Tree-based track initiation method and electronic equipment

Abstract

The invention relates to the technical field of track initiation, and discloses a tree-based track initiation method and electronic equipment. Comprising the following steps: S01, carrying out point-to-point correlation on a target trace point and a temporary track node, and formulating a correlation result; s02, related results are updated, and a temporary track tree to be processed is constructed; s03, identifying an initial node from the temporary track tree to be processed, and starting the initial node according to a track in sequence; s04, executing corresponding track processing operation on the temporary track tree to be processed; s05, carrying out structure adjustment on the temporary track tree to be processed; according to environment information sensed in real time, parameters in point-to-point association and track initiation confirmation can be adaptively optimized and adjusted, the problems of sensitive parameters, large calculation amount and poor non-linear adaptation existing when track initiation is carried out by depending on expert knowledge are avoided, the track initiation performance in a dynamic complex environment is improved, and the track initiation efficiency is improved. And accurate track initiation of the real target is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of track initiation, and more particularly, to a tree-based track initiation method and electronic device. BACKGROUND

[0002] Track initiation, as the starting stage of radar data processing, plays a crucial role in the process of radar data processing in civil and military fields. Track initiation involves a range from the detection of a target falling into the radar range to the final establishment of the track of the target. Correct track initiation can reduce false alarms caused by false targets, improve the accuracy and stability of target tracking, and thus avoid the phenomenon of false tracking and missed tracking of target plots.

[0003] A radar target track initiation method based on random forest is disclosed in patent application No. CN107688170A, which includes the following steps: step one, feature extraction of plot combinations of radar historical observation data, extraction of motion features between plot combinations and non-motion features of plot combinations, and formation of a training sample sampling set; step two, training of the training sample sampling set decision tree, and the trained decision trees as base classifiers to form a random forest combination classifier; step three, in the test phase, after data pre-selection and feature extraction of radar observation area plots, plot combination sample parameters for classification are formed, and the random forest combination classifier is used to obtain the track initiation result. The existing track initiation is usually implemented by using three methods, namely, heuristic rule method, logic method and Hough transform method. However, the heuristic rule method needs to rely on preset track initiation rules and cannot dynamically adapt to the real-time changes of clutter density or target maneuvering state. In the logic method, the setting of related parameter thresholds depends on artificial experience, and when the parameters are not properly set, the negative interference caused by false targets cannot be excluded. When the Hough transform method is used for parameter space mapping, a huge calculation burden will be generated in a short time, and it cannot meet the track initiation demand of non-linear dynamic target flight path, and thus cannot perform dynamic, real-time and accurate track initiation operation on different types of targets.

[0004] In view of this, the present application provides a tree-based track initiation method and electronic device to solve the above problems. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art and achieve the above-mentioned purpose, the present application provides the following technical scheme: a tree-based track initiation method, comprising: S01: The divided grid areas are summarized into a grid set, the temporary track nodes in the grid set are compared with the target track, the target category and target parameter of the target track are determined, and the target track and the temporary track nodes meeting the related requirements are point-to-point correlated to formulate the correlation results of the target track; S02: The correlation results are updated based on the correlation success flag of the correlation results to construct a to-be-processed temporary track tree; S03: The verification nodes are identified from the to-be-processed temporary track tree that has reached the processing time, the starting nodes are screened from the verification nodes based on the starting state of the verification nodes, and the starting nodes are sequentially tracked according to the size relationship between the speed variance of the starting node and the next starting node; S04: The track starting analysis is performed on the to-be-processed temporary track tree that has not reached the processing time, and the corresponding track processing operation is executed according to the track starting analysis result; S05: The direct adjustment mode or the indirect adjustment mode is selected, and the structure of the to-be-processed temporary track tree is adjusted by deleting the temporary track nodes corresponding to the starting nodes in the grid area and releasing the track space pointed by the starting nodes.

[0006] Further, the grid area summarizing method is: The center point is marked in the two-dimensional plane area scanned by the radar, the set grid distance length is used as the distance dimension division standard, the set grid azimuth angle is used as the azimuth dimension division standard, the center point is used as the division starting point, and the two-dimensional plane area is divided into A grid areas; The positions of B target tracks in the A grid areas are marked to obtain the track positions; The covering circle is drawn with the track positions as the center and 3 times the grid distance length as the radius, the grid areas inside the covering circle are recorded as target grids, and all the target grids are summarized to generate a grid set.

[0007] Further, the target category determination method is: The time interval between the time of the target track and the time of the temporary track node is calculated and recorded as the time interval; The distance interval is calculated by taking the absolute value of the difference between the distance from the target track to the center point and the distance from the temporary track node to the center point; The track speed of the target track is calculated by dividing the distance interval by the time interval; M candidate target categories are queried, the target speed upper limit and the target speed lower limit of the M candidate target categories are added and averaged to calculate the M speed centers; The speed intervals between the M speed centers and the track speed are calculated one by one, and the candidate target class corresponding to the minimum value of the speed intervals is determined as the target class.

[0008] Further, the correlation result includes a correlation success flag, a correlation success tree structure, a correlation success tree node and a correlation target class. When the target track is not correlated successfully with the temporary track node in the grid set, the correlation success flag, the correlation success tree structure, the correlation success tree node and the correlation target class are combined to form the correlation result. When the target track is correlated successfully with the temporary track node in the grid set, the comprehensive correlation factor needs to be calculated, and the correlation success flag, the correlation success tree structure, the correlation success tree node and the correlation target class corresponding to the maximum value of the comprehensive correlation factor are combined to form the correlation result.

