Space-based networking radar multi-coverage fusion target tracking method and system

Abstract

The invention relates to a space-based networking radar multi-coverage fusion target tracking method and system, and the method comprises the steps: carrying out the preprocessing of target echo data obtained through the observation of a same target through a plurality of radar nodes, which are disposed on each track plane of a low-orbit space, of a space-based networking radar, and obtaining radar measurement data, the target measurement data are three-dimensional measurement data under a Cartesian coordinate system with a target as an original point, unscented Kalman filtering is carried out on the three-dimensional measurement data to obtain a plurality of corresponding filtering data, sequential fusion is carried out on all the filtering data according to a covariance cross fusion algorithm to obtain fusion state estimation of the target, and the fusion state estimation of the target is obtained. And target tracking is realized. By adopting the method, the precise tracking of the space target can be realized, the low-orbit space target orbit coverage rate can be improved, the cooperative networking operation of the space-based surveillance radar can be realized, and the precision and efficiency of space target monitoring can be effectively improved.

Description

Technical Field

[0001] The present application relates to the field of space situational awareness technology, and in particular to a target tracking method and system for space-based networked radar with multiple coverage fusion. Background Art

[0002] The number of space targets has exploded with the increase of human space activities. Tracking and monitoring technology for various spacecraft has become an important technical support for space situational awareness missions. Enhancing space situational awareness capabilities is the key to space resource development, space security and space control.

[0003] The main task of the space target monitoring system is to accurately track and catalog important space targets. As an important part of the space target monitoring system, space-based radar can work together with ground-based radar and space-based optical sensors to further enhance the situational awareness of the space monitoring system. After years of development, the deployable antenna technology and T / R component technology of space-based radars in various countries have made further breakthroughs, which can effectively solve the problem of power emission of space-based radars and make the manufacturing, equipment and operation of space-based monitoring network radars possible.

[0004] Different from space-based optical sensors and ground-based radars, space-based networked radars have their own unique detection advantages. Space-based radars do not need to consider the geographical restrictions of various countries and can achieve full-sky deployment in space. At the same time, unlike space-based optical sensors, the detection capability of space-based radars is not affected by sunlight, and effective detection of space targets can be achieved in the shadow area. These characteristics can ensure that space-based radars have a higher frequency of observation of space targets, which can greatly enhance the monitoring system's ability to update catalog information on space targets.

[0005] However, space-based radars still face challenges such as: when performing space target monitoring tasks, the field of view that needs to be monitored is very large, so using space-based radars to search for space targets over a large range places high demands on the radar's power aperture product; a single space-based radar is not enough to form a large-scale low-orbit space target detection capability, and it is necessary to achieve full coverage of low-orbit space by building a Walker constellation. At this time, space targets will appear in the monitoring airspace of multiple space-based radars, and how to effectively use the sensor resources of space-based radars to achieve coordinated detection of space targets is a topic that needs to be studied in depth. Summary of the invention

[0006] Based on this, it is necessary to provide a target tracking method and system that can conduct a large-scale search for space targets and fully cover the low-orbit space by using multiple coverage fusion of space-based networked radars to address the above-mentioned technical problems.

[0007] A target tracking method for space-based networked radar multiple coverage fusion, the method comprising:

[0008] Acquire target echo data obtained by observing the same target from multiple radar nodes arranged on each orbital plane of the low-orbit space by the space-based network radar;

[0009] After preprocessing the target echo data, radar measurement data is obtained, wherein the target measurement data is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin;

[0010] Performing unscented Kalman filtering on each of the three-dimensional measurement data to obtain a corresponding plurality of filtered data;

[0011] All the filter data are sequentially fused according to the covariance cross-fusion algorithm to obtain a fusion state estimation of the target to achieve target tracking.

[0012] In one embodiment, the preprocessing of each target echo data includes: pulse compression and moving target detection.

