Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model

WANG Ding1; PAN Miao2; WU Ying1

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Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model

更新时间：2024-10-14

- Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model
- Vol. 32, Issue 2, Pages: 34-41(2011)
- 作者机构：
  
  1. 解放军信息工程大学信息工程学院
  2. 江南计算技术研究所
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.7
- Published：2011
- 稿件说明：
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WANG Ding1, PAN Miao2, WU Ying1. Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model[J]. 2011, 32(2): 34-41.
DOI：

WANG Ding1, PAN Miao2, WU Ying1. Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model[J]. 2011, 32(2): 34-41. DOI：

摘要

针对确定信号模型条件下方位依赖幅相误差的自校正问题

给出了一种基于辅助阵元的方位依赖幅相误差最大似然自校正方法;针对最大似然估计器中出现的高维非线性优化问题

推导了一种改进型交替投影迭代算法

从而实现了信号方位和方位依赖幅相误差的优化计算。此外

还推导了信号方位和方位依赖幅相误差的无偏克拉美罗界(CRB)。仿真实验结果验证了新方法的有效性和优越性。

Abstract

Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model

the maximum likelihood method（MLM） for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM

an improved alternative projection iteration algorithm

which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound（CRB） for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.

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