系统误差条件下基于AOA/TOA/FOA的多目标结构总体最小二乘算法

陈鑫; 王鼎; 刘瑞瑞; 尹洁昕; 吴瑛

doi:10.1631/FITEE.1700735

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系统误差条件下基于AOA/TOA/FOA的多目标结构总体最小二乘算法

常规文章 | Updated：2022-05-19

- 系统误差条件下基于AOA/TOA/FOA的多目标结构总体最小二乘算法
- Structural total least squares algorithm for locating multiple disjoint sources based on AOA/TOA/FOA in the presence of system error
- 信息与电子工程前沿（英文） 2018年19卷第7期页码：917-936
- Affiliations：
  
  National Digital Switching System Engineering and Technology Research Center, Zhengzhou 450002, China
  Zhengzhou Institute of Information Science and Technology, Zhengzhou 450002, China
- Author bio：
  
  Ding WANG, E-mail: wang_ding814@aliyun.com
- Funds：
  
  Project supported by the National Natural Science Foundation of China (Nos. 61201381, 61401513, and 61772548), the China Postdoctoral Science Foundation (No. 2016M592989), the Self-Topic Foundation of Information Engineering University, China (No. 2016600701), and the Outstanding Youth Foundation of Information Engineering University, China (No. 2016603201)
- DOI：10.1631/FITEE.1700735
  中图分类号： TN911.7
- 收稿：2017-11-08，
  
  修回：2018-;7-12，
  
  纸质出版：2018-07
- Accepted：
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陈鑫, 王鼎, 刘瑞瑞, 等. 系统误差条件下基于AOA/TOA/FOA的多目标结构总体最小二乘算法[J]. 信息与电子工程前沿（英文）, 2018,19(7):917-936.

Xin CHEN, Ding WANG, Rui-rui LIU, et al. Structural total least squares algorithm for locating multiple disjoint sources based on AOA/TOA/FOA in the presence of system error[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(7): 917-936.
陈鑫, 王鼎, 刘瑞瑞, 等. 系统误差条件下基于AOA/TOA/FOA的多目标结构总体最小二乘算法[J]. 信息与电子工程前沿（英文）, 2018,19(7):917-936. DOI： 10.1631/FITEE.1700735.

Xin CHEN, Ding WANG, Rui-rui LIU, et al. Structural total least squares algorithm for locating multiple disjoint sources based on AOA/TOA/FOA in the presence of system error[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(7): 917-936. DOI： 10.1631/FITEE.1700735.

摘要

单站无源定位系统避免了多个观测站之间复杂的时间同步和信息交换，在电子战中越来越重要。基于单个运动站定位系统，考虑到来自不同目标的观测具有相同的观测站位置及速度误差，提出一种具有高定位精度和数值稳定性的定位方法。根据到达角（AOA）、到达时间（TOA）和到达频率（FOA）等观测量，推导出相应的伪线性方程。在此基础上，提出一种结构总体最小二乘（STLS）优化模型，并利用逆迭代算法获得固定目标的位置。推导了所提算法的定位性能，并通过一阶误差分析证明了STLS算法的理论性能和约束总体最小二乘算法的理论性能一致，两者都能够达到克拉美罗界精度。仿真结果表明了理论推导的正确性和所提算法的优越性。

Abstract

Single-station passive localization technology avoids the complex time synchronization and information exchange between multiple observatories

and is increasingly important in electronic warfare. Based on a single moving station localization system

a new method with high localization precision and numerical stability is proposed when the measurements from multiple disjoint sources are subject to the same station position and velocity displacement. According to the available measurements including the angle-of-arrival (AOA)

time-of-arrival (TOA)

and frequency-of-arrival (FOA)

the corresponding pseudo linear equations are deduced. Based on this

a structural total least squares (STLS) optimization model is developed and the inverse iteration algorithm is used to obtain the stationary target location. The localization performance of the STLS localization algorithm is derived

and it is strictly proved that the theoretical performance of the STLS method is consistent with that of the constrained total least squares method under first-order error analysis

both of which can achieve the Cramér-Rao lower bound accuracy. Simulation results show the validity of the theoretical derivation and superiority of the new algorithm.

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