[0013] In one embodiment, the three-dimensional measurement data is represented as:

[0014]

[0015]

[0016] where θq,k(xk)=arctan2((yk-yq,k) / (xk-xq,k))

[0017]

[0018] In the above formula, R q,k ,θ q,k , They represent the target distance, azimuth angle information and elevation angle information in the measurement matrix of the qth radar node at time k, respectively. k represents the motion state of the target at time k, (x q,k ,y q,k , z q,k ) represents the position coordinates of the qth radar node in the Cartesian coordinate system at time k, (x k ,y k ,z k ) represents the position coordinates of the target in the Cartesian coordinate system at time k.

[0019] In one embodiment, the motion state of the target is expressed as:

[0020] x k =Fxk-1 +u k-1

[0021] In the above formula, x k Represents the motion state vector of the target, and its specific form is: Among them, (x k ,y k ,z k ), They represent the position, velocity and acceleration at the kth moment in the Cartesian coordinate system, F represents the state transfer matrix, u k-1 represents zero-mean Gaussian white noise.

[0022] In one embodiment, all the filter data are sequentially fused according to the covariance cross-fusion algorithm, and the fused target state estimate and the corresponding covariance are expressed as:

[0023]

[0024] In the above formula, represents the set of all tracking radar nodes of the target at time k, represents the fusion estimation state of the space target, represents the fusion covariance of tracking, ω q,k Represents the weights of different radar nodes in the fusion process.

[0025] In one embodiment, the weights of different radar nodes in the fusion process are obtained using the following formula:

[0026]

[0027] The present application also provides a target tracking system with multiple coverage fusion of space-based networked radars, the system comprising: a plurality of space-based radars arranged on each orbital plane of the low-orbit space, and an information fusion unit;

[0028] Each of the space-based radars is used to observe the target echo data obtained from the same target, and to obtain radar measurement data after preprocessing the target echo data, wherein the target measurement data is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin, and to obtain corresponding filtered data after performing unscented Kalman filtering on the three-dimensional measurement data, and the filtered data is sent to the information fusion unit;

[0029] The information fusion unit is used to sequentially fuse all the filter data according to the covariance cross fusion algorithm to obtain a fusion state estimation of the target to achieve target tracking.

[0030] In one embodiment, the space-based radars are networked in a Walker constellation geometry configuration.

[0031] In one embodiment, the radar power aperture product of each of the space-based radars is obtained based on the dual-row track element number TEL information.

[0032] The above-mentioned target tracking method and system with multiple coverage fusion of space-based network radars obtains radar measurement data after preprocessing the target echo data obtained by observing the same target by multiple radar nodes arranged on each orbital plane of the low-orbit space by the space-based network radar, wherein each target measurement data is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin, and then each three-dimensional measurement data is subjected to unscented Kalman filtering to obtain corresponding multiple filtered data, and all the filtered data are sequentially fused according to the covariance cross-fusion algorithm to obtain the fusion state estimation of the target to achieve target tracking. This method can achieve accurate tracking of space targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A schematic diagram of a flow chart of a target tracking method using multiple coverage fusion of space-based networked radars in one embodiment;

[0034] Figure 2 A schematic diagram of the geometric observation of a space-based network radar in one embodiment;

[0035] Figure 3 A schematic diagram of space-based radar monitoring in one embodiment;

[0036] Figure 4 This is a schematic diagram of a curve showing the variation of the power aperture product with the detection distance in a simulation experiment;

[0037] Figure 5 A schematic diagram of a curve showing the variation of power demand with effective aperture in a simulation experiment;

[0038] Figure 6 A schematic diagram of the Walker constellation of a space-based radar in a simulation experiment;

[0039] Figure 7 A schematic diagram of target track coverage in a simulation experiment;

[0040] Figure 8 A schematic diagram of coverage multiplicity quality parameters in a simulation experiment;

[0041] Fig. 9 A schematic diagram of tracking position error comparison in a simulation experiment;

[0042] Fig.10 A schematic diagram of tracking speed error comparison in a simulation experiment;

[0043] Fig.11FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] In view of the problem that a single space-based radar cannot achieve comprehensive coverage of the earth's low-orbit area in the prior art, this application provides a target tracking method with multiple coverage fusion of space-based networked radars, which specifically includes the following steps:

[0046] Step S100, obtaining target echo data obtained by observing the same target respectively by multiple radar nodes of the space-based network radar arranged on each orbital plane in the low-orbit space.

