CN-122017821-A - Multi-target tracking resource dynamic allocation system and method for multi-area array phased array radar

CN122017821ACN 122017821 ACN122017821 ACN 122017821ACN-122017821-A

Abstract

The invention discloses a multi-target tracking resource dynamic allocation system and a method for a multi-area array phased array radar, which relate to the technical field of radar systems and comprise the following steps: judging whether a plurality of low-speed small targets exist to cause the tracking load of the system to exceed a stable work load threshold value, and if so, collecting motion state vectors of all detection targets in each radar scanning period; generating a dynamic group set based on the motion state vector; when encountering large-scale low-speed small target saturation attack, the system can be converted from an unsustainable load state for tracking massive independent targets to a stable load state for tracking a few virtual large targets, so that overload breakdown of the system caused by the fact that the tracking load exceeds a stable work load threshold is prevented, and survivability and continuous combat capability of the system under a high-strength combat environment are improved; on the premise of ensuring the control of the overall situation of the cluster, the utilization efficiency of the beam resources and the computing resources of the multi-area array phased array radar is optimized.

Inventors

LIU XUEPENG
LIAO GUISHENG
ZHANG ZEXIN
LIU QIYUAN
Tan Pugang
HU DIE
LI JIECHEN

Assignees

浙江蓝箭防务科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260414

Claims (10)

