Method and device for simulating slant plane airborne strip echo for assisting autofocus processing

Abstract

The present invention discloses a method and device for simulating the echo of an inclined plane airborne strip for assisting autofocus processing, which relates to the technical field of echo simulation, and includes: planning a strip trajectory and a mapping grid for the relative detection scenario between a radar system and a mapping strip; driving the radar system to perform strip dynamic detection and echo reception with the strip trajectory and the mapping grid to determine grid echo signals; performing two-dimensional matched filtering based on signal spectrum matching and phase residual error compensation based on gradient autofocus on the grid echo signals to determine effective echo grids, where the phase residual error is the residual error after spectrum filtering; connecting to a visualization simulation platform to perform simulation visualization on the effective echo grids. The present invention solves the technical problems in the prior art that it is difficult for an airborne radar to accurately simulate the echo response in a non-horizontal mapping scenario and lacks an effective error compensation and simulation visualization mechanism, and achieves the technical effect of improving the echo simulation accuracy in an inclined plane detection scenario.

Description

Technical Field

[0001] The present invention relates to the technical field of echo simulation, and particularly to an oblique plane airborne strip echo simulation method and device for assisting autofocus processing. Background Art

[0002] Currently, most of the airborne radar echo simulation technologies are designed based on horizontal mapping scenarios, and it is difficult to adapt to the oblique plane mapping conditions where there is an inclination angle between the strip trajectory and the mapping area. In this case, during the strip detection process of the radar system, due to the dynamic changes of the slant range and azimuth, it is difficult to accurately simulate the actual echo signal, and spectral matching errors and phase distortions are likely to occur. At the same time, there is a lack of error compensation means and supporting simulation visualization mechanisms for such non-horizontal scenarios, making it difficult to meet the radar simulation application requirements under complex terrain of the inclined plane. Summary of the Invention

[0003] The present application provides an oblique plane airborne strip echo simulation method and device for assisting autofocus processing, which are used to solve the technical problems that in the prior art, it is difficult for an airborne radar to accurately simulate echo responses in non-horizontal mapping scenarios and there is a lack of effective error compensation and simulation visualization mechanisms.

[0004] In view of the above problems, the present application provides an oblique plane airborne strip echo simulation method and device for assisting autofocus processing.

[0005] In the first aspect of the present application, an oblique plane airborne strip echo simulation method for assisting autofocus processing is provided. The method includes:

[0006] For the relative detection scenario between the radar system and the mapping strip, plan the strip trajectory and mapping grid. Among them, the radar system performs oblique plane strip detection by airborne means; drive the radar system to perform strip dynamic detection and echo reception with the strip trajectory and the mapping grid to determine the grid echo signal; introduce grid resolution parameters, perform two-dimensional matched filtering based on signal spectrum matching and phase residual error compensation based on gradient autofocus on the grid echo signal to determine the effective echo grid, where the grid resolution parameters include the instantaneous slant range and instantaneous azimuth from the radar emission point to the beam center, and the phase residual error is the residual error after spectral filtering; connect to the visualization simulation platform to perform simulation visualization on the effective echo grid.

[0007] In the second aspect of the present application, an electronic device is provided, including: a memory for storing executable instructions; a processor for implementing the oblique plane airborne strip echo simulation method for assisting autofocus processing provided by the present application when executing the executable instructions stored in the memory.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] In view of the relative detection scenario between a radar system and a mapping strip, this application plans strip trajectories and mapping grids. Among them, the radar system performs inclined plane strip detection in an airborne manner; using the strip trajectories and the mapping grids, the radar system is driven to perform strip dynamic detection and echo reception to determine grid echo signals; introducing grid resolution parameters, two-dimensional matched filtering based on signal spectrum matching and phase residual error compensation based on gradient autofocus are performed on the grid echo signals to determine effective echo grids, where the grid resolution parameters include the instantaneous slant range and instantaneous azimuth from the radar emission point to the beam center, and the phase residual error is the residual error after spectrum filtering; connecting to a visualization simulation platform to perform simulation visualization on the effective echo grids. The present invention solves the technical problems in the prior art that it is difficult for airborne radars to accurately simulate echo responses in non-horizontal mapping scenarios and lack effective error compensation and simulation visualization mechanisms. Through the combined driving of strip trajectories and mapping grids, the combination of spectrum matching filtering and gradient phase compensation, and integrating a simulation visualization platform, the technical effect of improving the echo simulation accuracy in inclined plane detection scenarios is achieved. Description of the Drawings

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0011] Figure 1 It is a schematic flow chart of the inclined plane airborne strip echo simulation method for auxiliary autofocus processing provided by the embodiments of this application;

[0012] Figure 2 It is a schematic structural diagram of an exemplary electronic device of this application.