[0047] In step S110 , radar measurement data is obtained by preprocessing the echo data of each target, wherein the measurement data of each target is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin.

[0048] Step S120 , performing unscented Kalman filtering on each of the three-dimensional measurement data to obtain a plurality of corresponding filtered data.

[0049] Step S130, sequentially fuse all the filter data according to the covariance cross-fusion algorithm to obtain a fusion state estimation of the target to achieve target tracking.

[0050] In this embodiment, an algorithm for performing target tracking in a space-based network radar is provided by fusing observation data of a plurality of space-based radars on the same target in their respective observation fields.

[0051] In this embodiment, the observation geometry diagram of the space-based networked radar monitoring the space target is shown in Question 2. The space target appears in the observation airspace of multiple space-based radars at the same time. The space-based radar system can improve the tracking accuracy of the space target through collaborative tracking.

[0052] like Figure 2 As shown in the figure, the space-based radar and the space target are running in three-dimensional space at the same time. Through coordinate transformation, the space-based radar tracking problem of the space target can be converted into a multi-sensor target tracking problem. The motion equation of the space target in a shorter time interval can be modeled as a CA model, and the motion state of the target can be expressed as:

[0053] x k =Fx k-1 +u k-1 (1)

[0054] In formula (1), x k represents the motion state vector of the target at time k, and its specific form is: Among them, (x k ,y k ,z k ), They represent the position, velocity and acceleration at the kth moment in the Cartesian coordinate system, F represents the state transfer matrix, u k-1 represents zero-mean Gaussian white noise.

[0055] In step S110, after each space-based radar acquires the target echo data, pulse compression and moving target detection are performed on the data in sequence to obtain radar measurement data, wherein each target measurement data is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin.

[0056] In this embodiment, after preprocessing the target echo data, a series of radar measurements can be formed. At time k, Q space-based radars simultaneously track the target, and the relationship between the observation vector of the qth radar and the target state vector is:

[0057]

[0058] In formula (2), represents the measurement noise of each space-based radar system, is the measurement matrix of the qth radar at time k, including target distance, azimuth angle information and elevation angle information.

[0059] Furthermore, the three-dimensional measurement data is expressed as:

[0060]

[0061] Where, θq,k(xk)=arctan2((yk-yq,k) / (xk-xq,k))(4)

[0062]

[0063] In formula (3) and formula (4), R q,k ,θ q,k , They represent the target distance, azimuth angle information and elevation angle information in the measurement matrix of the qth radar node at time k, respectively. k represents the motion state of the target at time k, (x q,k ,y q,k , z q,k ) represents the position coordinates of the qth radar node in the Cartesian coordinate system at time k, (x k,y k ,z k ) represents the position coordinates of the target in the Cartesian coordinate system at time k.

[0064] In step S130, all filtered data are sequentially fused according to the covariance cross-fusion algorithm, and the fused target state estimate and the corresponding covariance are expressed as:

[0065]

[0066] In formula (5), represents the set of all tracking radar nodes of the target at time k, represents the fusion estimation state of the space target, represents the fusion covariance of tracking, ω q,k Represents the weights of different radar nodes in the fusion process.

[0067] Furthermore, in solving the weights ω of different radar nodes in the fusion process q,k When , the weight sum of all radar nodes is 1, and the minimum fusion covariance index is satisfied, using the following formula:

[0068]

[0069] In this embodiment, when the fusion processing is performed on all the filtered data, the data at the corresponding time is processed sequentially.

