蒋陶然,
陈志猛,
彭冬亮
杭州电子科技大学自动化学院 杭州 310018
基金项目:国家自然科学基金(61673146, 61771028, 61973102)，电子信息控制重点实验室基金(6142105200102)
详细信息
作者简介:左燕：女，1980年生，博士，副教授，研究方向为无源定位、传感器管理
蒋陶然：男，1995年生，硕士生，研究方向为无源定位
陈志猛：男，1993年生，硕士生，研究方向为无源定位和误差配准
彭冬亮：男，1977年生，教授，博士生导师，研究方向为目标跟踪、智能信息处理和信息融合
通讯作者:左燕 leftswallow@163.com
中图分类号:TN958.97计量
文章访问数:369
HTML全文浏览量:173
PDF下载量:40
被引次数:0
出版历程
收稿日期:2020-01-09
修回日期:2020-10-21
网络出版日期:2020-12-15
刊出日期:2021-04-20
BR/BRR Passive Localization and Registration for Multiple Moving Targets in Single-observer Multi-illuminator Radar Systems
Yan ZUO,,Taoran JIANG,
Zhimeng CHEN,
Dongliang PENG
School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Funds:The National Natural Science Foundation of China (61673146, 61771028, 61973102), Fund of Science and Technology on Electronic Information Control Laboratory (6142105200102)
摘要
摘要:单站多外辐射源雷达定位系统利用多组双基距(BR)和双基距变化率(BRR)量测值对多运动目标定位。量测偏差的存在使得定位性能下降，对此该文提出一种基于迭代后验关联最小二乘估计的联合误差校正和目标定位算法。首先引入辅助变量对BR和BRR非线性观测方程伪线性化，建立目标参数和偏差的联合估计方程。其次，利用辅助变量和目标参数之间的关系构建新的等式方程设计关联最小二乘算法，并采用后验迭代校正固定偏差进一步提高定位精度和全局收敛性。最后对算法的理论误差和全局收敛性进行了分析，仿真结果显示：所提算法具有较好的全局收敛性且目标定位性能达到克拉美罗下界。
关键词:无源定位/
误差校正/
双基距离(BR)/
双基距离变化率(BRR)/
关联最小二乘(DLS)
Abstract:Single-observer Multi-illuminator radars localize multiple moving targets using multiple Bistatic Range (BR) and Bistatic Range Rate (BRR) measurements. However the existence of the biases would degrade the localization performance. A novel joint localization and registration based on iterative post-estimation Dependent Least Squares (DLS) is proposed. Firstly, a new jointed target parameters and biases estimation model is given by linearizing the BR and BRR measurement equation with auxiliary parameters. Then a DLS algorithm refines the target parameters by reusing the relationships between the target parameters and auxiliary parameters. An iterative post-estimate further refines the estimation accuracy and global coverage by biases registration. Finally its theoretical error and global convergence are obtained analytically. Simulation results show that the proposed algorithm has a good global convergence behavior and the performance can achieve the Cramer-Rao Lower Bound.
Key words:Passive localization/
Registration/
Bistatic Range (BR)/
Bistatic Range Rate (BRR)/
Dependent Least Squares (DLS)
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