基于混沌麻雀搜索算法的TDOA/FDOA定位

doi:10.13229/j.cnki.jdxbgxb20210200

摘要/Abstract

摘要：

针对在实际定位场景中，接收站常被安装在运动平台上，导致其运动状态信息存在随机误差，而目标源定位精度对接收站的位置信息非常敏感，接收站位置的微小误差会导致目标源位置估计存在较大误差的问题，本文在考虑接收站位置信息存在随机误差的情况下，提出了一种使用到达时间差和到达频率差测量值定位移动源的解决方案。该方法通过在麻雀搜索算法中引入Logistic混沌映射对目标进行定位跟踪，Logistic混沌映射可以降低算法收敛到局部最优的风险，用以解决站址误差较低的情况下定位精度差的问题。仿真结果分析表明：在低站址误差的情况下，本文算法的定位精度比半定规划-重构线性化技术（SDP-RLT）、遗传算法、麻雀搜索算法和蚁群算法更接近克拉美罗下界。

关键词: 信息处理技术, 到达时间差, 到达频率差, 麻雀搜索算法, Logistic混沌映射

Abstract:

In the actual localization scenarios， the receiving station is usually installed on the moving platform， which leads to the random error in its moving state information. However， the target source location accuracy is very sensitive to the location information of the receiving station， and the small error in the location of the receiving station will lead to a large error in the estimation of the target source position. Therefore， considering the random error of the location information of the receiving station， a solution to locate the mobile source using the measured values of the time difference of arrival and the frequency difference of arrival is proposes in this paper. Logistic chaotic mapping is introduced into sparrow search algorithm to locate and track the target. Logistic chaotic mapping can reduce the risk of the algorithm convergence to local optimal， so as to solve the problem of poor localization accuracy in the case of low sensor position error. The analysis of simulation results shows that the accuracy of the proposed algorithm is closer to the Cramer-Rao lower bound than that of semi-definite programming and reformulation linearization technique（SDP-RLT）， genetic algorithm， sparrow search algorithm and ant colony algorithm under the condition of low sensor position error.

Key words: information processing technology, time difference of arrival, frequency difference of arrival, sparrow search algorithm, logistic chaotic mapping

中图分类号:

TP277

国强,朱国会,李万臣. 基于混沌麻雀搜索算法的TDOA/FDOA定位[J]. 吉林大学学报(工学版), 2023, 53(2): 593-600.

Qiang GUO,Guo-hui ZHU,Wan-chen LI. TDOA/FDOA localization based on chaotic sparrow search algorithm[J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(2): 593-600.

图/表 6

图1

图2

表1

接收站和目标源的位置及速度"

接收站及近场源	$x i$	$y i$	$z i$	$x ˙ i$	$y ˙ i$	$z ˙ i$
1	300	100	150	30	-20	20
2	400	150	100	-30	10	20
3	300	500	200	10	-20	10
4	350	200	100	10	20	30
5	-100	-100	-100	-20	10	10
近场源	600	650	550	-20	15	40

表1

图3

图4

图5

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