Robust Algorithm for Sensor Position Estimation Against the Direction Deviations of the Calibration Sources

WANG Ding; YAO Hui; WU Ying

doi:10.3969/j.issn.0372-2112.2013.09.005

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Robust Algorithm for Sensor Position Estimation Against the Direction Deviations of the Calibration Sources

更新时间：2025-07-16

- Robust Algorithm for Sensor Position Estimation Against the Direction Deviations of the Calibration Sources
- Acta Electronica Sinica Vol. 41, Issue 9, Pages: 1694-1702(2013)
- 作者机构：
  
  解放军信息工程大学信息系统工程学院,河南,郑州,450002
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61201381);Program Sponsered by Future Development Fund of Peking University School of Electronic and Computer Engineering (No.YP12JJ202057)
- DOI：10.3969/j.issn.0372-2112.2013.09.005
  CLC： TN911.7
- Published：2013
- 稿件说明：
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WANG Ding, YAO Hui, WU Ying. Robust Algorithm for Sensor Position Estimation Against the Direction Deviations of the Calibration Sources[J]. Acta Electronica Sinica, 2013, 41(9): 1694-1702.
DOI：

WANG Ding, YAO Hui, WU Ying. Robust Algorithm for Sensor Position Estimation Against the Direction Deviations of the Calibration Sources[J]. Acta Electronica Sinica, 2013, 41(9): 1694-1702. DOI： 10.3969/j.issn.0372-2112.2013.09.005.

摘要

针对校正源方位估计偏差会影响阵元位置误差校正精度这一问题

该文在假设校正源方位估计偏差的概率分布先验已知的条件下

根据信号子空间拟合理论和贝叶斯估计理论框架

提出一种能够抑制校正源方位估计偏差的阵元位置误差鲁棒估计算法.该算法以Newton迭代的形式给出

并不需要对校正源方位进行数值优化.理论分析和仿真实验均表明:在一定条件下

文中的新算法对校正源方位估计偏差具有较好的鲁棒性

并且其渐近性能可逼近相应的克拉美罗界.

Abstract

The direction deviations of the calibration sources would seriously degrade the calibration precision of the sensor positions.Aiming to this problem

the robust calibration algorithm for estimating the sensor shape against the location deviations is presented under the condition that the prior probability distribution of the direction deviations is available.The robust algorithm is derived based on the signal subspace fitting (SSF) technique and the Bayesian estimation theory frame

and it is numerically implemented via the Newton iteration without optimizing the locations of the calibration sources.Both the theory analysis and simulation experiments validate that the novel algorithm has preferable robustness against the location deviations of the calibration sources and its asymptotic performance can reach the Cram-Rao bound (CRB) under some moderate conditions.

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