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基于TDOA和FDOA多星联合定位技术研究
【作者】 郭文龙；
【导师】 束锋；
【作者基本信息】 南京理工大学 ， 通信与信息系统， 2009， 硕士
【摘要】 随着科技的发展,卫星定位技术在军事和民用领域具有越来越重要的地位和作用。由于无源定位系统本身不发射电磁波,完全是被动工作的,所以具有隐蔽性好、抗干扰能力强等优点。近年来,无源定位更是在航空、航海、航天和电子战等领域表现异常突出,发挥了无可替代的作用。因此,也越来越受到各国广泛的关注与重视。本文主要研究被动辐射源的多星定位,研究工作覆盖卫星定位精度分析、多星构型和TDOA/FDOA联合定位算法。主要工作如下:(一)为了设计好的卫星构型,本文介绍了克拉美罗界(CRLB)与几何稀度(GDOP)的推导过程,然后分析了一种典型的五星构型-五面体。通过仿真与分析,获得如下结论:主星与副星连线之间夹角在45°到60°时,能够获得较好定位性能。(二)为了提高单独TDOA或FDOA定位的精度,提出了基于最大比合并的TDOA/FDOA联合算法。仿真结果表明,有地球约束情况下的最大比合并算法已经可以达到克拉美罗界,比单独定位算法和Ho最小二乘联合算法具有更好定位性能。(三)深入研究了霍夫变换在卫星定位中应用,重点讨论了如何利用霍夫变换来实现数据的加权融合。最后的仿真结果表明,加权融合后的霍夫变换同单独TDOA或FDOA霍夫变换相比,具有更好的定位功能。
【Abstract】 With the development of science and technology, multi-satellite passive location plays a more and more important role in the military and the civil applications. Because passive location system does not emit electromagnetic wave, it has a high concealing and anti-jamming ability. In recent years, passive location shows an irreplaceable role in aviation and navigation, aerospace and electronic warfare, etc. Thus, it obtains more and more widespread concerning from many countries.This paper focuses on passive location and consists of the following parts: satellite locating accuracy analysis, joint time difference of arrival (TDOA) and frequency difference of arrival (FDOA) location algorithm. The main content is as follows:a) To design a good satellite array shape, we describe the derivation process of Cramer-Rao lower bound (CRLB) and Geometric dilution of Precision (GDOP). Then, a typical five-satellite array shape is discussed. Simulation results and discussions show: if the angle between the lines connecting the main satellite and aiding ones is between 45°and 60°, then a better GDOP is achieved.b) To improve the location precision of TDOA or FDOA, we propose a joint location algorithm based on maximum ratio combing (MRC). Simulation results show that this MRC algorithm under earth constraint (EC) can achieves CRLB and perform better than TDOA, FDOA and Ho algorithm regardless of EC.c) Application of Hough Transform (HT) to passive location is deeply studied, and data fusion based on HT is discussed. The simulation results show that the weighted HT has a better location performance than TDOA or FDOA location based on HT.