[0070] The distributed fusion solution proposed in this application has small computational complexity and strong stability, which can improve the tracking accuracy of the space-based network radar for the target to a certain extent, and at the same time expand the situational awareness capability of the space surveillance system for space targets.

[0071] In this embodiment, the above-mentioned target tracking method of multiple coverage fusion of space-based networked radars can also be implemented in ground-based networked radars. Multiple ground-based radars use the above-mentioned tracking method to track the same aerial target, and can also achieve good tracking accuracy.

[0072] In the present application, a target tracking system with multiple coverage fusion of space-based networked radars is also provided, which includes: a plurality of space-based radars arranged on each orbital plane of the low-orbit space, and an information fusion unit.

[0073] Among them, each space-based radar is used to observe the target echo data obtained from the same target, and the radar measurement data is obtained after pre-processing the target echo data. Among them, the target measurement data is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin. The three-dimensional measurement data is subjected to unscented Kalman filtering to obtain corresponding filtered data, and the filtered data is sent to the information fusion unit.

[0074] Among them, the information fusion unit is used to sequentially fuse all the filtered data according to the covariance cross-fusion algorithm to obtain the fusion state estimation of the target to achieve target tracking.

[0075] In order to meet the increasingly severe needs of space target monitoring and form a large-scale space-based radar observation system, it is necessary to deploy multiple space-based radar satellites in space orbit to form a networked collaborative observation capability and complete timely monitoring of key space targets through a "network-to-network" approach.

[0076] In this embodiment, the space-based radars are networked in a Walker constellation geometry configuration.

[0077] The Walker constellation is a space-based radar network composed of multiple satellites, which aims to achieve comprehensive monitoring and data collection of various areas of the Earth's low-orbit space. The Walker constellation configuration is commonly described as: (N / P / F,h,i). N is the total number of satellites in the constellation, P is the number of orbital planes in the constellation, i is the orbital inclination of the satellite in the constellation, h is the orbital altitude of the satellite in the constellation, and F is the phase factor, which is an integer between 0:(P:1) and represents the phase relationship between the corresponding satellites in two adjacent orbital planes in the constellation.

[0078] Specifically, the phase factor is used to determine the phase difference between corresponding satellites on two adjacent orbital planes. The offset angle between the two satellites is:

[0079]

[0080] These satellites are distributed in different orbits, covering different areas of the Earth's low-orbit space, and can complete real-time monitoring of low-orbit space targets. Through the Walker constellation, high-frequency data collection can be achieved, providing important support and data support for the monitoring of key space targets.

[0081] Considering that the main limiting factor for the performance of space-based radar systems is the power-aperture product, analyzing the power-aperture product of single-base space-based radar is crucial for the construction and design of space-based radar systems.

[0082] In this embodiment, the radar power aperture product of each space-based radar is obtained according to the dual-row track element TEL information. The space-based radar system can greatly reduce the search range of the space-based radar for space targets under the guidance of TLE information, thereby effectively reducing the demand for the space-based radar power aperture product for space target monitoring tasks.

[0083] Specifically, the ground surveillance system has a relatively complete catalog information library for key space targets, namely the double-row orbital element TLE information. Space-based radar can use TLE information to more accurately predict the position and operation status of space targets. Space-based radar only needs to complete the recapture of the target within the prediction error range to achieve effective tracking of space targets. Figure 3 Schematic diagram of space-based radar monitoring space targets. Assume that the TLE prediction error is ΔR TLE , R is the radar detection distance. Then the corresponding angle of the radar search area of ​​the space-based radar in the azimuth dimension and the pitch dimension can be expressed as Θ A =Θ E =2ΔR TLE / R.

