机载单站被动定位方法与跟踪算法的研究

发布时间：2018-05-26 05:06

本文选题：机载单站被动定位 + PDRC定位法　；参考：《中北大学》2017年硕士论文

【摘要】：随着现有的单站被动定位技术的发展与滤波算法的完善,结合载机的机动性,本文针对传统的弹载无线信标机回收方法中存在的定位精度低、速度慢、范围小的问题,重点从定位原理、误差分析、参数测量以及滤波算法等角度进行了一些研究工作:首先,针对机载单站被动定位,本文从角度变化率定位法(ARC)、相位差变化率定位法(PRC)、多普勒变化率定位法(DRC)三种方法的定位原理、单次目标测量的误差分析以及可观测性方面进行了仿真分析,给出了三种方法各自的优缺点。其次,研究一种使用相位差、相位差变化率及多普勒变化率三个参数对目标辐射源进行定位的单站被动定位方法(PDRC法)。该方法减少了测量角度变化率这一参数的复杂,在减少工程难度的基础上,PDRC具有更好的定位精度,定位误差更小;为了提高定位参数的测量精度,还对获取相位差变化率及多普勒变化率两个参数的测量方法进行了研究。最后,在分析扩展卡尔曼滤波算法(EKF)、无味卡尔曼滤波算法(UKF)及施密特卡尔曼滤波算法(SOUKF)三种滤波算法基本原理的基础上,研究了一种新的超球体无味卡尔曼滤波算法(Sqrt-UKFST),仿真结果表明该滤波算法的定位精度和收敛速度都优于其他几种算法。
[Abstract]:With the development of single station passive positioning technology and the improvement of filtering algorithm, combined with the maneuverability of the carrier, this paper aims at the problems of low positioning accuracy, slow speed and small range in the traditional recoverability method of the missile borne wireless beacon machine. This paper focuses on some research work from the aspects of positioning principle, error analysis, parameter measurement and filtering algorithm. In this paper, the positioning principle, error analysis and observability of angle change rate positioning method, phase difference change rate positioning method and Doppler change rate positioning method are analyzed. The advantages and disadvantages of the three methods are given. Secondly, a single station passive location method based on the three parameters of phase difference, phase difference change rate and Doppler change rate is studied. This method reduces the complexity of the parameter of measuring angle change rate, and on the basis of reducing the engineering difficulty, PDRC has better positioning accuracy and less positioning error, in order to improve the measuring accuracy of positioning parameters, The measurement methods of phase difference rate and Doppler rate are also studied. Finally, based on the analysis of the basic principles of the extended Kalman filtering algorithm (EKF), the tasteless Kalman filtering algorithm (UKF) and the Schmitt Kalman filtering algorithm (SOUKF), the basic principles of the three filtering algorithms are analyzed. A new hypersphere tasteless Kalman filter algorithm named Sqrt-UKFSTT is studied in this paper. The simulation results show that the location accuracy and convergence speed of the proposed algorithm are better than those of other algorithms.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TJ06;TN713

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