[0009] Further, the calculation method of the comprehensive correlation factor is: Based on the absolute value of the height difference and the height difference reference of the target class, a height correlation factor is calculated; Based on the absolute value of the Doppler difference and the Doppler difference reference of the target class, a Doppler correlation factor is calculated; Based on the time interval and the time reference of the target class, a time correlation factor is calculated; If the temporary track node has a parent node in the tree structure, the absolute value of the speed difference between the target track and the temporary track node is calculated, and the speed difference reference of the target class is compared to calculate a speed correlation factor; The absolute value of the heading difference between the target track and the temporary track node is calculated, and the heading difference reference of the target class is compared to calculate a heading correlation factor; The absolute value of the distance difference between the target track and the temporary track node is calculated, and the distance residual reference of the target class is compared to calculate a distance residual correlation factor; If the height correlation factor, the Doppler correlation factor, the speed correlation factor, the heading correlation factor, the distance residual correlation factor or the time correlation factor is less than 0, the height correlation factor, the Doppler correlation factor, the speed correlation factor, the heading correlation factor, the distance residual correlation factor or the time correlation factor is set to 0; The height correlation factor, the Doppler correlation factor, the speed correlation factor, the heading correlation factor, the distance residual correlation factor and the time correlation factor are respectively assigned to the coefficients corresponding to the target class and added to calculate the comprehensive correlation factor.

[0010] Further, the construction method of the temporary track tree to be processed is: SS1: When the correlation success flag is TRUE, the processing time update flag of the correlation tree structure is parsed; SS3: If the processing time update flag is 0, update the processing time update flag to 1, if the processing time update flag is not 0, do not update the processing time update flag; SS3: A new node is created, the tree where the node is located, the leaf node, the point trace, the target category, the sector index and the distance index are set, the sector index and the distance index are recorded as the node address, and the node address and the node are inserted into the tree where the node is located, and a temporary track tree to be processed is constructed; SS4: When the correlation success flag is FALSE, a new empty tree is created, and SS3 is executed until the update of B correlation results is completed.

[0011] Further, the identification method of the starting node is: The processing time and the update processing time flag of the temporary track tree to be processed which has reached the processing time are both set to 0, and D leaf nodes in the temporary track tree to be processed are marked; All nodes on the path from the leaf node to the root node are set to have participated in track starting, and the target category of the leaf node is identified through the target category number of the leaf node; The number of nodes with the same target category on the path from the leaf node to the root node is counted and recorded as the same value, and the leaf node corresponding to the path with the same value greater than or equal to the calibrated starting threshold is recorded as a verification node, obtaining E verification nodes; Based on the point trace information and target parameters of the E verification nodes, the starting state of the verification node is analyzed, and the verification node with the starting state of available state is recorded as a starting node, obtaining F starting nodes.

[0012] Further, the starting state includes available state and unavailable state; The analysis method of the starting state is: The E verification nodes are linearly fitted to obtain a fitting straight line, and the perpendicular distance from the verification node to the fitting straight line is calculated; When the perpendicular distance is greater than the track automatic starting height threshold, the starting state is recorded as unavailable state; otherwise, the starting state is recorded as available state; According to the tree structure from bottom to top, the position information of the verification node and the next verification node is compared to calculate the adjacent heading difference; When the adjacent heading difference is greater than the track automatic starting heading threshold, the starting state is recorded as unavailable state; otherwise, the starting state is recorded as available state; The position information of the verification node and the next verification node is compared to calculate the radial distance difference; When the radial distance difference is greater than the track automatic starting radial distance threshold, the starting state is recorded as unavailable state; otherwise, the starting state is recorded as available state; Set the starting strategy of the track initiation, the starting state in the clutter area is recorded as an unusable state, otherwise, the starting state is recorded as an available state; The time information and position information of the verification node are compared, the node speed is calculated, and the absolute value of the difference between the node speed of the verification node and the next verification node is calculated to obtain the adjacent speed difference; When the adjacent speed difference is greater than the track automatic initiation speed threshold, the starting state is recorded as an unusable state, otherwise, the starting state is recorded as an available state; The F amplitude information of the verification node is accumulated and averaged to obtain the amplitude value; When the amplitude value is greater than the track automatic initiation amplitude threshold, the starting state is recorded as an unusable state, otherwise, the starting state is recorded as an available state.

[0013] Further, the execution method of the track processing operation is: S04.1: The number of nodes in the to-be-processed temporary track tree that has not reached the processing time is counted, and when the number of nodes is 0, the to-be-processed temporary track tree is deleted; S04.2: When the number of nodes is not 0 and the processing time of the to-be-processed temporary track tree has not been reached, the next to-be-processed temporary track tree that has not reached the processing time is selected, and S04.1-S04.2 are repeatedly executed; S04.3: When the number of nodes is not 0 and the processing time of the to-be-processed temporary track tree has been reached, S03 is executed.

[0014] An electronic device, comprising: a processor and a memory; Wherein the memory stores a computer program that can be called by the processor; The processor executes a tree-based track initiation method by calling the computer program stored in the memory.

[0015] The technical effects of the tree-based track initiation method and the electronic device of the present application are: (1) The present application pre-configures track parameters of multiple different target categories, meets the track initiation operation from low, slow and small targets to high, fast and large targets, avoids the limitations of single type and specific type targets in track initiation, and improves the adaptability of track initiation.