[0084] At this time, the search solid angle of the space-based surveillance radar expressed in steradians is:

[0085]

[0086] The 3dB beamwidths of the space-based radar antenna in azimuth and elevation are θ a With θ e Then the number of antenna beam positions required to cover the solid angle Ω is n B for:

[0087]

[0088] Assuming that the space-based radar irradiates N pulses at a single wave position, considering τ = 1 / B and P t =P av T PRI / τ, the search radar equation (based on a single pulse per beam per PRI) can be reduced to:

[0089]

[0090] In formula (10), Δsnr represents the signal-to-noise ratio corresponding to a single pulse, P av represents the power of the space-based radar, B represents the bandwidth, σ is the target scattering cross section, T PRI represents the pulse repetition time, G represents the antenna gain, λ represents the wavelength, τ represents the pulse width, k represents the Boltzmann constant, T e represents radar noise temperature, F represents noise factor, and L represents system loss.

[0091] When the radar scans the solid angle Ω, the scanning time required is T sc , and when a single wave position irradiates N pulses, the radiation time T of the space-based radar to the space target i for:

[0092]

[0093] Combining formula (10) we get:

[0094]

[0095] After N pulses of a single wave position are accumulated, the signal-to-noise ratio of the single wave position is:

[0096]

[0097] Wherein, SNR is the cumulative detectable signal-to-noise ratio.

[0098] Furthermore, considering the relationship G = 4πA / λ 2 and G = 4π / θ a θ e , formula (13) can be transformed into:

[0099]

[0100] In formula (14), P av A is the power aperture product. The power aperture product PAP (Power Aperture product) of the space-based radar under the guidance of TLE information can be obtained as:

[0101]

[0102] It can be seen from formula (15) that when the TLE prediction error and the target scattering cross section are fixed, the transmit average power-aperture product of the single-base space-based radar is proportional to the square of the detection distance. When the TLE prediction error and the detection distance are fixed, the transmit average power-aperture product of the single-base space-based radar is inversely proportional to the target scattering cross section.

[0103] For the specific definition of the target tracking system of multiple coverage fusion of space-based networked radar, please refer to the definition of the target tracking method of multiple coverage fusion of space-based networked radar in the above text, which will not be repeated here. Each module in the above-mentioned target tracking system of multiple coverage fusion of space-based networked radar can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0104] In this paper, simulation experiments are also used to prove the effectiveness of calculating the power aperture product of space-based radar guided by TLE information. The experiment sets the TLE prediction error to ΔR TLE = 20km, the space target RCS is set to 1m 2According to formula (10), the curve of power aperture product size changing with detection distance under different detection distances can be obtained as follows: Figure 4 As shown in Figure 2, when the distance changes from 1000km to 2000km, the power aperture product requirement changes from 41.50dB to 53.54dB.

[0105] Furthermore, the curve of the power requirement of space-based radar changing with the effective aperture when the detection distance is 2000km is given, as follows: Figure 5 When the effective aperture area is 50m 2 At this time, the power requirement of the space-based radar is 4523W, which is achievable with the current level of radar devices.

[0106] Then, the coverage performance of the Walker constellation for low-orbit space targets was verified through simulation experiments. The detection range of the space-based radar was set to 2000km in the experiment, and the radar network consisted of 48 satellites with the same orbital inclination, and the corresponding constellation code was: (48 / 8 / 1, 6854km, 50°). Figure 6 It is a schematic diagram of the Walker constellation of the space-based radar. The simulation time is set to: 28Apr2024 00:00:00.000~29Apr 2024 00:00:00.000. The TLE data of the seed satellite of the space-based networking radar and the low-orbit space target are shown in Table 1.

[0107] Table 1 Six orbital elements of SBR seed and LEO satellite

[0108]

[0109] Figure 7 This is the coverage performance diagram of the Walker constellation for low-orbit space targets (Coverage for Target). From the figure, we can analyze that the Walker space-based network radar coded as 48 / 8 / 1,6854km,50° can cover most of the orbital arcs of low-orbit space targets. Through aerospace software, it can be calculated that the orbital coverage rate of the space-based network radar for the target has reached 87.7%, and its maximum revisit time is 757.64s.