[0013] Description of the reference numerals: Bus 300, Receiver 301, Processor 302, Transmitter 303, Memory 304, Bus Interface 305. Detailed Embodiments

[0014] By providing an inclined plane airborne strip echo simulation method and device with auxiliary autofocus processing, this application aims to solve the technical problems in the prior art that it is difficult for airborne radars to accurately simulate echo responses in non-horizontal mapping scenarios and lack effective error compensation and simulation visualization mechanisms. Through the combined driving of strip trajectories and mapping grids, the combination of spectrum matching filtering and gradient phase compensation, and integrating a simulation visualization platform, the technical effect of improving the echo simulation accuracy in inclined plane detection scenarios is achieved.

[0015] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the scope of protection of the present application.

[0016] It should be noted that any variations of the terms "comprising" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0017] Embodiment 1, as Figure 1 shown, the present application provides an oblique-plane airborne strip echo simulation method for assisting autofocus processing, and the method includes:

[0018] Step S100: For the relative detection scenario between the radar system and the mapping strip, plan the strip trajectory and mapping grid, where the radar system performs oblique-plane strip detection in an airborne manner.

[0019] In the embodiments of the present application, for the relative detection scenario between the radar system and the mapping strip, first, an attitude solution method is used to obtain attitude parameters such as the pitch angle, heading angle, and roll angle of the radar during the detection process, and in combination with the spatial position of the mapping strip, the spatial angular relationship between the radar beam and the mapping area is determined to construct a squint observation geometry.

[0020] Based on this geometric relationship, using the strip trajectory planning method, according to parameters such as the radar beam width, pulse repetition frequency, detection altitude, and azimuth resolution, the ground coverage range of the radar under squint conditions is calculated, thereby generating a continuous strip scanning path. Subsequently, in combination with the coverage range and resolution requirements of the mapping area, a regular grid division method is used to divide the mapping strip into two-dimensional grid cells, and each grid is used to carry the subsequent echo signal data. During the entire detection process, the radar system flies along the planned strip trajectory in an airborne manner, dynamically adjusts the beam pointing, and realizes strip-shaped continuous detection of the mapping grid under non-horizontal conditions, providing a spatial structure basis for high-precision radar simulation in an oblique-plane scenario.

[0021] Further, the method provided by the embodiments of the application further includes:

[0022] The mapping scenario based on the oblique-plane strip includes a first scenario and a second scenario, where the first scenario is that the strip trajectory is horizontally parallel to the mapping strip and there is a vertical inclination angle, and the second scenario is that there are horizontal and vertical inclination angles between the strip trajectory and the mapping strip.

[0023] In the embodiments of the present application, based on the mapping scenario of the inclined plane strip, in order to clarify the spatial relationship between the strip trajectory and the mapping band, it is divided into two scenarios. One is the scenario with only a vertical inclination angle, and the other is the composite scenario with both a horizontal inclination angle and a vertical inclination angle.

[0024] When identifying the mapping scenario, first, an attitude solution method is used to identify the spatial attitude of the radar system. By using the fused data of the inertial navigation system (INS) and the global positioning system (GPS), the current pitch angle, heading angle, and flight altitude of the radar are obtained. These parameters reflect the projection direction of the radar beam in three-dimensional space.

[0025] Then, an elevation modeling method is used to obtain the terrain height information of the mapping band area. Common means include the digital elevation model (DEM) or the surface model generated by lidar (LiDAR). The top-down direction of the radar is superimposed and analyzed with the terrain model, and the vertical angle between the radar emission point and the surface of the mapping band is calculated. If this angle is non-zero and the strip trajectory is consistent with the main axis direction of the mapping band in the horizontal projection direction, it can be determined as the first scenario, that is, only a vertical inclination angle exists.

[0026] Then, to identify whether there is a horizontal inclination angle, a spatial projection angle analysis method is adopted to calculate the included angle between the heading vector of the radar and the direction vector of the main axis of the mapping band in the two-dimensional plane. This operation is carried out in the geographical coordinate system. For example, the radar emission direction is projected in the WGS-84 coordinate system, and the vector included angle with the mapping band coordinates is calculated. If there is a significant included angle (such as >5°), it means that the strip trajectory is not parallel to the mapping band direction, which is the second scenario, with both horizontal and vertical inclination angles. For example, if the radar pitch angle is 15° and the heading angle is 70°, while the main axis direction of the mapping band is due north (0°), the heading offset is 70°, indicating that the strip trajectory deviates from the mapping band axis. Combining the pitch angle information, this scenario can be determined as the second scenario.

[0027] Step S200: Drive the radar system to perform strip dynamic detection and echo reception with the strip trajectory and the mapping grid, and determine the grid echo signal.

[0028] In the embodiments of the present application, during the dynamic detection of strips, based on the joint control of the strip trajectory and the mapping grid, a refined beam control strategy is constructed to drive the radar system to complete the acquisition of echo signals. Specifically, taking the center of the mapping grid as the main pointing reference of the radar beam, the first fixed-point planning is executed to determine the beam center position corresponding to each grid; at the same time, an equidistant ring greater than or equal to the size of the mapping grid is used as the beam action range constraint, and the second range planning is executed to limit the effective coverage area of the radar. Combining the relative motion relationship between the strip trajectory and the mapping grid in space, analyzing the strip motion state, and accordingly determining the control parameters of the radar, including specific azimuth parameters and beam parameters, to guide the pointing, width, and scanning rate of the radar beam. Finally, under the guidance of the strip trajectory, the radar system realizes adaptive beam control based on the above parameters, continuously detects each mapping grid unit under the oblique plane condition, and receives the corresponding grid echo signals to complete the dynamic strip detection task.

