Space target space-based microwave imaging parameter optimization method and device

Abstract

The application relates to the technical field of space imaging, and provides a space target space-based microwave imaging parameter optimization method and device. The method comprises the following steps: predicting a target intersection section of a detection satellite and a space target, extracting an average relative speed of the detection satellite and the space target, a minimum intersection distance and an orbit prediction error component from the target intersection section, determining an optimized detection time length and an optimized detection frequency of the detection satellite based on at least the minimum intersection distance and the orbit prediction error component, determining an optimized imaging time length of the detection satellite based on at least the average relative speed and the minimum intersection distance, and performing multi-constraint collaborative solving on a pulse repetition frequency (PRF) of the detection satellite based on at least the average relative speed and the minimum intersection distance to obtain an optimized PRF. The method realizes microwave imaging parameter optimization design of a quantitative model and actual scene constraint, is high in efficiency, is suitable for a wide range of scenes, and provides strong support for precision improvement and engineering landing of space-based microwave imaging technology.

Description

Technical Field

[0001] This application relates to the field of space imaging technology, and in particular to a method and apparatus for optimizing space target space-based microwave imaging parameters. Background Technology

[0002] The number of space targets is exploding, and the high-density satellite constellations (such as SpaceX's Starlink system) intertwine with massive amounts of space debris, leading to a sharp increase in the risk of orbital collisions. This has created a triple requirement of "high-precision identification, high-real-time monitoring, and high-reliability assessment," especially in key areas such as spacecraft operation and maintenance (e.g., collision warning and avoidance) and space environment governance (e.g., debris tracking and removal), where breakthroughs in core technologies are urgently needed. Space-based microwave imaging technology, with its unique advantages of being available all-weather, all-day, and unaffected by atmospheric attenuation, has become a core means of space target monitoring. Space-based platforms can overcome the limitations of Earth's curvature and terrain, achieving full-space coverage observation. Furthermore, by flexibly adjusting the observation perspective, it can acquire richer structural and motion information about targets, enabling ultra-high-resolution imaging and non-cooperative target identification. Currently, this technology is evolving towards multi-band, miniaturized, and multi-mode development for spaceborne platforms.

[0003] The core performance of space-based microwave imaging of space targets, such as ultra-high resolution, target acquisition success rate, and on-board resource utilization, directly depends on the precise design of key parameters such as detection time, number of detections, imaging time, and pulse repetition frequency (PRF). These parameters must simultaneously adapt to scenario characteristics such as "high-speed motion of both satellites (relative speed between the observation satellite and the target satellite reaches 7-14 km / s), large orbit prediction errors, and a high proportion of non-cooperative targets." Their design accuracy directly determines the imaging quality and mission efficiency.

[0004] Currently, some space-based microwave imaging technologies, both domestically and internationally, have laid the foundation in payload hardware (such as miniaturized Synthetic Aperture Radar (SAR), multi-band adaptation, and high-power transmission units) and imaging algorithms (such as 3D imaging, complex motion compensation, and compressed sensing imaging). The technical specifications of some Earth observation SAR satellites (such as Capella-2 and Qilu-1) have already met the requirements for high resolution and miniaturization. However, existing research on space-based microwave imaging is largely based on the technology transfer from Earth observation SAR satellites, or on ground-based radar, airborne radar, and vehicle-mounted radar for ground verification. There is a lack of dedicated satellite platforms and engineering practice accumulation for imaging space targets, and existing technologies still have many microscopic technical defects in the design of core parameters. Summary of the Invention

[0005] In view of this, the present application provides a method and apparatus for optimizing space target space-based microwave imaging parameters, in order to solve the problem that the existing space-based microwave imaging lacks a dedicated satellite platform and engineering practice accumulation for space target imaging scenarios, and there are still many technical defects at the microscopic level in the design of core parameters.

[0006] A first aspect of this application provides a method for optimizing space-based microwave imaging parameters for space targets, comprising:

[0007] Predict the target rendezvous segment between the probe satellite and the space target, and extract basic parameters from the target rendezvous segment; the basic parameters include the average relative velocity between the probe satellite and the space target, the minimum rendezvous distance, and the orbit prediction error components;

[0008] The optimized detection duration and number of detections for the probe satellite should be determined based at least on the minimum rendezvous distance and the orbit prediction error components.

[0009] The optimized imaging duration of the probe satellite should be determined based at least on the average relative velocity and the minimum intersection distance;

[0010] The pulse repetition frequency (PRF) of the probe satellite is solved by multiple constraints based at least on the average relative velocity and the minimum intersection distance to obtain the optimized PRF;

[0011] Among them, the multiple constraints include hardware constraints of the detection satellite, non-aliasing constraints of target imaging, constraints that echo reception does not cross the range gate during all time periods, and constraints that echoes do not conflict with pulse transmissions and nadir echoes.

[0012] A second aspect of this application provides a space target space-based microwave imaging parameter optimization device, comprising:

[0013] The prediction module is configured to predict the target rendezvous segment between the probe satellite and the space target, and extract basic parameters from the target rendezvous segment; the basic parameters include the average relative velocity between the probe satellite and the space target, the minimum rendezvous distance, and the orbit prediction error components;

[0014] The optimization module is configured to determine the optimized detection duration and the optimized number of detections for the probe satellite, based at least on the minimum intersection distance and the orbit prediction error components.

[0015] The optimization module is also configured to determine the optimized imaging duration of the probe satellite based at least on the average relative velocity and minimum intersection distance;

[0016] The optimization module is also configured to perform multi-constraint collaborative solution of the pulse repetition frequency (PRF) of the probe satellite based at least on the average relative velocity and minimum intersection distance, to obtain the optimized PRF;

[0017] Among them, the multiple constraints include hardware constraints of the detection satellite, non-aliasing constraints of target imaging, constraints that echo reception does not cross the range gate during all time periods, and constraints that echoes do not conflict with pulse transmissions and nadir echoes.

[0018] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method.