[0110] Figure 8Figure of Merit shows the coverage quality parameter of space-based network radar on low-orbit space targets. It can be seen from the figure that in the time period of 28Apr 2024 00:00:00.000 to 29Apr 2024 00:00:00.000, the space-based network radar can achieve triple coverage of space targets in a few time intervals, and the probability of single coverage is basically the same as that of double coverage. In the process of double coverage and triple coverage, the use of effective multi-sensor fusion tracking algorithm can further improve the cataloging accuracy of space targets.

[0111] In this paper, the target tracking method proposed in this paper is implemented based on the target tracking system of multiple coverage fusion of space-based network radar proposed in this paper, and experimental simulation is carried out. The tracking time interval of the space-based network radar for space targets is set to: 28Apr 2024 00:11:00.000~28Apr 2024 00:12:00.000. The performance of the algorithm is verified by comparing the position Root Mean Square Error (RMSE) and speed RMSE corresponding to the entire tracking process, and the target root mean square errors are defined as:

[0112]

[0113] In the above formula, MC is the number of Monte Carlo tracking, and are the estimated target position and target velocity respectively.

[0114] Combination Figure 8 It can be seen that in this time interval, the space-based networked radars achieved single coverage and double coverage of the space target in turn. Among them, in the interval of 28Apr 2024 00:11:00.000~28Apr 2024 00:11:26.000, space-based radar 1 achieved single observation of the space target; in the interval of 28Apr 2024 00:11:26.000~28Apr 2024 00:12:00.000, space-based radar 1 and space-based radar 2 jointly achieved double coverage of the space target. We compared the single coverage tracking result of space-based radar 1 only with the double coverage tracking result formed by space-based radar 1 and space-based radar 2 to verify the effectiveness of the space-based networked radar collaborative observation proposed in this paper to improve the space target tracking performance. Fig. 9 and Fig.10 They are the position RMSE and speed RMSE corresponding to the entire tracking process.

[0115] It can be seen that the entire tracking process of the space-based network radar for the space target is convergent. When tracking to the 26th frame, the coverage of the space target by the space-based network radar changes from single coverage to double coverage. At this time, since the two radars of the space-based network radar can form a state estimate of the space target, the covariance cross-fusion algorithm can effectively form the optimal fusion estimate, thereby further reducing the tracking error of the space target. Fig.10 It can be seen that at the 60th frame, the RMSE of the position estimation of the target by the space-based radar 1 is 205.956m, while the RMSE of the position estimation of the multi-coverage tracking algorithm proposed in this paper is 169.389m, and the position estimation accuracy is improved by about 17.56%. Fig.10 It can be seen that at the 60th frame, the RMSE of the speed estimation of the target by the space-based radar 1 is 38.314m / s, while the RMSE of the speed estimation of the algorithm proposed in this paper is 32.964m / s, and the speed estimation accuracy is improved by about 13.96%. The proposed algorithm can effectively integrate the state estimation information of multiple sensors on the target during the tracking process, and to a certain extent improve the tracking performance of space targets of the space-based networked radar system.

[0116] In the target tracking system of multiple coverage fusion of the above-mentioned space-based network radar, the radar power aperture product formula under the guidance of TLE information is analyzed in detail according to the particularity of space target monitoring. And by using the CI fusion criterion, the collaborative tracking of low-orbit space targets by space-based network radar is realized. By deploying low-orbit Walker constellation space-based radars, the orbital coverage of low-orbit space targets can be improved, and the collaborative networking operation of space-based surveillance radars can be realized, effectively improving the accuracy and efficiency of space target monitoring and cataloging.

[0117] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0118] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.11As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a target tracking method of multiple coverage fusion of a space-based network radar is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse, etc.

[0119] Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0120] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0121] Acquire target echo data obtained by observing the same target from multiple radar nodes arranged on each orbital plane of the low-orbit space by the space-based network radar;

[0122] After preprocessing the target echo data, radar measurement data is obtained, wherein the target measurement data is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin;

[0123] Performing unscented Kalman filtering on each of the three-dimensional measurement data to obtain a corresponding plurality of filtered data;

[0124] All the filter data are sequentially fused according to the covariance cross-fusion algorithm to obtain a fusion state estimation of the target to achieve target tracking.