1. The multi-target tracking resource dynamic allocation method for the multi-area array phased array radar is characterized by comprising the following steps of: judging whether a plurality of low-speed small targets exist or not to cause the system tracking load to exceed a stable work load threshold value, and if so: The method comprises the steps of collecting motion state vectors of all detection targets in each radar scanning period, generating a dynamic group set based on the motion state vectors, combining the motion state vectors of all member targets in each dynamic group based on three-dimensional position coordinates of all member targets in the dynamic group set to obtain motion state vectors of virtual large targets; The method comprises the steps of distributing single radar tracking beam resources for each virtual large target based on the virtual large target motion state vector, collecting real-time motion state vectors of each member target in a dynamic group based on the single radar tracking beam resources, judging whether the dynamic group is differentiated based on the real-time motion state vectors of each member and the group overall prediction track, and if so, judging whether the dynamic group is differentiated or not: Identifying differentiated member targets, carrying out sub-group re-division by adopting an online clustering algorithm based on the motion state vector of the differentiated member targets to obtain the division result of the new sub-group, creating a new virtual large target for each new sub-group based on the division result of the new sub-group, and reallocating radar tracking beam resources.
2. The method for dynamically allocating multi-target tracking resources of a multi-array phased array radar according to claim 1, wherein the method for generating the dynamic group set comprises: Calculating an instantaneous motion trail of each target based on the motion state vector of each target; according to the instantaneous motion trail of the targets, calculating a cosine value of a heading angle between any two targets and a correlation coefficient of a position sequence; Based on the cosine value of the course included angle and the correlation coefficient of the position sequence, a dynamic group set is generated by combining a preset path similarity threshold value.
3. The method for dynamically allocating multi-target tracking resources of a multi-array phased array radar according to claim 1, wherein the method for determining whether a plurality of slow small targets exist to cause a system tracking load to exceed a steady workload threshold comprises: Acquiring the number of targets produced in real time in a radar signal processing chain, the beam resource occupation proportion, the node utilization rate and the update period of an average tracking track, and calculating the instantaneous load coefficient of the current multi-array phased array radar based on the acquired information; obtaining a system load overrun mark based on the instantaneous load coefficient and a preset stable work load threshold; The method comprises the steps of collecting radar cross section measurement values and three-dimensional movement speed scalar values of tracked targets, obtaining type membership of each target based on the radar cross section measurement values, obtaining movement characteristic conformity of each target based on the three-dimensional movement speed scalar values and combining typical speed ranges of low-speed small targets; and based on the total number of the low-speed and small targets, combining the scale threshold of the cluster attack to obtain the target cluster threat sign.
4. The method for dynamically allocating multi-target tracking resources of a multi-array phased array radar according to claim 1, wherein the method for generating a group overall predicted trajectory based on a motion state vector of a virtual large target comprises: Based on the motion state vector of the virtual large target, extracting to obtain a three-dimensional position coordinate component and a three-dimensional speed vector component; based on the three-dimensional position coordinate component and the three-dimensional speed vector component, combining the measurement error characteristic parameters of the multi-area array phased array radar to obtain a state prediction sequence of the virtual large target; Based on the state prediction sequence, extracting a three-dimensional position coordinate predicted value corresponding to each prediction moment, and connecting to form a continuous space curve according to the three-dimensional position coordinate predicted value to obtain a geometric path of the group overall prediction track; Calculating the arrival time marks of each point on the track based on the geometric path of the group integral prediction track and combining the current motion state vector of the virtual large target; based on the geometric path and the arrival time stamp, outputting to obtain a group overall predicted track.
5. The method for dynamically allocating multi-target tracking resources for a multi-array phased array radar according to claim 4, wherein the method for obtaining the state prediction sequence of the virtual large target based on the three-dimensional position coordinate component and the three-dimensional speed vector component and by combining the measurement error characteristic parameters of the multi-array phased array radar comprises the following steps: Based on the three-dimensional position coordinate component and the three-dimensional speed vector component, obtaining a system state vector of the virtual large target; based on the historical motion state vector sequence, combining a state equation of the Kalman filtering predictor to obtain a process noise covariance matrix estimation value of the Kalman filtering predictor; And operating a prediction step of a Kalman filter predictor based on the complete parameter set to obtain a state prediction sequence of the virtual large target.
6. The method for dynamically allocating multi-target tracking resources of a multi-array phased array radar according to claim 1, wherein the method for obtaining the motion state vector of the virtual large target comprises the following steps: Calculating the geometric centroid position of each dynamic group according to the three-dimensional position coordinates of all member targets in the dynamic group set; And based on the geometric centroid position, combining the motion state vectors of all member targets to obtain the motion state vector of the virtual large target.
7. The method for dynamically allocating multi-target tracking resources for a multi-array phased array radar according to claim 1, wherein the method for judging whether the dynamic group is differentiated comprises the following steps: Calculating the deviation degree of the group overall prediction track based on the real-time motion state vector of each member and the group overall prediction track; comparing the deviation degree of the overall prediction track based on the group with a preset deviation degree threshold value; If the deviation degree of the overall prediction track of the group is larger than a preset deviation degree threshold value, the dynamic group is differentiated.
8. The multi-object tracking resource dynamic allocation method of the multi-object array phased array radar of claim 1, wherein the method for carrying out sub-group repartition by adopting an online clustering algorithm based on the motion state vector of the differentiated member object to obtain the partition result of the new sub-group comprises the following steps: Based on the motion state vector set, extracting to obtain a three-dimensional position coordinate and a three-dimensional speed vector of each differentiated member target; calculating the instantaneous relative distance and the instantaneous velocity vector included angle cosine value between any two differentiated member targets according to the three-dimensional position coordinates and the three-dimensional velocity vector of each differentiated member target; based on the motion similarity matrix, setting a neighborhood searching radius and a minimum membership threshold of an online clustering algorithm by combining with real-time calculation resource margin parameters of the current multi-area array phased array radar; Performing cluster analysis on the differentiated member targets by running an online clustering algorithm to obtain cluster labels, obtaining a preliminary cluster partitioning result of the differentiated member targets according to the cluster labels, and counting the number and the space scattering range of the member targets in each cluster based on the preliminary cluster partitioning result; and according to the number and the spatial dispersion range of the member targets in each cluster, combining the stability criteria of the new-born subgroup to obtain the dividing result of the new-born subgroup.
9. The method for dynamically allocating multi-target tracking resources of a multi-surface array phased array radar according to claim 8, wherein the method for obtaining the division result of the new-born subgroup by combining the stability criterion of the new-born subgroup according to the number of the member targets in each cluster and the space dispersion range comprises the following steps: Based on the number of members of each cluster, combining a preset minimum effective member number threshold to obtain a candidate cluster set; based on the spatial spreading range of each cluster in the candidate cluster set, combining a preset maximum allowable spreading radius to obtain a primary stable cluster set; calculating the speed consistency index of the members in the cluster according to the member motion state vector of each cluster in the primary stable cluster set; Based on the speed consistency index, combining a preset speed consistency threshold value to obtain a final stable cluster set; and collecting cluster labels of the final stable cluster set, remapping the cluster labels into new sub-group identifiers, and outputting a dividing result of the new sub-groups.
10. A multi-target tracking resource dynamic allocation system of a multi-area array phased array radar, which is used for realizing the multi-target tracking resource dynamic allocation method of the multi-area array phased array radar according to any one of claims 1 to 9, and is characterized by comprising the following steps: the system load monitoring and triggering module is used for judging whether a plurality of low-speed small targets exist or not to cause the system tracking load to exceed a stable work load threshold value; The system comprises a dynamic aggregation and virtual target generation module, a group integral prediction track generation module and a group integral prediction track generation module, wherein the dynamic aggregation and virtual target generation module is used for collecting motion state vectors of all detection targets in each radar scanning period, generating a dynamic group set based on the motion state vectors, combining the motion state vectors of all member targets in each dynamic group based on three-dimensional position coordinates of all member targets in the dynamic group set, and obtaining the motion state vector of a virtual large target; The system comprises a tracking execution and state monitoring module, a dynamic group and a group prediction module, wherein the tracking execution and state monitoring module is used for distributing single radar tracking beam resources for each virtual large target based on the motion state vector of the virtual large target, collecting real-time motion state vectors of targets of all members in the dynamic group based on the single radar tracking beam resources, and judging whether the dynamic group is differentiated based on the real-time motion state vectors of all members and the overall prediction track of the group; The system comprises a differentiation processing and resource reallocation module, a radar tracking beam resource allocation module and a radar tracking beam resource allocation module, wherein the differentiation processing and resource reallocation module is used for identifying differentiated member targets when dynamic groups are differentiated, performing sub-group repartition by adopting an online clustering algorithm based on motion state vectors of the differentiated member targets to obtain a new sub-group partitioning result, and creating a new virtual large target for each new sub-group based on the new sub-group partitioning result.

