar detection result, which combines the static and dynamic information of the target to ensure comprehensive identification and tracking of the target.

[0067] Further, in the method provided by the embodiments of the present application, performing parallel processing of static dimension and dynamic dimension and result fitting, and outputting radar detection results further includes:

[0068] According to the first static channel, the signal pairs of adjacent frame frequencies in the target signal group are located, signal characteristic detection and mutual verification are performed to determine the first detection result; according to the second dynamic channel, the signal pairs of step frame frequencies in the target signal group are located, signal characteristic capture is performed to determine the second detection result; and the first detection result and the second detection result are integrated as the radar detection result.

[0069] In the embodiments of the present application, according to the first static channel, the neighborhood frame frequency signal pairs in the target signal group are first located. Neighborhood frame frequency refers to the frequency characteristics similar or consistent between adjacent time frames in the frequency domain of the signal, which reflects the stability or continuity of the target in the time period. Through signal feature detection, each frame signal is evaluated to check its frequency, amplitude, and phase characteristics, etc., to ensure that the quality of these signals meets the predetermined standard. The mutual verification step verifies the consistency of the signals in time by comparing the signal characteristics in multiple time frames, to ensure the stability and consistency of the signals between different time points. After these steps, the first detection result is determined, which includes the static characteristics of the target, such as the stability of the target position or the continuous state of the target in a longer period of time.

[0070] Subsequently, according to the second dynamic channel, the step frame frequency signal pairs in the target signal group are located. Step frame frequency signals reflect the rapid changes of the target signal in a short period of time, which usually represent the dynamic behavior of the target, such as the change of the speed, acceleration, or direction of the target. Through signal feature capture, these rapidly changing signals are identified and extracted, so as to capture the dynamic characteristics of the target. Through this method, the second detection result is determined, which reflects the instantaneous dynamic characteristics of the target, such as the speed, acceleration, or direction of the target.

[0071] Finally, the first detection result and the second detection result are integrated together to form the final radar detection result.

[0072] Further, in the method provided by the embodiments of the present application, after outputting the radar detection result, the method further comprises:

[0073] identifying the radar detection result to determine a target orientation vector; storing the target orientation vector to a guidance database embedded in a radar central control to perform guidance driving assistance of a lower node.

[0074] In the embodiments of the present application, first, the target orientation vector is determined by analyzing the radar detection result. The radar detection result provides the static and dynamic characteristics of the target, such as the position, speed, and direction of the target. These data are converted into the target orientation vector through coordinate conversion method, i.e. the position and motion direction of the target relative to the radar. The target orientation vector is a three-dimensional vector, which contains the velocity vector and direction information of the target, and is used to accurately describe the motion trajectory and current state of the target. For example, when the radar detects the change of the speed, acceleration, or direction of the target, the orientation vector of the target is calculated according to these change data, so as to obtain the accurate position and motion trajectory of the target in space.

[0075] Next, the target orientation vector is stored in a guidance database. The guidance database is used to store all dynamic data about the target, including the real-time motion state and orientation information of the target. During storage, the target orientation vector is saved in the relevant table or record of the database, and it is ensured that these information can be quickly and accurately called in subsequent steps. In this way, the database can provide real-time target orientation data. For example, if the target changes direction or speed, the new orientation vector will be stored in the database for subsequent steps.

[0076] Finally, based on the target orientation vector stored in the guidance database, relevant information is passed to the lower node to perform guidance driving assistance. Guidance driving assistance refers to providing the lower node with information about the target's motion direction and speed based on the target orientation vector, which guides the lower node to adjust its action path. Specifically, the relevant information includes the target's position, speed, and motion direction, which are transmitted to the lower device through the calculated orientation vector to adjust the device's control instructions, enabling it to accurately track the target. For example, in a tracking system, through the target's motion trajectory data, the lower node will adjust its execution action according to the orientation vector to ensure continuous tracking and positioning of the target.