[0019] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0020] The beneficial effects of this application embodiment compared with the prior art are as follows: This application embodiment predicts the target intersection segment between the probe satellite and the space target, extracts the average relative velocity, minimum intersection distance, and orbit prediction error component of the probe satellite and the space target from the target intersection segment, determines the optimized detection duration and optimized detection number of the probe satellite based at least on the minimum intersection distance and orbit prediction error component, determines the optimized imaging duration of the probe satellite based at least on the average relative velocity and minimum intersection distance, and performs multi-constraint collaborative solution of the pulse repetition frequency (PRF) of the probe satellite based at least on the average relative velocity and minimum intersection distance to obtain the optimized PRF. This realizes the optimization design of microwave imaging parameters constrained by the quantitative model and the actual scene, which is highly efficient and widely applicable, providing strong support for the accuracy improvement and engineering implementation of space-based microwave imaging technology. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a method for optimizing space-based microwave imaging parameters for space targets, provided in an embodiment of this application.

[0023] Figure 2 This is a schematic diagram of the space-based microwave imaging process of a space target.

[0024] Figure 3 This is a schematic diagram illustrating the geometric relationship between the orbit prediction error components and the beam coverage area.

[0025] Figure 4This is a schematic diagram illustrating the process of multi-constraint collaborative solution of PRF provided in the embodiments of this application.

[0026] Figure 5 This is a schematic diagram of task time division obtained after parameter optimization using the method provided in the embodiments of this application.

[0027] Figure 6 This is a schematic diagram of a space target space-based microwave imaging parameter optimization device provided in an embodiment of this application.

[0028] Figure 7 This is a schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0029] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0030] The following will describe in detail, with reference to the accompanying drawings, a method and apparatus for optimizing space-based microwave imaging parameters of a space target according to embodiments of this application.

[0031] As mentioned above, existing space-based microwave imaging lacks dedicated satellite platforms and engineering experience for imaging space targets, and there are still many technical deficiencies at the observation level in the design of core parameters. These deficiencies are specifically manifested as follows:

[0032] 1) Lack of mechanism for determining the number of probes: The existing design of the number of probes is mostly a fixed value (single or multiple times), and it is not adaptively designed according to the magnitude of the target satellite orbit prediction error.

[0033] 2) Lack of quantitative basis for the design of detection time: In existing technologies, the detection time is mostly determined by engineering experience and has not been introduced into a specific model of dual high-speed targets and orbit prediction error. That is, no quantitative correlation model of orbit error projection, target relative angular velocity and beam coverage has been established.

[0034] 3) Lack of a direct quantitative correlation between imaging duration and resolution requirements: Current imaging duration designs do not directly link synthetic aperture principles to azimuth resolution, relying solely on empirically selected fixed durations, leading to issues of "inadequate resolution" or "time redundancy." For example, the synthetic aperture length corresponding to centimeter-level azimuth resolution needs to be quantitatively calculated using wavelength and minimum intersection distance to derive the theoretical imaging duration. However, current technologies have not established this quantitative relationship, resulting in a disconnect between imaging duration and resolution requirements. Either the preset resolution cannot be achieved due to insufficient duration, or onboard computing resources are wasted due to excessive duration.

[0035] 4) The selection of PRF does not take into account the coordination of multiple constraints, which may lead to imaging defects: As a core parameter, PRF must simultaneously meet three major constraints: "no aliasing inside the target, no conflict during range migration, and hardware feasibility". However, the existing technology has a single constraint-oriented problem: it only considers the upper and lower limits of hardware and Doppler bandwidth, without combining the target size to calculate the lower limit of non-aliasing; ultimately leading to target aliasing or wasting on-board resources.

[0036] In summary, existing parameter design methods lack refined quantitative models for core parameters, fail to address the micro-level coupling problem of "error constraints, resolution requirements, hardware limitations, and resource constraints," and are ill-suited to the complex scene characteristics of space target imaging, thus hindering the improvement of accuracy and engineering implementation of space-based microwave imaging technology. Therefore, it is urgent to construct an optimized design method that focuses on the quantitative calculation of core parameters to achieve precise adaptation of parameters to scene characteristics and imaging requirements.

[0037] In view of this, this application provides a method for optimizing space target space-based microwave imaging parameters. Focusing on four core parameters—detection duration, number of detections, imaging duration, and PRF—it achieves precise adaptation of parameters to the space target imaging scene through analysis of orbital dynamics, synthetic aperture size requirements, non-aliasing requirements for imaging scenes, and balancing onboard hardware conditions. This solves the problem of lack of quantitative basis for parameter design in the prior art.

[0038] Figure 1 This is a flowchart illustrating a method for optimizing space-based microwave imaging parameters for space targets, provided in an embodiment of this application. Figure 1 As shown, the method includes the following steps:

[0039] In step S101, the target intersection segment between the probe satellite and the space target is predicted, and basic parameters are extracted from the target intersection segment.

[0040] The basic parameters include the average relative velocity between the probe satellite and the space target, the minimum rendezvous distance, and the orbit prediction error components.

[0041] In step S102, the optimized detection duration and optimized number of detections for the probe satellite are determined based at least on the minimum intersection distance and the orbit prediction error component.

[0042] In step S103, the optimized imaging duration of the probe satellite is determined based at least on the average relative velocity and the minimum intersection distance.

[0043] In step S104, the pulse repetition frequency (PRF) of the probe satellite is solved by multiple constraints based at least on the average relative velocity and the minimum intersection distance to obtain the optimized PRF.

[0044] Among them, the multiple constraints include hardware constraints of the detection satellite, non-aliasing constraints of target imaging, constraints that the echo reception does not cross the range gate during all time periods, and constraints that the echo does not conflict with the pulse transmission and the nadir echo.

[0045] In some embodiments of this application, the method may be executed by a server or by a terminal device with certain processing capabilities.

[0046] In some embodiments of this application, the probe satellite carries a microwave imaging device. The microwave imaging device can be SAR or other equipment. For ease of explanation and description, the following description uses a probe satellite carrying SAR as an example.