[0125] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0126] Acquire target echo data obtained by observing the same target from multiple radar nodes arranged on each orbital plane of the low-orbit space by the space-based network radar;

[0127] After preprocessing the target echo data, radar measurement data is obtained, wherein the target measurement data is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin;

[0128] Performing unscented Kalman filtering on each of the three-dimensional measurement data to obtain a corresponding plurality of filtered data;

[0129] All the filter data are sequentially fused according to the covariance cross-fusion algorithm to obtain a fusion state estimation of the target to achieve target tracking.

[0130] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0131] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0132] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A target tracking method of space-based network radar multiple coverage fusion, characterized in that: The method comprises: Acquire target echo data obtained by observing the same target from multiple radar nodes arranged on each orbital plane of the low-orbit space by the space-based network radar; After preprocessing the target echo data, radar measurement data is obtained, wherein the target measurement data is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin; Performing unscented Kalman filtering on each of the three-dimensional measurement data to obtain a corresponding plurality of filtered data; All the filter data are sequentially fused according to the covariance cross-fusion algorithm to obtain a fusion state estimation of the target to achieve target tracking.

2. The target tracking method according to claim 1, characterized in that: The preprocessing of each target echo data includes: pulse compression and moving target detection.

3. The target tracking method according to claim 1, characterized in that: The three-dimensional measurement data is expressed as: where θq,k(xk)=arctan2((yk-yq,k) / (xk-xq,k)) In the above formula, R q,k ,θ q,k , They represent the target distance, azimuth angle information and elevation angle information in the measurement matrix of the qth radar node at time k, respectively. k represents the motion state of the target at time k, (x q,k ,y q,k , z q,k ) represents the position coordinates of the qth radar node in the Cartesian coordinate system at time k, (x k ,y k ,z k ) represents the position coordinates of the target in the Cartesian coordinate system at time k.

4. The target tracking method according to claim 3, characterized in that: The motion state of the target is expressed as: x k =Fx k-1 +u k-1 In the above formula, x k Represents the motion state vector of the target, and its specific form is: Among them, (x k ,y k ,z k ), They represent the position, velocity and acceleration at the kth moment in the Cartesian coordinate system, F represents the state transfer matrix, u k-1 represents zero-mean Gaussian white noise.

5. The target tracking method according to claim 3, characterized in that: All the filtered data are sequentially fused according to the covariance cross-fusion algorithm, and the fused target state estimation value and the corresponding covariance are expressed as: In the above formula, represents the set of all tracking radar nodes of the target at time k, represents the fusion estimation state of the space target, represents the fusion covariance of tracking, ω q,k Represents the weights of different radar nodes in the fusion process.

6. The target tracking method according to claim 5, characterized in that: The weights of different radar nodes in the fusion process are obtained using the following formula: 。 7. A target tracking system with multiple coverage fusion of space-based networked radars, characterized in that: The system comprises: a plurality of space-based radars arranged on each orbital plane of the low-orbit space, and an information fusion unit; Each of the space-based radars is used to observe the target echo data obtained from the same target, and to obtain radar measurement data after preprocessing the target echo data, wherein the target measurement data is three-dimensional measurement data in a Cartesian coordinate system with the target as the origin, and to obtain corresponding filtered data after performing unscented Kalman filtering on the three-dimensional measurement data, and the filtered data is sent to the information fusion unit; The information fusion unit is used to sequentially fuse all the filter data according to the covariance cross fusion algorithm to obtain a fusion state estimation of the target to achieve target tracking.

8. The target tracking system according to claim 7, characterized in that: The space-based radars are networked in a Walker constellation geometry configuration.

9. The target tracking system according to claim 7 or 8, characterized in that: The radar power aperture product of each of the space-based radars is obtained according to the double-row track element number TEL information.

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