系统工程与电子技术

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基于TAS模式的多目标跟踪波束调度策略

喻晨龙1, 李凡1, 谭贤四2, 王红2, 曲智国2   

  1. 1. 空军预警学院研究生管理大队, 湖北 武汉 430019;
    2. 空军预警学院陆基预警装备系, 湖北 武汉 430019
  • 出版日期:2017-06-23 发布日期:2010-01-03

Beam schedule strategy for multiple target tracking in TAS mode

YU Chenlong1, LI Fan1, TAN Xiansi2, WANG Hong2, QU Zhiguo2   

  1. 1. Department of Graduate Management, Air Force Early Warning Academy, Wuhan 430019, China;
    2. The Landbased Early Warning Equipment Department of Air Force Early Warning Academy, Wuhan 430019, China
  • Online:2017-06-23 Published:2010-01-03

摘要:

在跟踪加搜索工作方式下,相控阵雷达既要对已捕获的目标保持稳定跟踪,又要继续搜索责任空域发现新目标,为此提出了一种波束调度策略。在交互多模型框架下,基于状态的一步预测估计了目标的预期驻留时间,以检测概率和跟踪精度为约束条件进行了优化,基于驻留时间估计了目标的预期噪声方差和预期误差协方差,定义了目标跟踪的紧迫因子、偏差因子和调度系数,在各个时刻估算所有目标下一时刻的调度系数,根据调度系数大小确定下一时刻的波束指向,指挥波束进行照射,当波束照射到目标上时,更新量测噪声并滤波,当波束未照射到目标上时用预测值表示目标状态,仿真证明了算法的可行性和有效性。

Abstract:

Under the tracking and searching (TAS) mode, phased array radar has to maintain stability captured target tracking, but also the responsibility to continue to search the airspace for new target. a new beam schedule strategy for multiple target tracking is proposed to achieve adaptive transform. In the interacting multiple model (IMM) framework, target expected dwell time is estimated based on the state’s one step prediction and is optimized through the constraint conditions of radar detection probability and tracking accuracy, target’s expected noise variance and expected error covariance are estimated based on the dwell time. Then the urgency factor, deviation factor and scheduling coefficient are respectively defined, the scheduling coefficient of the next time for each target is estimated at every time and the beam pointing coefficient is determined according to them. Direct the beam irradiation, when the beam irradiates the target,the measurement noise is updated and filtering, when the beam fails to irradiate the target, the state is replaced by the predicted value,a new target can be added unless the original targets can be stability tracked. Finally, the feasibility and effectiveness of the algorithm are demonstrated through the simulation.