[0047] In some embodiments of this application, the target rendezvous segment between the probe satellite and the space target can be predicted first, and basic parameters can be extracted from the target rendezvous segment. For example, the target rendezvous segment between the probe satellite and the space target can be calculated based on the orbital parameters, error parameters, resolution requirements, and hardware constraints of the probe satellite and the space target, and then basic parameters such as the average relative velocity, minimum rendezvous distance, and orbit prediction error components can be extracted from the target rendezvous segment.

[0048] Among them, the orbital parameters of the probe satellite and the space target can be used to calculate the intersection geometry parameters of the probe satellite and the space target, such as relative angular velocity and minimum intersection distance; error parameters can be used to design error tolerance thresholds, and then optimize the detection time and number of detections based on the error tolerance thresholds; resolution requirements can be used to determine the synthetic aperture length and theoretical imaging time of the probe satellite.

[0049] Next, the beam coverage of the detection satellite and the space target can be determined based on the minimum intersection distance. Then, based on the quantization relationship between the orbit prediction error component and the beam coverage, it can be determined whether multiple detections are needed to obtain the optimized number of detections.

[0050] Simultaneously, the time required for a space target to cross the detection beam can be determined by detecting the orbit prediction errors of the satellite and the space target. Then, redundancy is added to this time based on the orbit prediction error components to obtain the optimized detection duration. This detection duration is the length of one detection operation.

[0051] In some embodiments of this application, the optimized imaging duration can be derived based on the synthetic aperture principle using average relative velocity and minimum intersection distance, ensuring that it matches the preset azimuth resolution. Furthermore, the optimized PRF can be obtained by co-solving multiple constraints based on average relative velocity and minimum intersection distance.

[0052] According to the technical solution provided in the embodiments of this application, by predicting the target intersection segment between the probe satellite and the space target, the average relative velocity, minimum intersection distance, and orbit prediction error component of the probe satellite and the space target are extracted from the target intersection segment. The optimized detection duration and optimized detection number of the probe satellite are determined at least based on the minimum intersection distance and the orbit prediction error component. The optimized imaging duration of the probe satellite is determined at least based on the average relative velocity and the minimum intersection distance. The pulse repetition frequency (PRF) of the probe satellite is solved by multiple constraints at least based on the average relative velocity and the minimum intersection distance to obtain the optimized PRF. This realizes the optimization design of microwave imaging parameters constrained by the quantitative model and the actual scene, which is highly efficient and widely applicable, providing strong support for the accuracy improvement and engineering implementation of space-based microwave imaging technology.

[0053] In some embodiments of this application, predicting the target rendezvous segment between the probe satellite and the space target may include: acquiring the operating parameters of the probe satellite and the operating parameters of the space target; using the radar equations of the probe satellite as range constraints, simulating and predicting the effective rendezvous parameters between the probe satellite and the space target through orbital dynamics, thereby determining the rendezvous segment between the probe satellite and the space target; the effective rendezvous parameters include at least the effective start time, effective end time, effective duration, and effective minimum distance; and filtering each rendezvous segment according to the principle of minimum angular velocity to obtain the target rendezvous segment.

[0054] Basic parameters, including average relative velocity, can be extracted from the target intersection segment. Minimum intersection distance and orbit prediction error components, which may include radial components. Tangential components and horizontal components In some implementations, the basic parameters may also include duration. .

[0055] Figure 2 This is a schematic diagram of the space-based microwave imaging process of a space target. Figure 2 The upper center displays the orbits of the space target, including the actual and predicted orbits. The lower center displays the orbits of the probe satellite and the operating mode of the SAR (Surveillance-Reliability System) onboard the probe satellite. Both the probe satellite and the space target move from left to right.

[0056] like Figure 2 The probe satellite can first activate the SAR search + track mode. In this mode, the SAR beam is widened, the entire array transmits, and four subarrays receive. The search results are used to correct the predicted orbit of the space target, thus achieving target tracking. This search + track process can be called the detection process. After multiple detections, if the probe satellite determines that the imaging conditions for the space target are met, it can activate the SAR imaging mode. In this mode, the SAR beam is narrowed, and the entire array transmits and receives until imaging is complete. Therefore, it is necessary to optimize the detection parameters during the detection process and the imaging parameters during the imaging process.

[0057] Since the detection parameters need to balance the target acquisition success rate and the efficiency of onboard resources, the detection duration and number of detections can be adaptively optimized by quantifying the orbit prediction error component and the beam coverage range: when the acquired space target orbit prediction error is large and exceeds the coverage range of the SAR detection beam, multiple detections can be initiated to ensure the target acquisition success rate; when the acquired space target orbit prediction error is small and is within the coverage range of the SAR detection beam, only one detection can be initiated to save onboard resources.

[0058] Figure 3 This is a schematic diagram illustrating the geometric relationship between the orbit prediction error components and the beam coverage area. Figure 3 The line of sight shown in the geometric relationship is perpendicular to the two velocities and pointing downwards from point O, which is the predicted intersection point of the probe satellite and the space target. The dashed box on the right is an enlarged view of the dashed box on the left. Here, the two velocities refer to the velocity of the probe satellite and the velocity of the space target, and "perpendicular to the two velocities downwards" means perpendicular to the plane formed by the velocities of the probe satellite and the space target.

[0059] The angle between the probe satellite's orbit and the space target's orbit is... The complementary angle between the probe satellite's orbit and the azimuth plane of the probe satellite's antenna is... The angle between the tangential component of the space target orbit prediction error and the elevation plane of the probe satellite antenna is... , The dashed box represents the beam coverage area of ​​the SAR satellite. Tangential error refers to the tangential component in the orbit prediction error components. Lateral error refers to the lateral component in the orbit prediction error components. .

[0060] Figure 3 Both the tangential and lateral errors are within the coverage area of ​​the detection beam, so only one detection needs to be activated. If the tangential and lateral errors exceed the coverage area of ​​the detection beam, multiple detections can be activated to ensure a high success rate in target acquisition.