[0016] (2) The application organizes the track that the target may involve by using a tree structure, ensures that each radar point related to a participating point can be a leaf node or a root node of a node in the tree, and can periodically eliminate outdated nodes in the tree structure, thereby accurately determining whether a possible path from a leaf node to a root node can form a track, and finally selecting a path with the largest track formation possibility to start a track, thereby ensuring that a real target can realize track starting effect and effectively suppressing negative interference of a false target on track starting.

[0017] (3) The application can adaptively optimize and adjust parameters in point-point correlation and track starting confirmation according to real-time sensed environmental information, thereby avoiding problems of parameter sensitivity, large calculation amount and poor nonlinear adaptation in track starting depending on expert knowledge, and greatly improving track starting performance in a dynamic complex environment. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 A flowchart of a tree-based track starting method provided for the first embodiment of the application is shown in the figure. Figure 2 A schematic diagram of an electronic device provided for the second embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by a person of ordinary skill in the art without creative labor fall within the protection scope of the application.

[0020] Embodiment one: refer to Figure 1 The tree-based track starting method described in the embodiment includes the following steps. S01: Compare the target point track with a temporary track node in a grid region of a grid set that does not participate in updating, determine the target category of the target point track, and perform point-point correlation on the target point track and the temporary track node that meets the relevant requirements based on the target parameters corresponding to the target category, and formulate the correlation result of the target point track. The target point track is a radar original track that does not participate in track updating and is a direct object for subsequent track starting. In the embodiment, whether the radar original track participates in track updating is determined when determining whether the radar original track is a target point track, and the radar original track that does not participate in track updating is recorded as a target point track.

[0021] After the target track is identified, the number of target tracks is large, in order to facilitate the orderly arrangement of the target track, the target track is stored in a linear table, so as to obtain a track starting track table; The linear table includes but is not limited to linked list, queue and the like.

[0022] The grid area is an area obtained by grid division of the two-dimensional plane of radar scanning, that is, the temporary track position, direction, distance and other information scanned by the radar can be effectively distinguished, so as to divide the overall two-dimensional area into a plurality of adjacent and small area grid areas, and facilitate the orderly comparison and analysis of the temporary track nodes and target nodes in the grid area; The grid set refers to a set composed of grid areas associated with the target track in the distance dimension or the bearing dimension, and serves as an effective range of the temporary track node for subsequent point-by-point correlation operation with the target track; Specifically, the grid area summarizing method is: Mark the center point in the two-dimensional plane area of radar scanning, take the set grid distance length as the distance dimension division standard, take the set grid bearing angle as the bearing dimension division standard, take the center point as the division starting point, and divide the two-dimensional plane area into A grid areas; The set grid distance length and the set grid bearing angle are used to represent the distance span and the coverage angle of a single grid area, that is, to ensure that each grid area can maintain a consistent fan state; The numerical size of the set grid distance length and the set grid bearing angle is set according to actual needs, for example, the set grid distance length is 1 kilometer, and the set grid bearing angle is 5 degrees; The distance from the grid area to the base point is recorded as the first address, the bearing of the grid area is recorded as the second address, and the first address and the second address are combined to generate the grid address of the grid area; The grid address is used to represent the specific position of each grid area relative to the center point, so that all grid areas can be assigned a unique and regular address, facilitating subsequent query and positioning of the grid area; Mark the positions of B target tracks in the A grid areas to obtain the track position; Draw a coverage circle with the track position as the center and 3 times the grid distance length as the radius, record the grid areas inside the coverage circle as target grids, and generate a grid set by summarizing all target grids.

[0023] After the grid set is determined, the real-time state of the temporary track node in the grid set which has not participated in the track starting needs to be analyzed to determine the target category corresponding to the target track; The target category is used to represent different types of aircrafts corresponding to the radar original track, so as to provide diversified reference basis for the type of target track; The target categories include, but are not limited to, low, slow and small targets, high, fast and large targets, etc. In the embodiment, the number of target categories is set according to actual requirements, and each target category corresponds to a unique target category number. For example, the low, slow and small target is a drone, and the high, fast and large target is a civil aviation passenger plane or a fighter.

[0024] Specifically, the determination method of the target category is as follows: The time interval of the target track to the time of the temporary track node is calculated and recorded as the time interval; The distance interval is calculated by subtracting the distance from the target track to the center point from the distance from the temporary track node to the center point and taking the absolute value; The track speed of the target track is calculated by dividing the distance interval by the time interval; The calculation formula of the track speed is as follows: ; In the formula, is the track speed, is the distance interval, is the time interval; M candidate target categories are queried out, which are completely covered by the upper and lower target speed limits of the track speed. The upper and lower target speed limits of the M candidate target categories are added and averaged to calculate the M speed centers; The speed interval between the M speed centers and the track speed is calculated one by one, and the candidate target category corresponding to the minimum value of the speed interval is determined as the target category.