[0077] In the embodiments of the present application, as described above, the embodiments of the present application have at least the following technical effects:

[0078] The present application acquires a radar detection environment, constructs a heat map by analyzing the environmental interference frequency band, performs wave frequency processing constraint of the detection fundamental wave, generates a fundamental frequency electromagnetic detection wave, deploys a parallel detection mode, performs parallel emission and echo reception under a time sequence on the fundamental frequency electromagnetic detection wave, performs main lobe interference filtering and multi-dimensional tensor decomposition on the received echo signal group, determines a target signal group, wherein the parallel detection mode contains at least four times of parallel detection; the target signal group is imported into a signal processor, parallel processing of static dimension and dynamic dimension and result fitting are performed, and a radar detection result is output, wherein continuous frame signals are used for static dimension processing, and step frame signals are used for dynamic dimension processing. The present application solves the technical problems of insufficient anti-interference performance of the radar seeker in a complex strong interference environment and low target detection precision in the prior art, selects a target signal through construction of an environmental interference heat map for fundamental wave constraint, multiple emission and reception under a parallel detection mode and tensor decomposition, and adopts parallel processing of static and dynamic dimensions, so that the technical effects of improving target recognition capability and anti-interference performance, improving radar detection accuracy and reliability are achieved.

[0079] Embodiment two, based on the same inventive concept as the pulse Doppler radar seeker signal processing method in the foregoing embodiments, such as Figure 2As shown, the present application provides a pulse Doppler radar seeker signal processing system, and the system and method embodiments in the present application are based on the same inventive concept. The system comprises:

[0080] A heat map construction module 11 is configured to acquire a radar detection environment, construct a heat map by analyzing an environment interference frequency band, perform wave frequency processing constraint on a detection fundamental wave, and generate a fundamental frequency electromagnetic detection wave. A target signal group determination module 12 is configured to deploy a parallel detection mode, perform parallel transmission and echo reception under a time sequence on the fundamental frequency electromagnetic detection wave, perform main lobe interference filtering and multi-dimensional tensor decomposition on a received echo signal group, and determine a target signal group. The parallel detection mode contains at least four times of parallel detection. A detection result acquisition module 13 is configured to import the target signal group into a signal processor, perform parallel processing of static dimensions and dynamic dimensions and result fitting, and output a radar detection result. The static dimension processing is performed on a continuous frame signal, and the dynamic dimension processing is performed on a step frame signal.

[0081] Further, the system is also configured to implement the following functions:

[0082] Real-time spectrum sensing is performed on a radar detection environment to determine an environment interference frequency band. A heat map based on the interference frequency band is established. With the generation of the heat map, a wave frequency processing engine deployed in a radar central controller is triggered to perform orthogonal fundamental wave matching and interference avoidance frequency modulation processing, and a fundamental frequency electromagnetic detection wave is generated.

[0083] Further, the system is also configured to implement the following functions:

[0084] A waveform database is established, wherein the waveform database integrates a plurality of orthogonal fundamental waves, and the waveform database and the wave frequency processing engine are interacted. The wave frequency processing engine is triggered to perform matching in the waveform database according to the heat map to determine an optimal detection fundamental wave. The optimal detection fundamental wave is identified, and wave frequency matching is performed according to the heat map. If the matching result is empty, the optimal detection fundamental wave is taken as the fundamental frequency electromagnetic detection wave. If the matching result is not empty, the matching frequency band in the optimal detection fundamental wave is located, directional frequency modulation processing is performed, and the fundamental frequency electromagnetic detection wave is determined. The frequency modulation mode at least contains frequency hopping and spread spectrum.

[0085] Further, the system is also configured to implement the following functions:

[0086] A time sequence constraint is set, wherein the first frame frequency wave and the second frame frequency wave are adjacent frame frequency waves, the third frame frequency wave and the fourth frame frequency wave are adjacent frame frequency waves, and the second frame frequency wave and the third frame frequency wave have a preset time interval. According to the time sequence constraint, the base frequency electromagnetic detection wave is time sequence coded for parallel detection, and the parallel detection mode is initialized.