[0061] In other words, in some embodiments of this application, the detection parameters can be optimized based on the minimum intersection distance and the orbit prediction error component, including the optimization of detection duration and the optimization of the number of detections.

[0062] When optimizing the detection duration, the time it takes for a space target to pass through the main lobe of the detection satellite can be determined first. ;in, It is the azimuth beamwidth of the antenna. It is the broadening factor of the antenna pattern in detection mode. It is the angular velocity of the space target in the coordinate system of the detection satellite antenna.

[0063] Then, based on the orbit prediction error components, the projection of the orbit error onto the azimuth direction in the antenna coordinate system is determined. ;in, The angle of the orbital error projection is determined based on the relationship between the angle between the velocity vectors of the probe satellite and the space target and their relative velocities.

[0064] Next, the coverage width of the orbit prediction error in the azimuth direction of the antenna coordinate system is determined based on the minimum intersection distance. Therefore, the orbital error redundancy time is determined to be... .

[0065] The duration of the first probe was finally determined to be... and the duration of non-first detection is ;in, It is a positive integer greater than 1.

[0066] In other words, during the first probe, since the orbit prediction error has not been corrected, the probe duration includes both the "target main lobe crossing time" and the "orbit error redundancy time". For subsequent probes, since previous probe data has been obtained and the orbit prediction error of the space target has been corrected, there is no need to add the "orbit error redundancy time".

[0067] When optimizing the number of detections, the projection of the orbital error onto the pitch direction in the antenna coordinate system can be determined first based on the orbital prediction error components. .

[0068] Then, based on the minimum intersection distance, the coverage width of the orbit prediction error in the elevation direction of the antenna coordinate system is determined. ;in, It is the antenna range beamwidth.

[0069] Next, if confirmed or confirm Then the number of detections can be determined as follows: Otherwise, the number of detections is set to 1; where, To allocate the maximum available time for the exploration mission, The fixed time interval required for orbit prediction correction This indicates the floor function.

[0070] In other words, whether to perform multiple probes is dynamically determined based on the projection of the orbit prediction error components and the beam coverage, which avoids resource waste or acquisition failure caused by a fixed number of probes. This section includes the judgment on whether to enable multiple probes and how to select the number of probes.

[0071] The judgment formula can be expressed as: .

[0072] In some embodiments of this application, when determining the number of detections, a priority weight of the space target can be introduced. For space targets with higher priority weights, a strategy of "multiple detections + iterative correction" is adopted, while for space targets with lower priority weights, a strategy of "single detection + error tolerance" is adopted.

[0073] In other words, in some implementations, when optimizing the number of probes, the priority weight of the space target can be obtained first. If the priority weight of the space target is determined to be greater than a preset weight threshold, then the number of probes is determined to be [number missing]. and after each detection Correction components for orbit prediction errors within the time period. Among them, To determine the maximum available time for the exploration mission, The fixed time interval required for orbital prediction correction.

[0074] Conversely, if the priority weight of the space target is determined to be less than or equal to the preset weight threshold, the number of detections is determined to be 1, and a higher orbit prediction error threshold is set.

[0075] In some implementations, the system can be configured to accept the single-detection result if the orbit prediction error obtained from a single detection is less than or equal to the orbit prediction error threshold. Conversely, if the orbit prediction error obtained from a single detection is greater than the orbit prediction error threshold, the system can report the error to the processing unit of the detection satellite, which will then decide whether and when to initiate another single detection.

[0076] Optimization of imaging parameters mainly includes imaging time optimization. The optimized imaging time of the probe satellite can be determined as follows: First, determine the synthetic aperture length as... ;in, This is the radar wavelength for SAR. This represents the azimuth resolution of the SAR.

[0077] Then, the quotient of the synthetic aperture length and the average relative velocity is determined as the optimized imaging duration, i.e. ;in, This is the optimized imaging duration.

[0078] Finally, the quotient of the maximum available time for the imaging task and the optimized imaging duration is rounded down to obtain the optimized number of images that can be imaged. .in, This is the maximum available time, which can last for a specified duration. Subtracting the total detection time yields the result. This can be determined when extracting basic parameters.

[0079] As a core performance characteristic of space-based microwave imaging of space targets, the Performance Response (PRF) also requires optimization. In some implementations, the PRF can be optimized through multi-constraint collaborative solving. Specifically, this includes: determining a first PRF value range based on the hardware constraints of the detection satellite; determining a lower PRF limit based on target imaging non-aliasing constraints, and an upper PRF limit based on the constraint that echo reception does not cross a range gate during all-time periods; determining a second PRF value range based on the lower and upper PRF limits; determining a third PRF value range and a set of conflicting PRFs based on the non-conflict constraints between echo and pulse transmission and nadir echo; determining the intersection of the first, second, and third PRF value ranges as a candidate PRF range; eliminating conflicting PRFs from the candidate PRF ranges to obtain a set of conflict-free candidate PRFs; and determining the minimum value in the set of conflict-free candidate PRFs as the PRF for radar detection and imaging in this mission.

[0080] The lower limit of the PRF is determined based on the target imaging non-aliasing constraint, taking into account the size and average relative velocity of the space target, and can be expressed as follows: , ;in, It is the oversampling rate. The size of the space target.

[0081] The upper limit of PRF is determined based on the range gate constraint that the full-time echo reception does not cross, and is used to determine the distance changes between the detection satellite and the space target during imaging, the hardware protection duration, and the transmission duty cycle. It can be expressed as follows: ; To detect the maximum distance between the satellite and space targets during imaging, The duration of hardware protection is determined in advance based on the performance of the probe satellite's hardware. This is the sampling redundancy duration for SAR. This refers to the launch duty cycle.

[0082] The third value range of PRF is based on the formula. Determined; among them, It is a pulse index. It is the SAR transmit pulse width that includes the guard time. For hardware protection duration, It is the SAR echo arrival time. It is the SAR receive window width that includes the sampling redundancy time; where the collision PRF set is determined according to the formula Determined; among them, It is the distance from the sub-satellite point. It's the speed of light. It is a positive integer.