Description

Multi-target tracking resource dynamic allocation system and method for multi-area array phased array radar Technical Field The invention relates to the technical field of radar systems, in particular to a multi-target tracking resource dynamic allocation system and method for a multi-area array phased array radar. Background When facing a large number of targets, the current multi-array phased array radar often adopts a multi-target tracking resource allocation technical scheme based on fixed priority or polling scheduling. The core principle of the technology is that when a tracking resource scheduling model of the multi-array phased array radar is constructed, in order to simplify scheduling logic and reduce the calculation complexity of real-time decision to meet the requirements of the multi-array phased array radar on high data rate and low time delay, the tracking priorities of different target types are usually preset, or the limited wave beams and calculation resources of the system are circularly distributed to each discovered target according to a fixed sequence, and the tracking maintenance of the multi-target is completed by depending on the static or quasi-static distribution strategy. However, in an actual battlefield environment, particularly when dealing with large-scale clustered attacks of low-speed and small targets such as unmanned aerial vehicles, targets in the threat space tend to exhibit significant clustered features. Tens or even hundreds of clustered targets with highly correlated motion tracks and dense spatial distribution can exist in the same monitoring space, and each target is regarded as a completely independent individual to perform resource allocation by the traditional technical scheme. The technology adopts a fixed and invariable scheduling strategy to process, when the cluster saturation attack scene with the rapid increase of the number of targets is processed, the stiff independent allocation strategy can continuously consume the intense wave beam and computing resources to lead the system tracking load to rise sharply aiming at a large number of targets with similar movements in the cluster, and the static allocation strategy can not quickly sense and re-track the resources to lead the tracking response of a new threat subgroup to be delayed aiming at tactical maneuver or structure differentiation of the whole cluster. The problem directly has a serious influence on the continuous monitoring capability and the defense stability of the multi-area array phased array radar. Under the saturation attack scene, the system capacity can be rapidly exhausted by independently distributing resources for each target, so that the overall update rate of the system is reduced, even the key target track is lost due to overload, and when the cluster is differentiated, the system cannot timely distribute special tracking resources for the differentiated subgroup due to the stiffness of the resource scheduling, thereby causing the tracking interruption and situation awareness gap of the new threat. The situation can not only reduce the resource utilization efficiency and the tracking efficiency of the multi-array phased array radar, but also directly weaken the capability of a defense system for dealing with cluster threats, increase the fight risks such as target missing and situation misjudgment, and can not meet the core requirements of the modern defense system for realizing efficient and stable multi-target tracking of the multi-array phased array radar under complex countermeasure environments. Disclosure of Invention The invention aims to solve the problems that when a multi-array phased array radar is used for coping with large-scale low-speed small-target saturation attack, the system tracking load exceeds a stable work load threshold value and cluster differentiation tracking response is delayed due to the adoption of a static resource allocation strategy, and provides a novel multi-array phased array radar multi-target tracking resource dynamic allocation system and method. In order to achieve the purpose, the invention adopts the following technology that the multi-object tracking resource dynamic allocation method of the multi-area array phased array radar comprises the following steps: judging whether a plurality of low-speed small targets exist or not to cause the system tracking load to exceed a stable work load threshold value, and if so: The method comprises the steps of collecting motion state vectors of all detection targets in each radar scanning period, generating a dynamic group set based on the motion state vectors, combining the motion state vectors of all member targets in each dynamic group based on three-dimensional position coordinates of all member targets in the dynamic group set to obtain motion state vectors of virtual large targets; The method comprises the steps of distributing single radar tracking beam resources for each virtual large target based