[0025] After the target category of the target track is determined, the target parameters corresponding to the target category of the target track need to be selected and set, so as to realize the point-point correlation operation between the target track and the temporary track node based on the target parameters corresponding to the target category, and lay a foundation for subsequent track initiation; Specifically, the target parameters include, but are not limited to, the target category number, the upper and lower target speed limits, the target speed float, the upper and lower time threshold limits, the upper and lower distance threshold limits, the upper and lower speed threshold limits, the height threshold, the Doppler threshold, the radial distance threshold limit, the timeout threshold, the height difference reference, the Doppler difference reference, the speed difference reference, the heading difference reference, the distance residual reference, the time reference, the height coefficient, the Doppler coefficient, the speed coefficient, the heading coefficient, the distance residual coefficient, the time coefficient, the track automatic initiation heading threshold, the track automatic initiation height threshold, the track automatic initiation radial distance threshold, the track automatic initiation speed threshold, and the track automatic initiation amplitude threshold.

[0026] The number of parameters contained in the target parameters of the target category is adjusted according to the task or user needs in real time, but the target parameters of each target category must contain target category number, target speed upper limit, target speed lower limit and target speed float, and the specific number of target categories is adjusted according to the task or user needs in real time.

[0027] The point-point correlation is a way of node correlation operation between target point traces and temporary track nodes, which can ensure that the target point traces of real targets can participate in track initiation, thereby inhibiting the negative interference of false target point traces. When performing point-point correlation on target point traces and temporary track nodes, the target point traces meeting the correlation requirements need to be identified first, thereby providing a logical basis for subsequent point-point correlation.

[0028] When identifying target point traces meeting the correlation requirements, multiple dimensions of the target point traces need to be comprehensively analyzed. Specifically, the determination method meeting the correlation requirements is: When the time of the target point trace is later than the time of the temporary track node, the target point trace meets the correlation requirements, otherwise, it does not meet the correlation requirements; When the time interval of the target point trace is greater than or equal to the lower limit of the time threshold and less than or equal to the upper limit of the time threshold, the target point trace meets the correlation requirements, otherwise, it does not meet the correlation requirements; When the interval distance of the target point trace is greater than or equal to the lower limit of the distance threshold and less than or equal to the upper limit of the distance threshold, the target point trace meets the correlation requirements, otherwise, it does not meet the correlation requirements; When the point trace speed of the target point trace is greater than or equal to the lower limit of the speed threshold and less than or equal to the upper limit of the speed threshold, the target point trace meets the correlation requirements, otherwise, it does not meet the correlation requirements; When the target point trace and the temporary track node both have altitudes, the absolute value of the difference between the altitudes of the target point trace and the temporary track node is obtained, if the absolute value of the altitude difference is greater than the altitude threshold, the target point trace meets the correlation requirements, otherwise, it does not meet the correlation requirements; When the target point trace and the temporary track node both have Dopplers, the absolute value of the difference between the Dopplers of the target point trace and the temporary track node is obtained, if the absolute value of the Doppler difference is greater than the Doppler threshold, the target point trace meets the correlation requirements, otherwise, it does not meet the correlation requirements; The absolute value of the radial distance difference between the target point trace and the temporary track node is calculated, when the absolute value of the radial distance difference is greater than or equal to the lower limit of the radial distance and less than or equal to the upper limit of the radial distance, the target point trace meets the correlation requirements, otherwise, it does not meet the correlation requirements.

[0029] The correlation result is used to represent point-to-point correlation between the target track and the temporary track node, and reflects the correlation between the target track and the temporary track node. Specifically, the correlation result includes a correlation success flag, a correlation success tree structure, a correlation success tree node, and a correlation target category.

[0030] The correlation success flag is used to represent whether the target track and the temporary track node in the grid set are successfully correlated. In this embodiment, when the target track and the temporary track node are successfully correlated, the correlation success flag is set to FALSE; when the target track and the temporary track node are not successfully correlated, the correlation success flag is set to TRUE.

[0031] The correlation success tree structure is used to represent the numerical value of the tree structure of the successful correlation between the target track and the temporary track node in the grid set. For example, the correlation success tree structure can be set to NULL or CT.

[0032] The correlation success tree node is used to represent the number of nodes of the tree structure of the successful correlation between the target track and the temporary track node in the grid set. For example, the correlation success tree node can be set to NULL or CTN.

[0033] The correlation target category is used to represent the real target category of the target track. When determining the correlation target category, if the temporary track node has a parent node in the tree structure, the target category is recorded as the correlation target category; if the temporary track node does not have a parent node in the tree structure, the target categories corresponding to the height difference reference, the Doppler difference reference, the time reference, the speed difference reference, the heading difference reference, and the speed residual reference are recorded as the correlation target category.

[0034] When formulating the correlation result, if the target track is not successfully correlated with the temporary track node in the grid set, the correlation success flag is FALSE, the correlation success tree structure is NULL, the correlation success tree node is NULL, and the correlation target category is 0, so the correlation result is (FALSE, NULL, NULL, 0); if the target track is successfully correlated with the temporary track node in the grid set, the comprehensive correlation factor needs to be calculated, and the correlation success flag, the correlation success tree structure, the correlation success tree node, and the correlation target category corresponding to the maximum value of the comprehensive correlation factor are combined to form the correlation result, so the correlation result is (TRUE, CT, CTN, targetIndex).