[0087] Further, the system is also used to realize the following functions:

[0088] The spatial domain information is an antenna array, and the time domain information is a pulse repetition interval. After the antenna array receives the echo signal group, the joint filter is triggered to perform filtering processing based on the criterion of distortionless response to determine an effective signal group.

[0089] Further, the system is also used to realize the following functions:

[0090] The effective signal group contains four, and the first effective signal is any one in the effective signal group. The first effective signal is executed in the distance dimension, the Doppler dimension and the angle dimension, and the multi-dimensional decomposition signal is determined. The multi-dimensional decomposition signal is integrated as the target signal corresponding to the first effective signal and added to the target signal group.

[0091] Further, the system is also used to realize the following functions:

[0092] The first static channel is deployed with the neighborhood frame frequency as the self-attention constraint and the single-frame feature detection and mutual test as the bottom logic. The second dynamic channel is deployed with the dynamic feature capture of the step frame frequency as the self-attention constraint. The bidirectional side interaction of the first static channel and the second channel is established, and the sample-driven training is trained to convergence as the signal processor.

[0093] Further, the system is also used to realize the following functions:

[0094] According to the first static channel, the signal pair of the neighborhood frame frequency in the target signal group is located, and the first detection result is determined by performing signal feature detection and mutual test. According to the second dynamic channel, the signal pair of the step frame frequency in the target signal group is located, and the second detection result is determined by performing signal feature capture. The first detection result and the second detection result are integrated as the radar detection result.

[0095] Further, the system is also used to realize the following functions:

[0096] The radar detection result is identified to determine a target direction vector. The target direction vector is stored in a guidance database embedded in a radar central control to perform guidance and driving assistance of a lower node.

[0097] It should be noted that the above-mentioned embodiment sequence of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the above describes a specific embodiment of the present application. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0098] The above only describes the preferred embodiments of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0099] The present application is only an exemplary description of the present application, and is considered to cover any and all modifications, changes, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art can make various modifications and changes to the present application without departing from the scope of the present application. Thus, if these modifications and changes of the present application belong to the scope of the present application and its equivalents, the present application intends to include these modifications and changes.

Claims

1. A method of signal processing for a pulse Doppler radar seeker, characterized in that, The method comprises: Acquiring radar detection environment, constructing heat map by analyzing environment interference frequency band, performing wave frequency processing constraint of detection fundamental wave, generating fundamental frequency electromagnetic detection wave; Deploying parallel detection mode, performing parallel emission and echo reception of the fundamental frequency electromagnetic detection wave under time sequence, performing main lobe interference filtering and multi-dimensional tensor decomposition on received echo signal group, determining target signal group, wherein the parallel detection mode contains at least four times of parallel detection; The target signal group is introduced into a signal processor to perform parallel processing of static dimension and dynamic dimension and result fitting, and radar detection result is output, wherein continuous frame signal is used for static dimension processing, and step frame signal is used for dynamic dimension processing.

2. The pulsed Doppler radar seeker signal processing method of claim 1 wherein, Constructing heat map by analyzing environment interference frequency band, performing wave frequency processing constraint of detection fundamental wave, generating fundamental frequency electromagnetic detection wave, comprising: Real-time spectrum sensing is performed on the radar detection environment to determine the environment interference frequency band; A heat map based on the interference frequency band is established; With the generation of the heat map, a wave frequency processing engine deployed in the radar central control is triggered to perform orthogonal fundamental wave matching and interference avoidance frequency modulation processing to generate a fundamental frequency electromagnetic detection wave.

3. The method of processing pulsed Doppler radar homing head signals as set forth in claim 2, wherein, Performing orthogonal fundamental wave matching and interference avoidance frequency modulation processing, comprising: A waveform database is established, wherein the waveform database integrates multiple orthogonal fundamental waves, and the waveform database and the wave frequency processing engine have interaction; The wave frequency processing engine is triggered to match in the waveform database according to the heat map to determine the optimal detection fundamental wave; The optimal detection fundamental wave is identified, and wave frequency matching is performed according to the heat map. If the matching result is empty, the optimal detection fundamental wave is used as the fundamental frequency electromagnetic detection wave; If the matching result is not empty, the matching frequency band in the optimal detection fundamental wave is located, directional frequency modulation processing is performed, and the fundamental frequency electromagnetic detection wave is determined, wherein the frequency modulation mode at least contains frequency hopping and spread spectrum.