[0083] In other words, the PRF must simultaneously satisfy four constraints: hardware limitations, no target imaging aliasing, no range gate for all-time echo reception, and no conflict between echo and pulse transmission and nadir echo. The optimal value is solved through multi-constraint collaborative solution.

[0084] Regarding hardware constraints, since the hardware system is constrained by the physical properties of the components or by the design of the hardware system, the PRF cannot be made infinitely large or infinitely small. Therefore, a maximum or minimum value that is usable within the design range can be given.

[0085] For target imaging non-aliasing constraints, the lower limit of PRF can be determined by the spatial target size and average relative velocity; for full-time echo reception non-range gate constraints, the upper limit of PRF can be determined by range variation, guard duration and duty cycle.

[0086] For the non-conflict constraint between echo and pulse transmission and nadir echo, it is necessary to consider that the receiving window must be located after the end of the transmission pulse and cannot overlap with the next transmission pulse to ensure that the echo signal is not blocked by the transmission pulse; and the nadir echo must fall outside the useful echo receiving window to avoid interfering with the target's echo.

[0087] Then, we can obtain the intersection of the above constraints. and Within this range, a set of conflict-free PRFs is selected, and the minimum value in the set is chosen as the PRF for radar detection and imaging in this mission.

[0088] The above process of multi-constraint collaborative solution of PRF can be described as follows: Figure 4 As shown. Figure 4The yellow line represents conflicting PRFs that cannot be selected; the green line represents the non-conflicting portion of the entire radar imaging time, i.e., the set of conflict-free PRFs; the blue line represents PRFs that have partial time conflicts during the radar imaging time and cannot be selected; the thin red line represents the finally selected PRFs.

[0089] In some embodiments of this application, when the space target includes multiple targets, a multi-objective optimization algorithm can also be used when performing multi-constraint collaborative solution of the PRF. In this case, the first range of PRF values ​​can be determined based on the hardware constraints of the probe satellite; then, the lower limit of PRF can be determined based on the target imaging non-aliasing constraint, and the upper limit of PRF can be determined based on the constraint that the echo reception does not cross the range gate. The second range of PRF values ​​can be determined based on the lower and upper limits of PRF; then, the third range of PRF values ​​and the set of conflicting PRF values ​​can be determined based on the non-conflict constraints between echo and pulse transmission and nadir point echo; finally, the first range of PRF values, the second range of PRF values, the third range of PRF values, and the set of conflicting PRF values ​​are used as constraints, and a multi-objective optimization algorithm is used to perform multi-constraint optimization solution to obtain the optimized PRF.

[0090] Among them, multi-objective optimization algorithms can be, for example, genetic algorithms.

[0091] In some embodiments of this application, after optimizing parameters such as detection duration, number of detections, imaging duration, and PRF, the optimized parameters can be verified by considering the constraints of the satellite's onboard resources (such as computing resources and power consumption), and the optimized parameters can be dynamically adjusted based on the verification results to obtain the final design parameters. These final design parameters include at least the mission time allocation and RPF.

[0092] Figure 5 This is a schematic diagram of the mission time allocation obtained after parameter optimization using the method provided in the embodiments of this application. The left vertical axis represents the distance between the probe satellite and the space target, and the right vertical axis represents the radial velocity of the space target relative to the probe satellite. The figure shows various optimized design parameters, including the phased array scanning range, available imaging duration, probe occupancy duration, calculated and adjusted occupancy duration, and optimal imaging arc segment.

[0093] The technical solution provided in this application can achieve precise quantification of detection parameters. By establishing a quantitative correlation model of orbital error, relative motion, and beam coverage, the detection duration and number of detections are driven by data rather than empirical judgment, thus solving the problems of "time redundancy" or "acquisition failure" in existing technologies.

[0094] The technical solution provided in this application enables the number of probes to adaptively adapt to different scenarios. By dynamically adjusting the number of probes using a core criterion formula, it reduces on-board resource waste while ensuring target coverage and adapts to target scenarios with varying orbit prediction accuracies. For low-error targets (such as cooperative targets), a single probe is used to save resources; for high-error targets (such as non-cooperative targets), the number of probes is automatically increased to ensure a high acquisition success rate.

[0095] The technical solution provided in this application can directly bind imaging time and resolution. By constructing a quantitative model of imaging time and azimuth resolution through the synthetic aperture principle, it ensures that ultra-high resolution is stably achieved, avoiding resolution failure due to insufficient imaging time or resource waste due to redundant imaging time.

[0096] The technical solution provided in this application can solve the problem of difficult PRF selection. By taking into account four constraints—hardware limitations, target non-aliasing, echo not crossing the range gate, and no collision—it effectively avoids imaging defects such as target aliasing and echo collision.

[0097] The technical solution provided in this application can improve the engineering adaptability of parameter design. The entire parameter design process is based on quantitative models and actual scenario constraints, without relying on engineering experience. It is suitable for the complex characteristics of space target imaging, such as dual high-speed motion, large orbital errors, and a high proportion of non-cooperative targets. At the same time, it reduces the difficulty of engineering implementation through closed-loop adjustment of on-board resource constraints, providing key support for the engineering implementation of space-based microwave imaging technology.

[0098] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0099] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0100] Figure 6 This is a schematic diagram of a space-based microwave imaging parameter optimization device for space targets provided in an embodiment of this application. Figure 6 As shown, the device includes:

[0101] The prediction module 601 is configured to predict the target intersection segment between the probe satellite and the space target, and extract basic parameters from the target intersection segment; the basic parameters include the average relative velocity between the probe satellite and the space target, the minimum intersection distance, and the orbit prediction error components.

[0102] The optimization module 602 is configured to determine the optimized detection duration and the optimized number of detections for the probe satellite based at least on the minimum intersection distance and the orbit prediction error component.

[0103] The optimization module 602 is also configured to determine the optimized imaging duration of the probe satellite based at least on the average relative velocity and the minimum intersection distance.

