﻿ 同步三星目标运动状态快速检测方法
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Fast algorithm of motion state detection based on tri geo-satellites
Yang Yuxiang, Zhang Huichuan
Southwest Electronics and Telecommunication Technology Research Institute, Chengdu 610041, China
Abstract:Aiming at the difficulty to detect the motion state of targets in the satellite-borne passive location system, a fast motion state detection algorithm, based on the principle that the location result of the dual-satellites geolocation using differential time offset (DTO) and differential frequency offset (DFO) should be consistent with that of the tri-satellites geolocation using dual DTOs under the stationary hypothesis, was proposed. Firstly the region of target was obtained by location error analysis. Then the DFO range of this region under the stationary hypothesis was obtained through the statistics. Finally the observed value of DFO at the location time was compared with the DFO range to detect the motion state of target. And the expression of theoretical detection probability was given. The algorithm was verified by the simulation and experiment results. For the targets with velocity above 40 m/s, the detection probabilities are more than 99% when the estimation precision of DTO/DFO is 10 μs/100 mHz. It is demonstrated by the practical data that the proposed algorithm helps the system improve the ability to detect motion state significantly.
Key words: differential frequency offset (DFO)     differential time offset (DTO)     passive location     error ellipse     motion state detection

 图 1 定位系统示意图 Fig. 1 Schematic diagram of location system
1.1 同步三星时差定位原理

2 检测算法 2.1 定位一致性检测算法

PdrS的协方差矩阵,则

drS服从高斯分布[14,15],其概率密度函数为

 图 2 误差椭圆示意图 Fig. 2 Schematic diagram of error ellipse

σxσy表示式(14)所示误差椭圆的长、短半轴,则其代表了exey方向上的定位误差标准差.由于正态分布99.7%样本集中在3倍标准差以内,故要覆盖目标真实位置,将其扩展为3σx和3σy,本文定义其为扩展误差椭圆.

 图 3 目标与卫星几何关系 Fig. 3 Geometrical relationship of target and satellites

y=cos β的条件概率密度函数为

3 仿真与试验分析 3.1 仿真分析

 卫星编号 轨道根数 a/km e i/(°) ω/(°) Ω/(°) M/(°) 25 404 14 720 0.000 563 1.374 8 342.11 74.77 97.67 31 800 14 721 0.000 292 0.009 6 140.23 256.36 61.69 35696 14719 0.000 145 0.006 2 274.25 91.62 258.28

 图 4 检测概率随速度变化曲线 Fig. 4 Curves of detection probability vs velocity

 图 5 系统对某移动和静止目标定位结果 Fig. 5 Location results of system for moving and stationary targets

 图 6 静止目标运动状态检测结果 Fig. 6 Motion state detection results of the stationary

 图 7 移动目标运动状态检测结果 Fig. 7 Motion state detection results of the moving target
4 结 论

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#### 文章信息

Yang Yuxiang, Zhang Huichuan

Fast algorithm of motion state detection based on tri geo-satellites

Journal of Beijing University of Aeronautics and Astronsutics, 2014, 40(10): 1392-1398.
http://dx.doi.org/10.13700/j.bh.1001-5965.2013.0631