首页|基于多特征融合的高机动多目标低截获概率跟踪技术

基于多特征融合的高机动多目标低截获概率跟踪技术

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在多目标跟踪过程中,目标的高机动特性使得传统采用固定运动模型或交互式多模型的目标跟踪算法很难实时精确匹配目标运动模型,从而引起高机动目标的低跟踪精度问题.针对这一问题,本文提出一种基于目标运动状态模型自适应更新的高机动多目标跟踪算法.在多目标跟踪过程中,该算法采用多特征聚类融合算法进行目标运动模型估计,并根据各目标跟踪波动参数进行状态转移矩阵决策更新,同时利用联合概率数据关联实现多机动目标状态转移矩阵自适应更新的关联跟踪,从而解决了传统多目标跟踪算法因目标运动模型失配引起的低跟踪精度问题.在目标跟踪算法的传感器选择上,无源传感器不对外辐射能量,具有较好的低截获概率性能,但其跟踪精度有限,常不能满足多目标高跟踪精度的要求.雷达作为有源传感器,具有较高的跟踪精度.但由于雷达对外辐射信号,容易被防御方截获.针对这一问题,本文提出了一种无源传感器目标跟踪为主,有源雷达间歇跟踪为辅的多传感器协同管理目标跟踪算法.该算法通过对目标跟踪本征堆积误差的判断进行传感器的最优分配,并根据波动参数的大小进行状态转移矩阵决策更新.仿真结果验证了本文所提出的多传感器协同的高机动目标跟踪算法在满足高机动目标跟踪精度的条件下可以有效的提升雷达低截获概率性能.
High-Maneuvering Multi-Target Tracking Technology with Low Probability of Intercept Based on Multi-Feature Fusion
In the process of multi-target tracking,when the targets have high maneuvering characteristics,it is difficult for tradi-tional target tracking algorithms using fixed-motion models or interactive multi-models to accurately match the target motion model in real time,resulting in low tracking accuracy for high-maneuvering targets.To solve this problem,this paper proposes a high-mobility multi-target tracking algorithm based on adaptive updating of a target motion state model.In the process of multi-target tracking,a multi-feature clustering fusion algorithm is used to estimate the target motion model,and performs a state-transition matrix decision-making update based on the fluctuation parameters of each target being tracked.At the same time,the algorithm utilizes joint probabilistic data association to adaptively update the associated tracking of the multi-maneuvering target state transition matrix,thereby solving the problem of the low tracking accuracy caused by the mismatch of the target motion mod-els in traditional multi-target tracking algorithms.In the sensor selection of the target tracking algorithm,passive sensors do not ra-diate energy,and have good low intercept probability performance,but their tracking accuracy is limited,and often cannot meet the multi-target high-tracking-accuracy requirements.As an active sensor,radar has high tracking accuracy.However,the exter-nal radiation energy of the radar makes it easy for a defender to intercept.In order to solve this problem,this paper proposes a multi-sensor cooperative management target-tracking algorithm based on passive sensor target tracking and supplementary active-radar intermittent tracking.The algorithm allocates sensors optimally by determining the intrinsic stacking error of the target track-ing,and updates the state transition matrix based on the magnitude of the fluctuation parameters.Simulation results verified that the multi-sensor cooperative high-maneuvering target tracking algorithm proposed in this paper could effectively improve the low intercept-probability performance of radar while meeting the high-maneuvering target-tracking accuracy requirement.

low probability of interceptmultiple high-maneuvering targetsmulti-feature fusiontrajectory cluster-ingmulti-sensor management

陈军、丁一、王杰、汪飞、周建江

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南京信息工程大学电子与信息工程学院,江苏南京 210044

南京航空航天大学雷达成像与微波光子技术教育部重点实验室,江苏南京 210016

低截获概率 高机动多目标 多特征融合 轨迹聚类 多传感器管理

国家自然科学基金江苏省自然科学基金航空科学基金航空科学基金

62171229BK201907722020002005200520200020052002

2024

10.16798/j.issn.1003-0530.2024.02.006

信号处理
中国电子学会

信号处理

CSTPCD北大核心
影响因子：1.502
ISSN：1003-0530
年,卷(期)：2024.40(2)
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