系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (12): 2708-2715.doi: 10.3969/j.issn.1001-506X.2020.12.06

• 电子技术 • 上一篇    下一篇

空基外辐射源定位系统的观测站航迹优化

卢雨(), 周正()   

  1. 海军航空大学航空作战勤务学院, 山东 烟台 264001
  • 收稿日期:2020-02-18 出版日期:2020-12-01 发布日期:2020-11-27
  • 作者简介:卢雨(1996-),男,硕士研究生,主要研究方向为信息对抗、信息融合。E-mail:17664113162@163.com|周正(1978-),男,副教授,博士,主要研究方向为信息对抗、多源信息融合。E-mail:13906384504@139.com
  • 基金资助:
    国防科技卓越青年人才基金(2017-JCJQ-ZQ-003);泰山学者工程专项经费(ts201712072)

Observation station track optimization of airborne external transmitter location system

Yu LU(), Zheng ZHOU()   

  1. School of Aviation Operations and Support, Naval Aviation University, Yantai 264001, China
  • Received:2020-02-18 Online:2020-12-01 Published:2020-11-27

摘要:

针对空基外辐射源定位(airborne passive coherent location, APCL)系统容易出现可观测性差、定位性能不稳定的问题,提出了观测站航迹优化算法以提高系统的定位跟踪性能。首先,建立APCL系统的二维运动学模型与量测方程,并选取系统可观测度和几何精度因子(geometrical dilution of precision, GDOP)作为优化指标,推导出航迹优化函数。然后,使用加权离散搜索优化算法控制观测站机动至最优观测位置,并以容积卡尔曼滤波(cubature Kalman filter, CKF)为工具,对目标和外辐射源进行定位跟踪。仿真结果表明,观测站采用航迹优化算法能大幅提高系统定位的稳定性,显著减小跟踪估计误差。

关键词: 外辐射源定位, 航迹优化, 可观测度, 几何精度因子, 容积卡尔曼滤波

Abstract:

Aiming at the problems of poor observability and unstable positioning performance of airborne passive coherent location (APCL) system, a track optimization algorithm of observation station is proposed to improve the positioning and tracking performance of the system. Firstly, the two-dimensional kinematic model and measurement equation of APCL system are established, then the observability measure and geometrical dilution of precision (GDOP) of the system are selected as the optimization indexes, and the track optimization function is derived. Secondly, the weighted discrete search optimization algorithm is used to control the observation station to the optimal observation position. The cubature Kalman filter (CKF) is used as a tool to locate and track the target and the external transmitter. The simulation results show that the tracking optimization algorithm can greatly improve the stability of the system positioning, and decrease the tracking estimation error significantly.

Key words: passive coherent location, track optimization, observability measure, geometrical dilution of precision (GDOP), cubature Kalman filter (CKF)

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