[0029] Further, in the method provided by the application embodiments, driving the radar system with the strip trajectory and the mapping grid further includes:

[0030] Taking the grid center as the radar beam center to determine the first fixed-point planning; taking the equidistant ring as the range constraint to determine the second range planning, where the equidistant ring is greater than or equal to the size of the mapping grid; according to the first fixed-point planning and the second range planning, based on the strip motion state of the radar system and the mapping grid under the strip trajectory, determining the radar parameters, where the radar parameters include azimuth parameters and beam parameters; driving the radar system adaptively with the strip motion through the radar parameters.

[0031] In the embodiments of the present application, first, the grid center matching method is adopted. Taking the center coordinates of each mapping grid as the target points, the first fixed-point planning is executed. This process determines the spatial position that the current radar beam should accurately point to by converting the grid center coordinates to the radar working coordinate system and calculating the corresponding pitch angle and azimuth angle.

[0032] Then, the beam action range constraint method is used. An equidistant ring is set around the above grid center for the second range planning. This equidistant ring is a circular area with the grid center as the center and a radius greater than or equal to the grid side length, which is used to limit the tolerance offset range of the radar beam around the target point. By calculating the radar depression angle and the working distance and combining the detection accuracy requirements, the coverage radius corresponding to the minimum beam size is selected to ensure that the beam can still effectively hit the target grid during dynamic offset.

[0033] Based on the first fixed point and the second range planning, combined with the continuous flight of the radar system along the strip trajectory, the strip motion states between the radar and each grid are obtained, including information such as instantaneous slant range, pitch change, beam incident angle, and platform speed. The track dynamic calculation method is used to analyze in real time the attitude of the radar at different flight times and the spatial position relationship with the relative mapping grid, so as to capture the angle and distance changes brought by the trajectory.

[0034] Based on the above position relationship and planning constraints, a set of radar parameters for driving the radar are determined, including azimuth parameters (such as azimuth angle, pitch angle) and beam parameters (such as beam width, pointing adjustment rate). These parameters are accurately calculated to indicate how the radar beam should be continuously adjusted as the platform moves to match the changing state of each grid.

[0035] Finally, the beam adaptive control method is called, and the resolved radar parameters are input into the control system to drive the dynamic adjustment of the radar beam, realizing continuous coverage of each mapping grid. During the operation of the radar system, the beam center continuously changes under the guidance of the strip trajectory, always remaining within the first fixed point planning range and being restricted by the equidistant ring set by the second range planning, achieving high-density and high-precision echo reception of the target area and completing the stable acquisition of grid-level echo signals.

[0036] Furthermore, in the method provided by the application embodiment, based on the strip motion states of the radar system and the mapping grid under the strip trajectory, determining the radar parameters further includes:

[0037] The radar system is composed of a phased radar array; based on the strip trajectory, the co-frequency detection grids under strip motion are determined, where the instantaneous slant range and instantaneous azimuth of the co-frequency detection grids are the same or different; according to the co-frequency detection grids, the radar parameter deployment is carried out on the phased radar array.

[0038] In the embodiment of the present application, the radar system is composed of a phased radar array and, based on the strip trajectory, completes the identification of the co-frequency detection grids and the radar parameter deployment through a series of steps.

[0039] Specifically, first, based on the planned strip trajectory, combined with parameters such as the flight speed, transmitted beam width, and pulse repetition frequency (PRF) of the radar system, the strip trajectory is divided into time segments using the time-sequence positioning method. For each time point, the line-of-sight projection method is used to calculate the position and attitude (pitch angle, heading angle) of the current radar in three-dimensional space, and the projection area of the radar beam on the ground is mapped onto the surveying grid, thereby identifying the co-frequency detection grids that can be irradiated by the radar beam at that moment. For example, if the radar is currently at a height of 1000 meters above the ground, the beam depression angle is 20°, and the main lobe width is 6°, then its projection width on the ground is approximately 2×1000×tan(6° / 2)≈105 meters. In the surveying area, any grid whose center point falls within this 105-meter range and is within the current operating frequency bandwidth of the radar is included in the co-frequency detection grid set.

[0040] Next, for each identified co-frequency detection grid, the slant range and azimuth calculation method is used to separately solve the spatial distance (i.e., the instantaneous slant range) and spatial angle (i.e., the instantaneous azimuth) from the center of the radar system array plane to the center of the grid. This calculation is based on the three-dimensional vector difference in the radar working coordinate system and is combined with geographical coordinate transformation. For example, if a certain grid is directly in front of the radar beam axis, its azimuth difference is 0°; if it deviates within 3° to the left or right of the main axis, it can still be regarded as the same direction.