4. The method of processing pulsed Doppler radar seeker signals as recited in claim 1, wherein, Deploying parallel detection mode, comprising: Setting time sequence constraint, wherein the first frame frequency wave and the second frame frequency wave are adjacent frame frequency waves, the third frame frequency wave and the fourth frame frequency wave are adjacent frame frequency waves, and the second frame frequency wave and the third frame frequency wave have a preset time interval; According to the time sequence constraint, the base frequency electromagnetic detection wave is time sequence coded for parallel detection, and the parallel detection mode is initialized.

5. The method of processing pulsed Doppler radar homing head signals as set forth in claim 4, wherein, Performing main lobe interference filtering on the received echo signal group, comprising: Combined with space domain information and time domain information, a joint filter is constructed, wherein the joint filter is used to suppress main lobe interference, the space domain information is an antenna array, and the time domain information is a pulse repetition interval; After the antenna array receives the echo signal group, the joint filter is triggered to perform filtering processing based on the criterion of distortionless response to determine an effective signal group.

6. The method of processing pulsed Doppler radar homing head signals as set forth in claim 5, wherein, Performing multi-dimensional tensor decomposition to determine the target signal group, comprising: Identifying a first effective signal, wherein the effective signal group contains four, and the first effective signal is any one in the effective signal group; Performing tensor decomposition on the first effective signal in distance dimension, Doppler dimension and angle dimension to determine a multi-dimensional decomposition signal; Integrating the multi-dimensional decomposition signal as the target signal corresponding to the first effective signal and adding it to the target signal group.

7. The method of processing pulsed Doppler radar seeker signals as recited in claim 1, wherein, Before the target signal group is introduced into the signal processor, the construction of the signal processor includes: deploying a first static channel with neighborhood frame frequency as self-attention constraint and single-frame feature inspection and mutual inspection as underlying logic; deploying a second dynamic channel with step frame frequency as self-attention constraint for dynamic feature capture; establishing bidirectional side interaction of the first static channel and the second channel, and training to convergence through sample driving, as the signal processor.

8. The method of processing pulsed Doppler radar homing head signals as defined in claim 7, wherein, performing parallel processing of static dimension and dynamic dimension and result fitting, and outputting radar detection results, including: locating signal pairs of neighborhood frame frequency in the target signal group according to the first static channel, and determining first detection results by performing signal feature inspection and mutual inspection; locating signal pairs of step frame frequency in the target signal group according to the second dynamic channel, and determining second detection results by performing signal feature capture; integrating the first detection results and the second detection results as the radar detection results.

9. The method of pulse Doppler radar seeker signal processing of claim 1 wherein, After outputting the radar detection results, including: identifying the radar detection results to determine a target orientation vector; storing the target orientation vector to a guidance database embedded in a radar central control to perform guidance driving assistance of a lower node.

10. A signal processing system for a pulse Doppler radar seeker, characterized in that The system is used to perform the pulse Doppler radar seeker signal processing method as claimed in any one of claims 1-9, and the system includes: a heat map construction module for acquiring a radar detection environment, constructing a heat map by analyzing environment interference frequency bands, performing wave frequency processing constraint of a detection fundamental wave, and generating a fundamental frequency electromagnetic detection wave; a target signal group determination module for deploying a parallel detection mode, performing parallel emission and echo reception under time series on the fundamental frequency electromagnetic detection wave, performing main lobe interference filtering and multi-dimensional tensor decomposition on the received echo signal group, and determining a target signal group, wherein the parallel detection mode contains at least four times of parallel detection; a detection result acquisition module for introducing the target signal group into a signal processor, performing parallel processing of static dimension and dynamic dimension and result fitting, and outputting radar detection results, wherein continuous frame signals are used for static dimension processing, and step frame signals are used for dynamic dimension processing.

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