BR/BRR Passive Localization and Registration for Multiple Moving Targets in Single-observer Multi-illuminator Radar Systems
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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。
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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. -
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