[0041] Subsequently, the direction consistency judgment method is used to perform clustering judgment on the co-frequency detection grids. If the instantaneous slant range differences of multiple grids are less than the set tolerance (such as ±10 meters) and the azimuth differences are within the main lobe coverage range (such as ±3°), they can be determined as grids with consistent directions and can be irradiated by a single beam; otherwise, multiple beams in different directions need to be deployed. For the sets of grids with consistent and inconsistent directions, the beam control parameter calculation method is used respectively to generate the control parameters of the radar array. These parameters include azimuth parameters (main lobe pointing angle, pitch angle), beam parameters (array spacing, phase control accuracy, beam width), and element control instructions (the phase difference Δφ to be applied to each array element). For example, if a target grid deviates 2° from the main axis, the transmission phase of each antenna element in the array must be adjusted to the delay amount Δφ=(2πd / λ)·sin(2°) that satisfies wavefront coherence, where d is the element spacing and λ is the wavelength.

[0042] Finally, the array control instruction deployment method is used to load the above parameters into the phased radar array control module in real time to complete the rapid adjustment of the beam direction. For grids with consistent directions, unified beam parameters are deployed; for grids with inconsistent directions, beam switching is completed in sequence or in parallel to achieve rapid polling irradiation of multiple targets.

[0043] Furthermore, in the method provided by the application embodiment, after determining the grid echo signal, it further includes:

[0044] Receive the grid echo signal, perform grid size cutting based on the equidistant ring, and determine the equidistant grid; perform relative distribution stitching of the equidistant grid based on the mapping grid to determine the echo grid; perform identification clustering on the echo grid based on the grid resolution parameter, and label the grid clustering label.

[0045] In the embodiment of the present application, after receiving the grid echo signal, first perform grid size cutting based on the equidistant ring. This step screens the effective echo area by setting an equidistant ring. Specifically, the equidistant ring is centered on the center of the mapping grid, and a radius range is set. The radius is greater than or equal to the grid size, which is used to define the effective signal area. For each received echo signal, the radar system checks whether the signal is within this equidistant ring. If it is within the range, the signal is retained; if it exceeds the range, the signal is considered an invalid signal and is removed. By this method, the radar system avoids receiving too many invalid edge or weak signals in the received echo signals, and thus only retains high-quality echo data. These effective signals form an equidistant grid, representing the effective echo area detected by the radar in this area.

[0046] Next, perform relative distribution stitching of the obtained equidistant grid based on the mapping grid. In this process, the radar system spatially stitches the echo signals of each grid according to the coordinate positions of the mapping grid. First, align the center coordinates of each equidistant grid with the coordinate system of the mapping grid, and then stitch these grids according to the predetermined grid layout method through a coordinate transformation algorithm. For example, if the area scanned by the radar is divided into multiple grids, and each grid contains a segment of echo signal, after stitching, each grid combines with the adjacent grid to form a continuous echo area. This stitching process not only ensures the spatial continuity of the data, but also ensures that the measurement accuracy between different grids is not lost, thereby obtaining a complete and continuous echo grid.

[0047] Finally, based on the grid resolution parameters, the echo grid is identified and clustered. In this process, the radar system analyzes multiple characteristic parameters of the echo grid, mainly including the instantaneous slant range (i.e., the real-time distance between the radar and the echo target), the instantaneous azimuth (i.e., the angle between the radar beam direction and the grid), and the signal intensity, etc. By comprehensively analyzing these parameters, it is judged which echo grids are similar in characteristics, and then they are classified into the same category. Specifically, the radar system uses clustering algorithms, such as the K-means algorithm or DBSCAN density clustering, to group the echo grids. Each group of grids is labeled with a clustering label, which indicates the similarity of these grids in signal characteristics and spatial positions. For example, if the slant ranges and azimuths of two echo grids are relatively close and the signal intensities are similar, they are classified into the same cluster and given the same label.

[0048] Furthermore, the method provided by the application embodiment further includes:

[0049] Construct a filter array with a multi-signal spectrum, where each filter partition in the filter array corresponds to a two-dimensional spectrum template; construct a first matched filter block according to the filter array; take the phase consistency of the scattering points as the judgment criterion, determine the phase error by analyzing the phase gradient, and construct a second phase correction block for performing phase error compensation; connect the second phase correction block to the back of the first matched filter block to determine the echo processing module; embed and deploy the echo processing module in the radar system.

[0050] In the embodiment of the present application, first, the received echo signal is subjected to spectrum analysis using a multi-signal spectrum. This process converts the echo signal from the time domain to the frequency domain through methods such as the fast Fourier transform (FFT), and extracts the frequency components of the signal. In the frequency domain, the radar system decomposes different frequency signals and constructs a filter array according to the frequency characteristics of the signals. Each array partition corresponds to a two-dimensional spectrum template. These spectrum templates optimize the signals by adjusting the frequency bandwidth and directivity. The filter array enhances the target signals respectively at different frequency components, while suppressing the background noise and improving the signal quality.