[0104] The optimization module 602 is also configured to perform multi-constraint collaborative solution of the pulse repetition frequency (PRF) of the probe satellite based at least on the average relative velocity and the minimum rendezvous distance, so as to obtain the optimized PRF.

[0105] Among them, the multiple constraints include hardware constraints of the detection satellite, non-aliasing constraints of target imaging, constraints that the echo reception does not cross the range gate during all time periods, and constraints that the echo does not conflict with the pulse transmission and the nadir echo.

[0106] According to the technical solution provided in the embodiments of this application, by predicting the target intersection segment between the probe satellite and the space target, the average relative velocity, minimum intersection distance, and orbit prediction error component of the probe satellite and the space target are extracted from the target intersection segment. The optimized detection duration and optimized detection number of the probe satellite are determined at least based on the minimum intersection distance and the orbit prediction error component. The optimized imaging duration of the probe satellite is determined at least based on the average relative velocity and the minimum intersection distance. The pulse repetition frequency (PRF) of the probe satellite is solved by multiple constraints at least based on the average relative velocity and the minimum intersection distance to obtain the optimized PRF. This realizes the optimization design of microwave imaging parameters constrained by the quantitative model and the actual scene, which is highly efficient and widely applicable, providing strong support for the accuracy improvement and engineering implementation of space-based microwave imaging technology.

[0107] In some implementations, predicting the target rendezvous segment between the probe satellite and the space target includes: acquiring the probe satellite's operating parameters and the space target's operating parameters; using the probe satellite's radar equations as range constraints, simulating and predicting the effective rendezvous parameters between the probe satellite and the space target through orbital dynamics, thereby determining the rendezvous segment between the probe satellite and the space target; the effective rendezvous parameters include at least the effective start time, effective end time, effective duration, and effective minimum distance; and filtering each rendezvous segment based on the principle of minimum angular velocity to obtain the target rendezvous segment.

[0108] In some implementations, the optimized detection duration of the probe satellite is determined as follows: the time it takes for a space target to pass through the main lobe of the probe satellite. ;in, It is the azimuth beamwidth of the antenna. It is the broadening factor of the antenna pattern in detection mode. It is the angular velocity of the space target in the coordinate system of the detection satellite antenna; the projection of the orbital error onto the azimuth direction of the antenna coordinate system is determined based on the orbital prediction error components. ;in, This refers to the tangential component of the orbit prediction error. This refers to the lateral component of the orbit prediction error; The orbital error projection angle is determined based on the relationship between the angle between the velocity vectors of the probe satellite and the space target and their relative velocities; the coverage width of the orbital prediction error in the azimuth direction of the antenna coordinate system is determined based on the minimum intersection distance. ;in, To determine the minimum intersection distance; the track error redundancy time is determined as follows: The duration of the first probe was determined to be... and the duration of non-first detection is ;in, It is a positive integer greater than 1.

[0109] In some implementations, the optimized number of probes by the probe satellite is determined as follows: the projection of the orbital error onto the elevation direction in the antenna coordinate system is determined based on the orbital prediction error components. The coverage width of the orbit prediction error in the antenna coordinate system in the elevation direction is determined based on the minimum intersection distance. ;in, It is the antenna range beamwidth; in response to determination or confirm The number of detections was determined to be... Otherwise, the number of detections is set to 1; where, To allocate the maximum available time for the exploration mission, The fixed time interval required for orbit prediction correction This indicates the floor function.

[0110] In some implementations, the optimized number of probes by the probe satellite is determined as follows: in response to the priority weight for determining the space target being greater than a preset weight threshold, the number of probes is determined to be... and after each detection Correction components for orbit prediction errors within the time period; among which... To determine the maximum available time for the exploration mission, The fixed duration required for orbit prediction correction; in response to determining that the priority weight of the space target is less than or equal to a preset weight threshold, the number of detections is determined to be 1.

[0111] In some implementations, the detection satellite is a synthetic aperture radar (SAR) detection satellite; the optimized imaging duration of the detection satellite is determined as follows: the synthetic aperture length is determined to be... ;in, For SAR radar wavelength, The azimuth resolution of the SAR is given; the quotient of the synthetic aperture length and the average relative velocity is determined as the optimized imaging duration; and the quotient of the maximum available time for the imaging task and the optimized imaging duration is rounded down to obtain the optimized number of images that can be imaged.

[0112] In some implementations, the detection satellite is a synthetic aperture radar (SAR) detection satellite. The PRF (Probe Recognition Function) of the detection satellite is solved using a multi-constraint collaborative method, including: determining a first PRF value range based on the satellite's hardware constraints; determining a lower PRF limit based on target imaging non-aliasing constraints, determining an upper PRF limit based on all-time echo reception not crossing a range gate constraint, and determining a second PRF value range based on the lower and upper PRF limits; determining a third PRF value range and a conflicting PRF set based on echo and pulse transmission and nadir echo non-conflict constraints; determining the intersection of the first, second, and third PRF value ranges as a candidate PRF range; eliminating conflicting PRF sets from the candidate PRF ranges to obtain a conflict-free candidate PRF set; and determining the minimum value in the conflict-free candidate PRF set as the PRF for radar detection and imaging in this mission.

[0113] In some implementations, the lower limit of the PRF is determined based on the target imaging non-aliasing constraint, taking into account the size and average relative velocity of the space target; the lower limit of the PRF is... , ;in, It is the oversampling rate. For the size of the space target, To minimize the intersection distance, This is the radar wavelength for SAR.

[0114] In some implementations, the PRF upper limit is determined based on the constraint that the full-time echo reception does not cross the range gate, taking into account the distance changes between the detection satellite and the space target during imaging, the hardware protection duration, and the transmission duty cycle; the PRF upper limit is... ; To detect the maximum distance between the satellite and space targets during imaging, To detect the minimum distance between the satellite and the space target during imaging, For hardware protection duration, This is the sampling redundancy duration for SAR. For the launch duty cycle, It is the speed of light.