[0035] Specifically, the comprehensive correlation factor is used to represent the numerical value of the correlation degree between the target parameters of the target track and the temporary track node. The calculation method of the comprehensive correlation factor is as follows: Based on the height difference absolute value and the height difference reference of the target category, the height correlation factor is calculated. The calculation formula of the height correlation factor is: ; In the formula, is the height correlation factor, is the absolute value of the height difference, is the height difference reference; The Doppler correlation factor is calculated based on the absolute value of the Doppler difference and the Doppler difference reference of the target category; The calculation formula of the Doppler correlation factor is: ; In the formula, is the Doppler correlation factor, is the absolute value of the Doppler difference, is the Doppler difference reference; The time correlation factor is calculated based on the time interval and the time reference of the target category; The calculation formula of the time correlation factor is: ; In the formula, is the time correlation factor, is the time interval, is the time reference; If the temporary track node has a parent node in the tree structure, the absolute value of the speed difference between the target track and the temporary track node is calculated, and the absolute value of the speed difference is compared with the speed difference reference of the target category to calculate the speed correlation factor; The calculation formula of the speed correlation factor is: ; In the formula, is the speed correlation factor, is the absolute value of the speed difference, is the speed difference reference; The absolute value of the heading difference between the target track and the temporary track node is calculated, and the absolute value of the heading difference is compared with the heading difference reference of the target category to calculate the heading correlation factor; The calculation formula of the heading correlation factor is: ; In the formula, is the heading correlation factor, is the absolute value of the heading difference, is the heading difference reference; The absolute value of the distance difference between the target track and the temporary track node is calculated, and the absolute value of the distance difference is compared with the distance residual reference of the target category to calculate the distance residual correlation factor; The calculation formula of the distance residual correlation factor is: ; wherein, is a distance residual correlation factor, is a distance difference absolute value, is a distance residual reference; if the height correlation factor, the Doppler correlation factor, the speed correlation factor, the heading correlation factor, the distance residual correlation factor or the time correlation factor is less than 0, the height correlation factor, the Doppler correlation factor, the speed correlation factor, the heading correlation factor, the distance residual correlation factor or the time correlation factor is set to 0; the height correlation factor, the Doppler correlation factor, the speed correlation factor, the heading correlation factor, the distance residual correlation factor and the time correlation factor are respectively assigned to the corresponding coefficients of the target category and added, and the comprehensive correlation factor is calculated; the calculation formula of the comprehensive correlation factor is: ; wherein, is a comprehensive correlation factor, is a height coefficient, is a Doppler coefficient, is a time coefficient, is a speed coefficient, is a heading coefficient, is a distance residual coefficient.

[0036] Based on the above point-to-point correlation operation of the target track and the temporary track node, the target parameters of the B target tracks and the temporary track nodes in the grid set are correlated one by one in the order of radar scanning, so as to obtain B correlation results.

[0037] S02: updating the correlation results according to the correlation success flag, and constructing a to-be-processed temporary track tree; After obtaining the correlation results of the target track, the correlation success flag in the correlation results needs to be analyzed and judged, and according to the difference of the correlation success flag, the correlation results are updated and processed, so that the target track can be dynamically and continuously updated along the time line with the temporary track node, avoiding the lag problem existing in the parameter calculation of static point-to-point correlation, thereby improving the adaptability to variable speed targets and non-linear target starting.

[0038] The to-be-processed temporary track tree is a tree structure that can provide accurate and dynamic node positions for subsequent track starting, ensuring the reliability of the subsequent track starting results; Specifically, the construction method of the to-be-processed temporary track tree is: SS1: when the correlation success flag is TRUE, the processing time update flag of the correlation tree structure is analyzed; SS3: If the processing time update flag is 0, update the processing time update flag to 1, if the processing time update flag is not 0, do not update the processing time update flag; SS3: A new node is created, the tree where the node is located, the leaf node, the track, the target category, the sector index and the distance index are set, the sector index and the distance index are recorded as the node address, and the node address and the node are inserted into the tree where the node is located, and a temporary track tree to be processed is constructed; SS4: When the correlation success flag is FALSE, a new empty tree is created, and SS3 is executed until the update of B correlation results is completed.

[0039] It should be noted that the number of temporary track trees to be processed is not only one, when multiple temporary track trees to be processed are constructed, all temporary track trees to be processed can be imported into a linear list, thereby forming a temporary track tree linear list to be processed.

[0040] S03: Identify the verification node from the temporary track tree to be processed with the processing time, record the verification node with the starting state as the available state as the starting node, and perform track starting in sequence according to the starting node; The starting node is a node in the temporary track tree to be processed that can be used as a subsequent track starting node, which can ensure the integrity and continuity of track starting, and lay the foundation for track starting; Since the starting node is identified and marked from the nodes in the temporary track tree to be processed, when identifying and marking the starting node, it is necessary to judge whether the temporary track tree to be processed meets the track starting requirement, and identify the starting node from the temporary track tree to be processed that meets the track starting requirement; Specifically, the track starting requirement is that the processing time of the temporary track tree to be processed has arrived; when the processing time of the temporary track tree to be processed has not arrived, the temporary track tree to be processed is removed from the temporary track tree linear list to be processed and inserted into the temporary track tree linear list to be processed that has not arrived.

[0041] Specifically, the identification method of the starting node is: The processing time of the temporary track tree to be processed and the update processing time flag are both set to 0, and D leaf nodes in the temporary track tree to be processed are marked; All nodes on the path from the leaf node to the root node are set to have participated in track starting, and the target category of the leaf node is identified through the target category number of the leaf node; Counting the number of nodes with the same target category on the path from the leaf node to the root node, and recording the number as the same value, and recording the leaf node corresponding to the path with the same value greater than or equal to the calibrated starting threshold value as a verification node, to obtain E verification nodes; the calibrated starting threshold value is the minimum value of the number of nodes meeting the track starting operation, to ensure that each track starting can have a sufficient number of nodes; according to the actual track starting, a track starting needs at least 3 nodes, therefore, the minimum value of the calibrated starting threshold value is 3; Based on the point trail information and target parameters of the E verification nodes, the starting state of the verification node is analyzed, and the verification node with the starting state as available is recorded as a starting node, to obtain F starting nodes.