[0051] Next, using the constructed filter array, the radar system generates a first matched filter block through the matched filtering method. Matched filtering is to compare the received echo signal with a preset template, enhance the part related to the target signal, and weaken the part related to the background noise at the same time. This method is based on the correlation between the signal and the template. By calculating the matching degree between the two, the signal intensity is optimized to ensure that the target signal is maximally enhanced while reducing the noise influence from the interference source.

[0052] After the echo signal is enhanced, it enters the phase error compensation stage. Due to platform movement or relative target movement, the phase of the echo signal usually shifts, resulting in phase errors. Therefore, a phase gradient analysis method is adopted to identify these phase errors. Specifically, by measuring the phase of the scattering points in the echo signal and calculating the phase difference between adjacent scattering points, the phase change of the echo signal is analyzed. The calculation method of the phase gradient is based on the phase change of each echo signal point, and by solving the formula , where and are the phase values of adjacent scattering points respectively. Through these calculations, the phase distortion caused by platform or target movement is identified, providing a basis for subsequent compensation.

[0053] After the phase error is identified, a second phase correction block is constructed. This block is used to perform phase error compensation. The phase compensation method uses an iterative algorithm (such as the least squares method or the gradient descent method). By analyzing the phase difference in the echo signal, the phase of the echo signal is gradually adjusted to eliminate the phase error caused by platform or target movement. The radar system corrects the phase of the signal through multiple iterations until the phase of the echo signal reaches the expected target and the phase distortion of the signal is completely corrected.

[0054] Finally, the second phase correction block is connected to the first matched filtering block to form a complete echo processing module. This module combines matched filtering and phase compensation to ensure that while enhancing the target signal, the phase error caused by platform or target movement is corrected. This echo processing module is embedded and deployed in the radar system to process the received echo signal in real time.

[0055] Step S300: Introduce a grid resolution parameter, perform two-dimensional matched filtering based on signal spectrum matching on the grid echo signal, and perform phase residual error compensation based on gradient autofocus to determine the effective echo grid, where the grid resolution parameter includes the instantaneous slant range and instantaneous azimuth from the radar emission point to the beam center, and the phase residual error is the residual error after spectrum filtering.

[0056] In the embodiments of the present application, grid resolution parameters are first introduced, including the instantaneous slant range and the instantaneous azimuth. The instantaneous slant range refers to the actual straight-line distance from the radar emission point to the center of the target echo, which changes continuously with the relative motion between the radar and the target; while the instantaneous azimuth refers to the angle between the radar beam and the target echo. Next, based on the grid resolution parameters, a two-dimensional matched filtering based on signal spectrum matching is performed on the echo grid signal. By performing spectrum analysis on the received echo signal, the signal is converted into a frequency-domain signal, and the signal is optimized through a two-dimensional spectrum template matching method. Specifically, the spectrum of the echo signal is compared with a preset spectrum template to enhance the spectral components of the target signal while suppressing background noise. The matched filtering process is based on the frequency and spatial characteristics of the signal to ensure that the signal components within the spectral range are effectively amplified, thereby enhancing the intensity of the target signal.

[0057] However, due to the motion of the platform or the target, the phase of the echo signal often shifts, resulting in phase residual errors. To compensate for these phase errors, a phase residual error compensation technique based on gradient autofocus is adopted. Specifically, first, through the phase gradient analysis method, the phase changes between adjacent scatterers in the echo signal are analyzed to identify and determine the phase errors. Phase gradient analysis helps the system locate the phase distortion caused by the motion of the platform or the target by calculating the phase differences of the scatterers in the echo signal. According to the calculated phase errors, the second phase correction block is triggered to perform phase residual error compensation. In this process, the phase of the echo signal is adjusted through an iterative method to gradually eliminate the phase errors and restore the accurate phase of the echo signal. Finally, after the spectrum matching filtering and phase error compensation processing, the effective echo grid is determined.

[0058] Furthermore, in the method provided by the embodiments of the application, when performing the two-dimensional matched filtering based on signal spectrum matching and the phase residual error compensation based on gradient autofocus, it further includes:

[0059] By identifying the grid clustering label, the first matched filtering block is triggered. By performing two-dimensional spectrum template matching, the filtering array is directionally activated to perform directional filtering processing on the echo grid to determine the first processed echo grid; for the first processed echo grid, a phase residual error ambiguity verification is performed, the second phase correction block is triggered, and phase residual error compensation is performed to determine the effective echo grid.