[0115] In some implementations, the third value range of PRF is determined according to the formula. Determined; among them, It is a pulse index. It is the SAR transmit pulse width that includes the guard time. For hardware protection duration, It is the SAR echo arrival time. It is the SAR receive window width that includes sampling redundancy time; the collision PRF set is based on the formula Determined; among them, It is the distance from the sub-satellite point. It's the speed of light. It is a positive integer.

[0116] In some implementations, the space target includes multiple targets; the PRF of the probe satellite is solved collaboratively with multiple constraints, including: determining a first range of PRF values ​​based on the hardware constraints of the probe satellite; determining a lower limit of PRF based on the target imaging non-aliasing constraint, determining an upper limit of PRF based on the constraint that the echo reception does not cross the range gate, and determining a second range of PRF values ​​based on the lower and upper limits of PRF; determining a third range of PRF values ​​and a set of conflicting PRF values ​​based on the non-conflict constraints between echo and pulse transmission and nadir point echo; and using a multi-objective optimization algorithm to perform multi-constraint optimization with the first, second, and third ranges of PRF values ​​and the set of conflicting PRF values ​​as constraints to obtain the optimized PRF.

[0117] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0118] Figure 7 This is a schematic diagram of the electronic device provided in an embodiment of this application. For example... Figure 7 As shown, the electronic device 7 of this embodiment includes a processor 701, a memory 702, and a computer program 703 stored in the memory 702 and executable on the processor 701. When the processor 701 executes the computer program 703, it implements the steps in the various method embodiments described above. Alternatively, when the processor 701 executes the computer program 703, it implements the functions of each module / unit in the various device embodiments described above.

[0119] Electronic device 7 can be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 7 may include, but is not limited to, processor 701 and memory 702. Those skilled in the art will understand that... Figure 7 This is merely an example of electronic device 7 and does not constitute a limitation on electronic device 7. It may include more or fewer components than shown, or different components.

[0120] The processor 701 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0121] The memory 702 can be an internal storage unit of the electronic device 7, such as a hard disk or RAM of the electronic device 7. The memory 702 can also be an external storage device of the electronic device 7, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc., equipped on the electronic device 7. The memory 702 can also include both internal and external storage units of the electronic device 7. The memory 702 is used to store computer programs and other programs and data required by the electronic device.

[0122] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0123] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0124] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for optimizing space-based microwave imaging parameters for space targets, characterized in that, include: Predict the target intersection segment between the probe satellite and the space target, and extract basic parameters from the target intersection segment; The basic parameters include the average relative velocity between the probe satellite and the space target, the minimum rendezvous distance, and the orbit prediction error components; The optimized detection duration and the optimized number of detections for the probe satellite are determined at least based on the minimum intersection distance and the orbit prediction error components; The optimized imaging duration of the probe satellite is determined based at least on the average relative velocity and the minimum intersection distance; The pulse repetition frequency (PRF) of the probe satellite is solved using a multi-constraint collaborative method based at least on the average relative velocity and the minimum intersection distance to obtain an optimized PRF; Among them, the multiple constraints include the hardware constraints of the detection satellite, the non-aliasing constraint of target imaging, the constraint that the echo reception does not cross the range gate during all time periods, and the constraint that the echo does not conflict with the pulse transmission and the nadir point echo. The detection satellite is a synthetic aperture radar (SAR) detection satellite; The PRF of the aforementioned probe satellite is solved collaboratively with multiple constraints, including: The first range of PRF values ​​is determined based on the hardware constraints of the probe satellite; The lower limit of PRF is determined based on the target imaging non-aliasing constraint, the upper limit of PRF is determined based on the full-time echo reception non-crossing range gate constraint, and the second value range of PRF is determined based on the lower limit of PRF and the upper limit of PRF. The third value range of PRF and the set of conflicting PRFs are determined based on the non-conflict constraints between echo and pulse transmission and nadir echo. The intersection of the first range of PRF values, the second range of PRF values, and the third range of PRF values ​​is determined as the candidate PRF range; The conflicting PRF set is removed from the candidate PRF range to obtain a conflict-free candidate PRF set; The minimum value in the set of conflict-free candidate PRFs is determined as the PRF for radar detection and imaging in this mission.

2. The method for optimizing space-based microwave imaging parameters for space targets according to claim 1, characterized in that, The predicted target intersection segment between the probe satellite and the space target includes: Acquire operational parameters of probe satellites and space targets; Using the radar equations of the probe satellite as the range constraint, the effective rendezvous parameters between the probe satellite and the space target are obtained through orbital dynamics simulation using the probe satellite's operating parameters and the space target's operating parameters, thereby determining the rendezvous segment between the probe satellite and the space target; the effective rendezvous parameters include at least the effective start time, effective end time, effective duration, and effective minimum distance; The target intersection segment is obtained by selecting each intersection segment based on the principle of minimum angular velocity.

3. The method for optimizing space-based microwave imaging parameters for space targets according to claim 1, characterized in that, The optimized detection duration of the probe satellite was determined using the following method: Determine the time when the space target passes through the main lobe of the probe satellite. ;in, It is the azimuth beamwidth of the antenna. It is the broadening factor of the antenna pattern in detection mode. It is the angular velocity of the space target in the coordinate system of the detection satellite antenna; The projection of the orbit error onto the azimuth direction in the antenna coordinate system is determined based on the orbit prediction error components. ;in, This refers to the tangential component of the orbit prediction error. This refers to the lateral component of the orbit prediction error; The orbital error projection angle is determined based on the relationship between the angle between the velocity vectors of the probe satellite and the space target and their relative velocities. The coverage width of the orbit prediction error in the azimuth direction of the antenna coordinate system is determined based on the minimum intersection distance. ;in, This is the minimum intersection distance; The track error redundancy time is determined as follows: ; The duration of the first detection was determined to be and the duration of non-first detection is ;in, It is a positive integer greater than 1.