[0042] It should be noted that the starting state is used to indicate whether the verification node can be used as a state for performing track starting, and can distinguish the verification node into two states of being able to perform track starting and being unable to perform track starting; specifically, the starting state includes an available state and an unavailable state.

[0043] When analyzing the starting state of the verification node, the point trail information and target parameters of the verification node need to be calculated and analyzed, wherein the point trail information is used to comprehensively represent the time information, position information, amplitude information, Doppler information and other information of the verification node in the to-be-processed temporary track tree; Specifically, the analysis method of the starting state is: The E verification nodes are linearly fitted to obtain a fitting straight line, and the perpendicular distance of the verification node to the fitting straight line is calculated; When the perpendicular distance is greater than the track automatic starting height threshold, the starting state of the verification node is recorded as an unavailable state; when the perpendicular distance is less than or equal to the track automatic starting height threshold, the starting state of the verification node is recorded as an available state; According to the tree structure from bottom to top, the position information of the verification node and the next verification node is compared to calculate the adjacent heading difference; When the adjacent heading difference is greater than the track automatic starting heading threshold, the starting state of the verification node is recorded as an unavailable state; when the adjacent heading difference is less than or equal to the track automatic starting heading threshold, the starting state of the verification node is recorded as an available state; The position information of the verification node and the next verification node is compared to calculate the radial distance difference; When the radial distance difference is greater than the track automatic starting radial distance threshold, the starting state of the verification node is recorded as an unavailable state; when the radial distance difference is less than or equal to the track automatic starting radial distance threshold, the starting state of the verification node is recorded as an available state; A starting strategy for starting a track is set, a starting state of a verification node located in a clutter region is recorded as an unusable state, and a starting state of a verification node located outside the clutter region is recorded as an available state; the starting strategy is a limiting rule for starting quality and point position of a starting node for starting a track, and ensures that the starting node participating in starting a track is not located in the clutter region; for example, the starting strategy is that the starting node participating in starting a track is located outside the clutter region; The time information and the position information of the verification node are compared, the node speed is calculated, and the absolute value of the difference between the node speed of the verification node and the node speed of the next verification node is calculated to obtain the adjacent speed difference; When the adjacent speed difference is greater than a track automatic starting speed threshold, the starting state of the verification node is recorded as the unusable state; when the adjacent speed difference is less than or equal to the track automatic starting speed threshold, the starting state of the verification node is recorded as the available state; The F amplitude information of the verification node is accumulated and averaged to obtain an amplitude value; When the amplitude value is greater than a track automatic starting amplitude threshold, the starting state of the verification node is recorded as the unusable state; when the amplitude value is less than or equal to the track automatic starting amplitude threshold, the starting state of the verification node is recorded as the available state.

[0044] After the starting state of the verification node is identified, the verification node with the available starting state can be marked as a starting node, so that the starting node can serve as a track point for subsequent track starting.

[0045] After the starting node is obtained, all the starting nodes need to be arranged in sequence, and the starting nodes are subjected to track starting according to the arrangement order, so that an efficient and accurate track starting effect is achieved. Specifically, the method for starting a track is as follows: The node speeds of the starting node and the next starting node are combined to form a speed sequence, and the speed variance of the speed sequence is calculated based on a variance formula; The F starting nodes are arranged in sequence in the order of increasing speed variance, and after the repeated starting nodes are removed, the remaining starting nodes are subjected to track starting in sequence.

[0046] S04: Track starting analysis is performed on the to-be-processed temporary track trees that have not reached the processing time, and corresponding track processing operations are performed; In the above steps, only the starting nodes in the to-be-processed temporary track trees that have reached the processing time can be analyzed and identified, and the starting nodes in the to-be-processed temporary track trees are subjected to track starting, and the to-be-processed temporary track trees that have not reached the processing time are not subjected to track starting operations, therefore, corresponding operations for track starting of the to-be-processed temporary track trees are needed; When analyzing whether to start a track for the to-be-processed temporary track tree that has not reached the processing time, the to-be-processed temporary track tree is analyzed for track starting, and according to the analysis result of the track starting, a corresponding track processing operation is performed; Specifically, the execution method of the track processing operation is as follows: S04.1: The number of nodes in the to-be-processed temporary track tree that has not reached the processing time is counted, and when the number of nodes is 0, the to-be-processed temporary track tree is deleted; S04.2: When the number of nodes is not 0 and the to-be-processed temporary track tree has not reached the processing time, the next to-be-processed temporary track tree that has not reached the processing time is selected, and S04.1-S04.2 are repeatedly executed; S04.3: When the number of nodes is not 0 and the to-be-processed temporary track tree has reached the processing time, S03 is executed.

[0047] In this embodiment, by performing the track starting operation on the to-be-processed temporary track tree that has not reached the processing time, it is ensured that all to-be-processed temporary track trees that meet the track starting can participate in the track starting operation, thereby ensuring the accuracy of the final track starting result.