[0060] In the embodiments of the present application, first, by identifying grid clustering labels, the received echo signals are classified and identified according to a predetermined spatial region. Next, the first matching filter block is triggered according to the grid clustering labels to enhance the echo signals. Through two-dimensional spectrum template matching, spectrum analysis and filtering processing are performed on the received echo signals. After the signals are transformed into the frequency domain through fast Fourier transform (FFT), they are matched with a preset two-dimensional spectrum template, so as to enhance the spectral characteristics of the target signals and suppress background noise. Through this process, the radar system can enhance the frequency components related to the target in the echo signals, ensuring that the target signals are prominent in the filtered echo grid. After completing the matching filtering, the radar system performs directional filtering processing, which optimizes the signals based on the spatial positions of each echo grid and the direction of the radar beam. By directionally activating the filter array, targeted processing is performed on the echo signals. The directional filtering process ensures that the signals are effectively enhanced within a specific frequency range and spatial distribution, thereby eliminating background noise and optimizing the clarity of the signals, and finally obtaining the first processed echo grid.

[0061] Next, for the first processed echo grid, phase residual error ambiguity verification is performed. The purpose of this process is to detect and correct the phase errors caused by the relative motion of the platform or the target. First, traverse the first processed echo grid, and randomly select a part of the grids for preliminary inspection, which are called pre-inspection grids. Then, randomly select a group of scatter points in these pre-inspection grids for analysis. For each group of scatter points, calculate the phase difference between adjacent scatter points, and analyze the phase changes of these scatter points through difference analysis. By calculating the phase difference, it is judged whether there is a phase error. If the detected phase difference does not meet the predetermined consistency coefficient, it indicates that there is a phase residual error. At this time, a residual error compensation instruction is generated, and the second phase correction block is triggered to perform phase error compensation.

[0062] The second phase correction block iteratively adjusts the phase of the echo signals through techniques such as gradient autofocus method to eliminate the phase distortion caused by the motion of the platform or the target. The phase error compensation ensures that the signals are restored to an ideal state by gradually optimizing the phase of each echo signal. After this compensation process, an effective echo grid is obtained.

[0063] Furthermore, in the method provided by the application embodiments, when performing phase residual error ambiguity verification, it further includes:

[0064] Traverse the first processed echo grid, randomly determine the first number of pre-inspection grids; for the pre-inspection grids, randomly determine the second number of scatter points within the grids, determine multiple groups of scatter points, perform intra-group phase difference calculation on the multiple groups of scatter points, if the phase difference does not meet the consistency coefficient, generate a residual error compensation instruction; trigger the second phase correction block through the residual error compensation instruction.

[0065] In the embodiments of the present application, first, the first processed echo grid is traversed, that is, each echo grid is checked one by one to analyze its signal quality and potential errors. Next, a first number of pre-inspection grids are randomly determined, and a part of the grids are randomly selected from all the processed echo grids for further inspection. The selection of the pre-inspection grids is random. Through this random selection method, potential problems in the echo signal can be quickly identified without completely analyzing all the echo grids.

[0066] For each selected pre-inspection grid, a second number of scatter points within the grid are randomly determined. These scatter points are key data points in the echo signal, representing specific reflection characteristics of the target or scene. The radar system ensures the phase difference analysis of multiple points in the echo signal by randomly selecting a certain number of scatter points to obtain a more comprehensive signal quality assessment.

[0067] Next, multiple groups of scatter point pairs are determined, and the phases of the scatter points within these groups are subtracted. That is, by comparing the phase differences between each group of scatter points, the phase changes in the echo signal are detected. If the phase difference between adjacent scatter points is too large, it indicates that there is a phase error in the echo signal. By calculating the phase differences within the scatter point groups, the phase consistency of the echo signal is judged. If the calculated phase differences do not meet the consistency coefficient (i.e., the phase differences exceed the set tolerance range), it means that there are phase residual errors in the echo signal. The consistency coefficient is a preset tolerance standard used to measure whether the phase changes in the echo signal meet the expectations. If the phase differences exceed the tolerance range, error compensation is performed.

[0068] Finally, a residual error compensation instruction is generated based on the detected phase error. This instruction instructs the system to trigger the second phase correction block to perform phase compensation. Through this correction block, the radar system adjusts the phase in the echo signal according to the error compensation instruction, gradually eliminating the phase errors caused by platform or target movement to ensure the restoration of signal accuracy.

[0069] Step S400: Connect to the visualization simulation platform to perform simulation visualization on the effective echo grid.

[0070] In the embodiments of the present application, at the final stage of radar signal processing, after spectrum matching filtering and phase error compensation, effective echo grids are obtained. These echo grids represent optimized signal data with high signal quality and accuracy. To further analyze and display these echo data, the effective echo grids are connected to the visualization simulation platform. The visualization simulation platform generates intuitive images or 3D models by associating the echo grid data with the spatial coordinate system to display the spatial distribution and target characteristics of the echo signal.

[0071] Furthermore, the method provided by the embodiments of the application further includes:

[0072] For the said survey strip, determine the regional characteristics; according to the regional characteristics, determine the scene interference wave and simulation focus direction; use the scene interference wave to filter and modulate the grid echo signal; use the simulation focus direction to simulate and modulate the effective echo grid.