4. The method for optimizing space-based microwave imaging parameters for space targets according to claim 3, characterized in that, The optimized number of probes by the probe satellite was determined as follows: The projection of the orbital error onto the elevation direction in the antenna coordinate system is determined based on the orbital prediction error components. ; The coverage width of the orbit prediction error in the antenna coordinate system in the elevation direction is determined based on the minimum intersection distance. ;in, It is the beamwidth in the antenna range direction; Response to determination or confirm The number of detections was determined to be... Otherwise, the number of detections is set to 1; where, To allocate the maximum available time for the exploration mission, The fixed time interval required for orbit prediction correction This indicates the floor function.

5. The method for optimizing space-based microwave imaging parameters for space targets according to claim 3, characterized in that, The optimized number of probes by the probe satellite was determined as follows: In response to the priority weight of determining a space target being greater than a preset weight threshold, the number of detection attempts is determined. and after each detection Correction components for orbit prediction errors within the time period; among which, To determine the maximum available time for the exploration mission, The fixed time required for orbital prediction correction; In response to the determination that the priority weight of the space target is less than or equal to a preset weight threshold, the number of detection attempts is determined to be 1.

6. The method for optimizing space-based microwave imaging parameters for space targets according to claim 1, characterized in that, The detection satellite is a synthetic aperture radar (SAR) detection satellite; The optimized imaging duration of the probe satellite was determined using the following method: The synthetic aperture length is determined to be ;in, This is the radar wavelength for SAR. This represents the azimuth resolution of the SAR. This is the minimum intersection distance; The quotient of the synthetic aperture length and the average relative velocity is determined as the optimized imaging duration; Furthermore, the quotient of the maximum available time for the imaging task and the optimized imaging duration is rounded down to obtain the optimized number of images that can be imaged.

7. The method for optimizing space-based microwave imaging parameters for space targets according to claim 1, characterized in that, The lower limit of the PRF is determined based on the size of the space target and the average relative velocity according to the target imaging non-aliasing constraint. The lower limit of PRF is , ;in, It is the oversampling rate. The size of the space target. The minimum intersection distance, This is the radar wavelength for SAR.

8. The method for optimizing space-based microwave imaging parameters for space targets according to claim 1, characterized in that, The upper limit of the PRF is determined based on the distance change between the detection satellite and the space target during imaging, the hardware protection duration, and the transmission duty cycle, according to the constraint that the full-time echo reception does not cross the distance gate. The upper limit of the PRF is ; To detect the maximum distance between the satellite and space targets during imaging, To detect the minimum distance between the satellite and the space target during imaging, The duration of the hardware protection is [duration]. This is the sampling redundancy duration for SAR. The launch duty cycle is... It is the speed of light.

9. The method for optimizing space-based microwave imaging parameters for space targets according to claim 1, characterized in that, The third value range of PRF is based on the formula. Determined; among them, It is a pulse index. It is the SAR transmit pulse width that includes the guard time. For hardware protection duration, It is the SAR echo arrival time. It is the width of the SAR receive window, including the sampling redundancy time; The conflict PRF set is based on the formula Determined; among them, It is the distance from the sub-satellite point. It's the speed of light. It is a positive integer.

10. The method for optimizing space-based microwave imaging parameters of space targets according to claim 1, characterized in that, The space targets include multiple targets; The PRF of the aforementioned probe satellite is solved collaboratively with multiple constraints, including: The first range of PRF values ​​is determined based on the hardware constraints of the probe satellite; The lower limit of PRF is determined based on the target imaging non-aliasing constraint, the upper limit of PRF is determined based on the all-time echo reception not crossing the range gate constraint, and the second value range of PRF is determined based on the lower limit and the upper limit of PRF. The third value range of PRF and the set of conflicting PRFs are determined based on the non-conflict constraints between echo and pulse transmission and nadir echo. Using the first range of PRF values, the second range of PRF values, the third range of PRF values, and the set of conflicting PRFs as constraints, a multi-objective optimization algorithm is used to perform multi-constraint optimization to obtain the optimized PRF.

11. A space-based microwave imaging parameter optimization device for space targets, characterized in that, include: The prediction module is configured to predict the target intersection segment between the probe satellite and the space target, and extract basic parameters from the target intersection segment; The basic parameters include the average relative velocity between the probe satellite and the space target, the minimum rendezvous distance, and the orbit prediction error components; The optimization module is configured to determine the optimized detection duration and the optimized number of detections for the probe satellite based at least on the minimum intersection distance and the orbit prediction error components. The optimization module is also configured to determine the optimized imaging duration of the probe satellite based at least on the average relative velocity and the minimum intersection distance; The optimization module is also configured to perform multi-constraint collaborative solution of the pulse repetition frequency (PRF) of the probe satellite based at least on the average relative velocity and the minimum intersection distance, to obtain the optimized PRF; Among them, the multiple constraints include the hardware constraints of the detection satellite, the non-aliasing constraint of target imaging, the constraint that the echo reception does not cross the range gate during all time periods, and the constraint that the echo does not conflict with the pulse transmission and the nadir point echo. The detection satellite is a synthetic aperture radar (SAR) detection satellite; The PRF of the aforementioned probe satellite is solved collaboratively with multiple constraints, including: The first range of PRF values ​​is determined based on the hardware constraints of the probe satellite; The lower limit of PRF is determined based on the target imaging non-aliasing constraint, the upper limit of PRF is determined based on the full-time echo reception non-crossing range gate constraint, and the second value range of PRF is determined based on the lower limit of PRF and the upper limit of PRF. The third value range of PRF and the set of conflicting PRFs are determined based on the non-conflict constraints between echo and pulse transmission and nadir echo. The intersection of the first range of PRF values, the second range of PRF values, and the third range of PRF values ​​is determined as the candidate PRF range; The conflicting PRF set is removed from the candidate PRF range to obtain a conflict-free candidate PRF set; The minimum value in the set of conflict-free candidate PRFs is determined as the PRF for radar detection and imaging in this mission.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 10.

13. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 10.

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