基于时差法的无源定位跟踪技术

发布时间：2018-01-10 04:09

本文关键词：基于时差法的无源定位跟踪技术　出处：《西安电子科技大学》2014年硕士论文　论文类型：学位论文

【摘要】：在现代信息化战争环境中,随着电子对抗和防御技术的不断发展,传统的有源定位跟踪系统在隐蔽性、抗干扰性、生存能力等方面所面临的威胁越来越严重,作为对有源定位系统的补充和完善,无源定位跟踪系统由于其设备简单、隐蔽性好、作用距离远、生存能力强等优点越来越受到国内外军事强国的关注。本课题围绕无源定位技术及其跟踪算法展开研究。从定位原理、跟踪滤波算法和系统模型建立等方面进行了详细的研究和仿真分析。本文对基于时差法的无源定位跟踪技术进行了研究。首先介绍了无源定位系统,详细研究了时差法多站无源定位的基本原理及其定位算法,并对定位精度进行了分析,通过仿真验证了影响定位精度的因素。其次针对无源定位跟踪的问题,介绍了非线性滤波算法中的扩展卡尔曼滤波算法和无迹卡尔曼滤波算法,列出了两种滤波算法的具体实现步骤,并通过仿真比较了两种算法的跟踪性能。针对目标的机动性问题,介绍了几种运动模型的基本原理以及实现步骤,通过仿真分析比较了各个模型在跟踪目标运动过程中的跟踪误差。最后,介绍了基于无迹卡尔曼滤波(Unscented Kalman Filter,UKF)的交互式多模型滤波算法,通过多个滤波器并行运算,对不同运动模型下的目标进行跟踪,能够有效的跟踪机动目标,并通过仿真比较了两种交互式模型对目标的跟踪性能以及各模型的使用概率情况,得到了一种比较好的目标跟踪模型算法。
[Abstract]:In the modern information war environment, with the continuous development of electronic countermeasures and defense technology, the traditional active positioning and tracking system is facing more and more serious threats in the aspects of concealment, anti-jamming, survivability and so on. As a supplement to the active positioning system, the passive positioning and tracking system has the advantages of simple equipment, good concealment and long operating distance. The advantages of strong survivability have been paid more and more attention by the military powers at home and abroad. This paper focuses on passive location technology and its tracking algorithm. The tracking filtering algorithm and system model are studied and simulated in detail. In this paper, the passive location and tracking technology based on time difference method is studied. Firstly, the passive location system is introduced. The basic principle and location algorithm of multi-station passive location with time difference method are studied in detail, and the positioning accuracy is analyzed. The factors that affect the positioning accuracy are verified by simulation. Secondly, the problem of passive location tracking is discussed. The extended Kalman filter algorithm and the unscented Kalman filter algorithm are introduced, and the implementation steps of the two filtering algorithms are listed. The tracking performance of the two algorithms is compared by simulation. Aiming at the maneuverability of the target, the basic principles and implementation steps of several motion models are introduced. Finally, the unscented Kalman Filter based on unscented Kalman filter is introduced. UKF interactive multi-model filtering algorithm, through the parallel operation of multiple filters to track the target under different moving models, can effectively track the maneuvering target. The tracking performance of two interactive models and the usage probability of each model are compared by simulation, and a better target tracking algorithm is obtained.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN95

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