[0073] In the embodiment of the present application, first analyze the survey strip to determine its regional characteristics. The survey strip refers to a specific geographical area covered during the radar scanning process, which is closely related to the radar's coverage, target type, and environmental characteristics. The regional characteristics include factors such as terrain, weather conditions, obstacles, and target distribution, all of which may affect the propagation and reception of radar signals. For example, in mountainous areas, the echo signal may be reflected or blocked by mountains, and in rainy weather, raindrops may attenuate the radar signal. Therefore, analyze the corresponding regional characteristics based on these features of the survey strip to optimize the signal processing strategy.

[0074] Then, based on the identified regional characteristics, further analyze the scene interference wave and simulation focus direction. The scene interference wave refers to factors that may interfere with the target signal during radar detection, such as ground reflection, weather fluctuations, and reflections from other objects. These interference waves will affect the quality of the echo signal, and it is necessary to determine the parameters such as the frequency, intensity, and time delay of these interference waves according to the regional characteristics. For example, rainy weather may increase the noise in the reflected signal, and the presence of buildings may cause multipath effects, resulting in signal distortion.

[0075] After identifying the scene interference wave, determine the simulation focus direction. The simulation focus direction refers to the specific aspects that should be concerned during the simulation process, such as the enhancement of the target echo or the suppression of interference signals. According to the regional characteristics, select different simulation focus directions to make the simulation process closer to the actual situation. For example, in an area with strong interference, the simulation focus direction may be concentrated on weakening the interference signal, while in an environment with strong target signals, the simulation may be more focused on optimizing the enhancement of the target echo.

[0076] Next, based on the scene interference wave, filter and modulate the grid echo signal. The grid echo signal refers to the signal data received by the radar corresponding to the target echo. These signals contain the reflection information of the target and the noise from the environment. Through filtering and modulation, the radar system can effectively reduce the impact of the scene interference wave. Specifically, use appropriate filtering algorithms, such as adaptive filtering or Kalman filtering, to dynamically adjust the filter parameters according to the characteristics of the interference wave, such as frequency and time delay. Suppress the interference components unrelated to the target signal through this process while maintaining the integrity of the target echo signal. For example, if there is a strong multipath effect in the scene, use a multipath interference suppression filtering algorithm to reduce the interference of this effect on the echo signal.

[0077] Finally, according to the simulation focus direction, the effective echo grid is simulated and modulated. At this stage, the radar system adjusts the characteristics of the echo signal according to the definition of the simulation focus direction. For example, if the simulation focus direction is to enhance the target signal, signal enhancement techniques (such as gain control or target signal amplification) are used to increase the intensity of the target echo. If the simulation focus direction is to reduce interference, noise suppression algorithms (such as spectral subtraction or minimum mean square error estimation) are selected to reduce the noise in the signal. Finally, through these simulation modulations, accurate echo signals are generated for target detection or image reconstruction.

[0078] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0079] The present application plans the strip trajectory and the mapping grid for the relative detection scenario between the radar system and the mapping strip. Among them, the radar system performs inclined plane strip detection by an airborne method; with the strip trajectory and the mapping grid, the radar system is driven to perform strip dynamic detection and echo reception to determine the grid echo signal; a grid resolution parameter is introduced, and two-dimensional matched filtering based on signal spectrum matching and phase residual error compensation based on gradient autofocus are performed on the grid echo signal to determine the effective echo grid, where the grid resolution parameter includes the instantaneous slant range and instantaneous azimuth from the radar emission point to the beam center, and the phase residual error is the residual error after spectral filtering; a visualization simulation platform is connected to perform simulation visualization on the effective echo grid. The present invention solves the technical problems in the prior art that it is difficult for airborne radar to accurately simulate echo response in non-horizontal mapping scenarios and lacks effective error compensation and simulation visualization mechanisms. Through the combined driving of the strip trajectory and the mapping grid, the combination of spectral matching filtering and gradient phase compensation, and the integration of the simulation visualization platform, the technical effect of improving the echo simulation accuracy in the inclined plane detection scenario is achieved.

[0080] Embodiment 2, based on the inventive concept of the inclined plane airborne strip echo simulation method with auxiliary autofocus processing in the foregoing embodiment, the present application also provides an electronic device, including: at least one processor; a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the steps of any one of the methods in the foregoing Embodiment 1.

[0081] Figure 2 It is a schematic structural diagram of an exemplary electronic device of the present application. In Figure 2In it, the bus architecture is represented by bus 300. Bus 300 may include any number of interconnected buses and bridges. Bus 300 connects various circuits including one or more processors represented by processor 302 and a memory represented by memory 304 together. Bus 300 may also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, etc., which are well known in the art, so further description thereof will not be provided herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same element, i.e., a transceiver, which provides a unit for communicating with various other devices on the transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 may be used to store data used by processor 302 when performing operations.