[0048] S05: An adjustment mode of the to-be-processed temporary track tree is selected, and the structure of the to-be-processed temporary track tree is adjusted according to the adjustment mode; The adjustment mode is a specific mode for optimizing and maintaining the nodes of the tree structure of the to-be-processed temporary track tree, that is, the tree structure of different to-be-processed temporary track trees can be adjusted accordingly; Specifically, the adjustment mode includes a direct adjustment mode and an indirect adjustment mode. When selecting the adjustment mode, it is necessary to identify whether the starting node of the to-be-processed temporary track tree has participated in forming the track starting, and when the starting node has participated in forming the track starting, the direct adjustment mode is selected; if the current time is later than the processing time of the starting node, and the time difference between the current time and the processing time of the starting node is greater than the timeout threshold, the indirect adjustment mode is selected.

[0049] After the direct adjustment mode or the indirect adjustment mode is selected, the structure of the to-be-processed temporary track tree is adjusted according to the different adjustment modes, so as to eliminate the starting nodes that are not used in the to-be-processed temporary track tree, thereby optimizing the structure of the to-be-processed temporary track tree; Specifically, the structure adjustment method of the to-be-processed temporary track tree is as follows: When the direct adjustment mode is selected, the temporary track node corresponding to the starting node is deleted from the grid area, and the starting node is deleted from the to-be-processed temporary track tree, and the tree structure of the to-be-processed temporary track tree is adjusted; When the indirect adjustment mode is selected, the point trail space pointed by the starting node is released, and the temporary track node corresponding to the starting node is deleted from the grid area, and the tree structure of the to-be-processed temporary track tree is adjusted.

[0050] After the tree structure adjustment of the to-be-processed temporary track tree is performed, a complete track starting can be realized at this time, and when the next track starting is performed, it is needed to return to S01 and repeatedly perform all the steps again.

[0051] Embodiment 2, please refer to Figure 2 As shown in the figure, the embodiment discloses an electronic device, comprising a processor and a memory; Wherein, the memory stores a computer program that can be called by the processor; The processor executes the computer program stored in the memory to realize the tree-based track starting method.

[0052] Since the electronic device introduced in the embodiment is the electronic device used to implement the tree-based track starting method in the embodiment 1 of the present application, the specific implementation of the electronic device in the embodiment and its various forms can be understood by those skilled in the art based on the tree-based track starting method introduced in the embodiment. Therefore, how the electronic device realizes the method in the embodiment will not be introduced in detail. As long as the electronic device used to implement the tree-based track starting method in the embodiment is implemented by those skilled in the art, it belongs to the scope of protection of the present application.

[0053] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited to this. Any skilled person in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered within the protection scope of the present application.

Claims

1. A tree-based method for initiating a flight path, characterized in that, include: S01: The divided grid regions are aggregated into a grid set. The temporary track nodes in the grid set are compared with the target points to determine the target category and target parameters of the target points. The target points that meet the relevant requirements are correlated with the temporary track nodes to formulate the relevant results of the target points. S02: Based on the relevant success indicators of the relevant results, update the relevant results and construct a temporary track tree to be processed; S03: Identify verification nodes from the pending temporary track tree that has reached its processing time, select starting nodes from the verification nodes based on the starting state of the verification nodes, and start the track of the starting nodes in sequence according to the relationship between the velocity variance of the starting node and the next starting node. S04: Perform track initiation analysis on the pending temporary track trees that have not yet reached their processing time, and execute the corresponding track processing operation based on the track initiation analysis results; S05: Select the direct adjustment mode or the indirect adjustment mode, and adjust the structure of the temporary track tree to be processed by deleting the temporary track node corresponding to the starting node in the grid area and releasing the track space pointed to by the starting node.

2. The tree-based trajectory initiation method according to claim 1, characterized in that, The method for summarizing grid regions is as follows: Mark the center point in the two-dimensional plane area scanned by the radar, use the set grid distance length as the standard for dividing the distance dimension, use the set grid azimuth angle as the standard for dividing the azimuth dimension, and use the center point as the starting point for dividing, and divide the two-dimensional plane area into A grid areas. Mark the locations of B target points within grid area A to obtain the point locations; Draw a covering circle with the point location as the center and a radius of 3 times the grid distance. The grid area inside the covering circle is recorded as the target grid. After summing all the target grids, a grid set is generated.

3. The tree-based path initiation method according to claim 2, characterized in that, The method for determining the target category is as follows: The time interval between the time of the target point and the time of the temporary track node is calculated and recorded as the time interval. The distance interval is calculated by subtracting the distance from the target point to the center point from the distance from the temporary track node to the center point and taking the absolute value. Divide the distance interval by the time interval to calculate the velocity of the target point. Find M candidate target categories whose target speed upper and lower limits completely cover the point speed. Add the target speed upper and lower limits of the M candidate target categories and calculate the average to find the M speed centers. Calculate the velocity interval between each of the M velocity centers and the velocity of the point trace, and determine the candidate target category corresponding to the minimum velocity interval as the target category.

4. The tree-based trajectory initiation method according to claim 3, characterized in that, The relevant results include relevant success indicators, relevant success tree structure, relevant success tree nodes, and relevant target categories; When formulating relevant results, if the target point is not successfully associated with a temporary track node in the grid set, the relevant success flag, the relevant success tree structure, the relevant success tree node, and the relevant target category are combined into relevant results; If the target point is successfully correlated with a temporary track node in the grid set, a comprehensive correlation factor needs to be calculated, and the correlation success flag corresponding to the maximum value of the comprehensive correlation factor, the correlation success tree structure, the correlation success tree node, and the correlation target category are combined to form the correlation result.

