基于TDOA和TOA的定位技术研究

发布时间：2018-02-13 00:50

本文关键词： 到达时差到达时间多维尺度分析 TDOA/FDOA联合定位克拉美-罗下界　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】：无论是在民用系统还是在军用系统中,对目标的精确定位,都有着非常重要的作用。有源定位、无源定位以及自定位是目前常见的三种目标定位问题。其中,无源定位是在对目标不发射电磁波的条件下,通过测量辐射源诸如通信发射机、雷达等的电磁波,来确定目标的位置信息。其定位方式决定了无源定位具有隐蔽性强、不易被察觉的优点,因而使其成为现代一体化防空系统、远程预警系统以及机载对敌等方面的重要组成部分,在电子对抗领域发挥着与日俱增的关键作用。目前,在对目标的定位问题中,常用的定位参数主要有到达时差(TDOA)、到达时间(TOA)、到达角(AOA)以及它们的混合参数等。一方面,本文分别研究并分析了基于TDOA信息的静止目标和基于TDOA/FDOA信息的运动目标的定位算法。对于静止目标,主要介绍了几种经典的TDOA无源定位算法,并分析了各自的定位性能;对于运动目标,主要研究了几种常用的基于TDOA测量值和FDOA测量值的联合定位算法。另一方面,本文还介绍了一种基于TOA测量值的MDS(multi-dimensional scaling)定位算法,并对该算法进行改进,提出了一种新的利用多个时刻TOA测量值的MDS定位算法,大大提高了定位精度。本文的所有工作主要着眼于下述几个方面:(1)第一章首先简要叙述了几种常见的目标定位问题,尤其是无源定位的研究背景、研究意义及其发展历史和研究现状。随后重点介绍了用于定位的几种主要方法及其数学模型,同时研究了对于各种定位算法的常用的定位精度评价指标。(2)第二章首先介绍了TDOA定位算法的基本原理以及估计TDOA值的主要方法,然后重点介绍了3种典型的TDOA定位算法,包括加权最小二乘(WLS)算法、泰勒级数法以及Chan算法,并分别分析比较了各算法的优缺点及其定位性能。(3)第三章首先介绍了一种近些年提出的多维尺度分析(MDS)算法以及它在TOA定位问题中的应用,随后在此基础上对该算法进行改进,针对多运动基站的TOA定位模型,提出了一种新的利用多个时刻TOA测量值的MDS定位算法,该算法考虑了二阶误差项的影响,在传统MDS算法的基础上利用了多个时刻的基站位置信息和TOA测量信息,进一步提高了定位精度。(4)第四章主要研究了针对运动目标的定位问题,介绍了几种常用的基于TDOA测量值以及FDOA测量值的联合定位算法,包括总体最小二乘(TLS)算法、泰勒级数法以及两步最小二乘算法,并分析比较了它们各自对目标位置和速度的估计性能。
[Abstract]:In both civil and military systems, the precise positioning of targets plays a very important role. Active location, passive location and self-positioning are three common target positioning problems. Passive location is to determine the location information of the target by measuring the electromagnetic waves of emitter such as communication transmitter, radar and so on under the condition that no electromagnetic wave is emitted to the target. Its undetectable advantages make it an important component of modern integrated air defense systems, long-range early warning systems and airborne enemies, playing an increasingly critical role in the field of electronic countermeasures. In the problem of target location, the commonly used location parameters are time difference of arrival (TDOA), arrival time (TOAA), arrival angle (AOAA) and their mixed parameters. In this paper, the static target location algorithm based on TDOA information and the moving target location algorithm based on TDOA/FDOA information are studied and analyzed respectively. For the static target, several classical TDOA passive localization algorithms are mainly introduced, and their localization performance is analyzed. For moving target, several commonly used joint localization algorithms based on TDOA measurement and FDOA measurement are studied. On the other hand, a MDS(multi-dimensional scaling algorithm based on TOA measurement is introduced, and the algorithm is improved. In this paper, a new MDS localization algorithm using TOA measurements at multiple times is proposed, which greatly improves the positioning accuracy. The first chapter focuses on the following aspects: in Chapter 1, several common target localization problems are briefly described. In particular, the research background, research significance, development history and present situation of passive location are introduced. Then, several main methods and their mathematical models for location are introduced. The second chapter introduces the basic principle of TDOA localization algorithm and the main methods of estimating TDOA value, and then introduces three typical TDOA localization algorithms. Including weighted least squares (WLS) algorithm, Taylor series method and Chan algorithm, The advantages and disadvantages of each algorithm and its localization performance are analyzed and compared respectively. In chapter 3, a multi-dimensional scale analysis (MDS) algorithm proposed in recent years and its application in TOA localization are introduced, and then the algorithm is improved. Based on the TOA location model of multi-moving base stations, a new MDS localization algorithm based on multi-time TOA measurements is proposed, which takes into account the effect of second-order error terms. Based on the traditional MDS algorithm, the position information of the base station and the TOA measurement information at several times are used to further improve the positioning accuracy. Chapter 4th focuses on the localization of moving targets. This paper introduces several common joint localization algorithms based on TDOA measurements and FDOA measurements, including the total least squares algorithm, the Taylor series method and the two-step least squares algorithm. The performance of their estimation of target position and velocity is analyzed and compared.
【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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