[0082] It should be noted that the above order of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above description of specific embodiments of this specification has been made. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0083] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

[0084] This specification and the drawings are only exemplary descriptions of the present application and are considered to have covered any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A simulation method for the echo of an inclined-plane airborne strip for assisting autofocus processing, characterized in that The method includes: For the relative detection scenario between the radar system and the survey strip, plan the strip trajectory and the survey grid, where the radar system performs inclined plane strip detection by an airborne method; Drive the radar system to perform strip dynamic detection and echo reception with the strip trajectory and the survey grid, and determine the grid echo signal; Introduce grid resolution parameters, perform two-dimensional matched filtering based on signal spectrum matching and phase residual error compensation based on gradient autofocus on the grid echo signal, and determine the effective echo grid, where the grid resolution parameters include the instantaneous slant range and instantaneous azimuth from the radar emission point to the beam center, and the phase residual error is the residual error after spectrum filtering; Connect to the visualization simulation platform and perform simulation visualization on the effective echo grid.

2. The method for simulating the echo of an inclined plane airborne strip for auxiliary autofocus processing according to claim 1, wherein The survey scenario based on the inclined plane strip includes a first scenario and a second scenario, where in the first scenario, the strip trajectory is horizontally parallel to the survey strip and there is a vertical inclination angle, and in the second scenario, there are horizontal and vertical inclination angles between the strip trajectory and the survey strip.

3. The method for simulating the echo of an inclined plane airborne strip with auxiliary autofocus processing according to claim 1, wherein Drive the radar system with the strip trajectory and the survey grid, including: Determine the first fixed-point plan with the grid center as the radar beam center; Determine the second range plan with an equidistant ring as the range constraint, where the equidistant ring is greater than or equal to the survey grid size; According to the first fixed-point plan and the second range plan, determine the radar parameters based on the strip motion state of the radar system and the survey grid under the strip trajectory, where the radar parameters include azimuth parameters and beam parameters; Drive the radar system adaptively with the strip motion through the radar parameters.

4. The method for simulating the slant-plane airborne strip echo for auxiliary autofocus processing according to claim 3, wherein Determine the radar parameters based on the strip motion state of the radar system and the survey grid under the strip trajectory, including: The radar system is composed of a phased radar array; Based on the strip trajectory, determine the co-frequency detection grid during strip motion, where the instantaneous slant range and instantaneous azimuth of the co-frequency detection grid are the same or different; Deploy the radar parameters for the phased radar array according to the co-frequency detection grid.

5. The method for simulating the echo of an inclined plane airborne strip with auxiliary autofocus processing according to claim 3, characterized in that, After determining the grid echo signal, including: Receive the grid echo signal, perform grid size cutting based on the equidistant ring, and determine the equidistant grid; Perform relative distribution splicing of the equidistant grid based on the survey grid to determine the echo grid; Based on the grid resolution parameters, perform identification clustering on the echo grid and label the grid clustering label.

6. The method for simulating the echo of an inclined plane airborne strip with auxiliary autofocus processing according to claim 5, wherein The method further includes: Construct a filtering array with a multi-signal spectrum, where each filtering partition in the filtering array corresponds to a two-dimensional spectrum template; Construct the first matched filtering block according to the filtering array; With the phase consistency of scatter points as the judgment criterion, determine the phase error by analyzing the phase gradient, and construct the second phase correction block for performing phase error compensation; Connect the second phase correction block behind the first matched filtering block to determine the echo processing module; Embed and deploy the echo processing module in the radar system.

7. The method for simulating the echo of an inclined plane airborne strip for auxiliary autofocus processing according to claim 6, characterized in that, Perform two-dimensional matched filtering based on signal spectrum matching and phase residual error compensation based on gradient autofocus, including: By identifying the grid clustering label, trigger the first matching filter block, perform two-dimensional spectrum template matching, directionally activate the filter array, perform directional filtering processing on the echo grid, and determine the first processed echo grid; For the first processed echo grid, perform phase residual error ambiguity verification, trigger the second phase correction block, perform phase residual error compensation, and determine the effective echo grid.

8. The method for simulating the echo of an inclined plane airborne strip with auxiliary autofocus processing according to claim 7, characterized in that, Performing phase residual error ambiguity verification includes: Traverse the first processed echo grid and randomly determine a first number of pre-inspection grids; For the pre-inspection grids, randomly determine a second number of scatter points within the grid to determine multiple sets of scatter points; Perform in-group phase difference calculation on the multiple sets of scatter points. If the phase difference does not meet the consistency coefficient, generate a residual error compensation instruction; Through the residual error compensation instruction, trigger the second phase correction block.

9. The method for simulating the echo of an inclined plane airborne strip with auxiliary autofocus processing according to claim 1, wherein The method further includes: Determine the regional characteristics for the mapping strip; According to the regional characteristics, determine the scene interference wave and the simulation focus direction; Use the scene interference wave to perform filtering modulation on the grid echo signal; use the simulation focus direction to perform simulation modulation on the effective echo grid.

10. An electronic device, characterized in that, The electronic device includes: A memory for storing executable instructions; A processor for implementing the oblique plane airborne strip echo simulation method for auxiliary autofocus processing according to any one of claims 1-9 when executing the executable instructions stored in the memory.

Images