5. The tree-based trajectory initiation method according to claim 4, characterized in that, The calculation method for comprehensive correlation factors is as follows: The height correlation factor is calculated based on the absolute value of the height difference and the height difference benchmark of the target category; The Doppler correlation factor is calculated based on the absolute value of the Doppler difference and the Doppler difference benchmark of the target category; Based on the time reference of the time interval and the target category, the time correlation factor is calculated; If the temporary track node has a parent node in the tree structure, calculate the absolute value of the speed difference between the target track and the temporary track node, and compare the absolute value of the speed difference with the speed difference benchmark of the target category to calculate the speed correlation factor. Calculate the absolute value of the heading difference between the target point and the temporary track node, and compare the absolute value of the heading difference with the heading difference benchmark of the target category to calculate the navigation-related factor; Calculate the absolute value of the distance difference between the target point and the temporary track node, and compare the absolute value of the distance difference with the distance residual benchmark of the target category to calculate the distance residual correlation factor; If the altitude correlation factor, Doppler correlation factor, velocity correlation factor, heading correlation factor, distance residual correlation factor, or time correlation factor is less than 0, set the altitude correlation factor, Doppler correlation factor, velocity correlation factor, heading correlation factor, distance residual correlation factor, or time correlation factor to 0; The comprehensive correlation factor is calculated by assigning coefficients to the target category for each of the following factors: height correlation factor, Doppler correlation factor, velocity correlation factor, heading correlation factor, distance residual correlation factor, and time correlation factor, and then summing them together.

6. The tree-based path initiation method according to claim 5, characterized in that, The method for constructing the temporary track tree to be processed is as follows: SS1: When the relevant success flag is TRUE, parse out the processing time update flag of the relevant tree structure; SS3: If the processing time update flag is 0, update the processing time update flag to 1; if the processing time update flag is not 0, do not update the processing time update flag. SS3: Create a new node, set the tree in which the node is located, leaf nodes, track, target category, sector index and distance index, record the sector index and distance index as the node address, and insert the node address and the node into the tree in which it is located to construct the temporary track tree to be processed; SS4: When the relevant success flag is FALSE, create a new empty tree and execute SS3 until the updates of B relevant results are completed.

7. The tree-based trajectory initiation method according to claim 6, characterized in that, The method for identifying the starting node is as follows: Set the processing time and update processing time flags of the pending temporary track trees that have reached their processing time to 0, and mark the D leaf nodes in the pending temporary track trees. Set all nodes on the path from the leaf node to the root node to be those that have participated in the start of the track, and identify the target category of the leaf node by the target category number of the leaf node. The number of nodes with the same target category on the path from the leaf node to the root node is counted and recorded as the same value. The leaf nodes corresponding to the paths with the same value greater than or equal to the calibrated starting threshold are recorded as verification nodes, and E verification nodes are obtained. Based on the trace information of E verification nodes and the target parameters, the initial state of the verification nodes is analyzed, and the verification nodes whose initial state is available are recorded as the starting nodes, thus obtaining F starting nodes.

8. The tree-based path initiation method according to claim 7, characterized in that, The initial state includes an available state and an unavailable state; The method for analyzing the initial state is as follows: Perform a straight line fitting on the E verification nodes to obtain the fitted line, and calculate the vertical distance from the verification nodes to the fitted line. When the vertical distance is greater than the automatic start altitude threshold of the track, the start state is recorded as unavailable; otherwise, the start state is recorded as available. Following the tree structure from bottom to top, the position information of the verification node is compared with that of the next verification node to calculate the difference in adjacent headings; When the difference between adjacent headings is greater than the automatic starting heading threshold, the starting state is recorded as unavailable; otherwise, the starting state is recorded as available. The radial distance difference is calculated by comparing the position information of the verification node with that of the next verification node. When the radial distance difference is greater than the automatic start radial distance threshold of the track, the starting state is recorded as unavailable; otherwise, the starting state is recorded as available. Set the initial strategy for the start of the track, and record the initial state located in the clutter area as an unavailable state, and vice versa, record the initial state as an available state. The time and location information of the verification node are compared to calculate the node speed. The absolute value of the difference between the speed of the verification node and the speed of the next verification node is calculated to calculate the speed difference between adjacent nodes. When the speed difference between adjacent speeds is greater than the automatic start speed threshold of the track, the start state is recorded as unavailable; otherwise, the start state is recorded as available. The amplitude value is obtained by summing the F amplitude information of the verification node and averaging them. When the amplitude value is greater than the automatic start amplitude threshold of the track, the start state is recorded as unavailable; otherwise, the start state is recorded as available.

9. The tree-based path initiation method according to claim 8, characterized in that, The execution method for track processing operations is as follows: S04.1: Count the number of nodes in the pending temporary track tree that has not yet reached its processing time. When the number of nodes is 0, delete the pending temporary track tree. S04.2: When the number of nodes is not 0 and the processing time for the pending temporary track tree has not yet expired, select the next pending temporary track tree that has not yet expired and repeat S04.1-S04.

2. S04.3: When the number of nodes is not 0 and the processing time for the pending temporary track tree has arrived, execute S03.

10. An electronic device, comprising: Processor and memory; The memory stores computer programs that can be called by a processor; The processor executes a tree-based trajectory initiation method according to any one of claims 1-9 by calling a computer program stored in the memory.

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