航空学报 > 2018, Vol. 39 Issue (7): 321835-321835   doi: 10.7527/S1000-6893.2018.21835

基于DP-SA的机载外辐射源无源协同定位

郭云飞1, 张沛男1, 才智2   

  1. 1. 杭州电子科技大学 自动化学院, 杭州 310018;
    2. 中国电子科技集团公司 第二十八研究所, 南京 210007
  • 收稿日期:2017-10-31 修回日期:2017-12-29 出版日期:2018-07-15 发布日期:2018-04-09
  • 通讯作者: 郭云飞 E-mail:gyf@hdu.edu.cn
  • 基金资助:
    国家自然科学基金(61573123)

DP-SA based airborne passive coherent location

GUO Yunfei1, ZHANG Peinan1, CAI Zhi2   

  1. 1. School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China;
    2. No. 28 Institute, China Electronics Technology Group Corporation(CETC), Nanjing 210007, China
  • Received:2017-10-31 Revised:2017-12-29 Online:2018-07-15 Published:2018-04-09
  • Supported by:
    National Natural Science Foundation of China (61573123)

摘要: 针对强杂波背景下机载外辐射源无源协同定位(APCL)问题,提出一种基于动态规划和状态扩维(DP-SA)的单目标无源协同定位方法。首先,基于误差传播理论,构建了考虑外辐射源位置不确定性的状态转移范围,进而建立动态规划(DP)的值函数。其次,推导了基于极值理论的动态规划回溯阈值,提高了低可观测目标的检测概率。最后,对测量新息协方差进行在线修正,降低了外辐射源位置不确定性的影响,并利用状态扩维技术实现目标状态与外辐射源状态的联合估计。仿真验证了所提方法的有效性。

关键词: 机载外辐射源, 无源协同定位, 动态规划, 低可观测目标, 传感器位置不确定

Abstract: To address the problem of Airborne Passive Coherent Location (APCL) in heavy clutter, a method for single target passive coherernt location is proposed based on Dynamic Programming-State Augmentation (DP-SA). Based on the error propagation theory, the state transition is analyzed considering transmitter location uncertainty. The state transition is then used to construct the cost function in the Dynamic Programming (DP) framework. The backtracking threshold of the DP is derived using the extreme value theory, which helps to improve the detection probability of the low observable target. To reduce the effect of transmitter location uncertainty on tracking performance, the measurement covariance is modified online. In addition, the state augment technique is invoked to estimate the target state and the transmitter state simultaneously. Simulation results verify effectiveness of the proposed method.

Key words: airborne transmitter, passive coherent location, dynamic programming, low observable target, sensor location uncertainty

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