Exact maximum likelihood error estimation algorithm in MMW/IR imaging system

被引：0

作者：

Qi L. ^{[1
,2
,3
,4
]}

Su W.-B. ^{[1
,2
,3
,4
]}

Shi Z.-L. ^{[1
,3
,4
]}

机构：

[1] Shenyang Institute of Automation, Chinese Academy of Sciences

[2] Graduate School of Chinese Academy of Sciences

[3] Key Laboratory of Optical-Electronics Information Processing, Chinese Academy of Sciences

[4] Key Laboratory of Image Understanding and Computer Vision, Shenyang 110016, Liaoning Province

来源：

Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves | 2010年 / 29卷 / 05期

关键词：

Data fusion; Error estimation; Maximum likelihood estimation; Unbiased converted measurement;

D O I：

10.3724/sp.j.1010.2010.00372

中图分类号：

学科分类号：

摘要：

An exact maximum likelihood error estimation algorithm based on unbiased converted measurements (UCM-EML) was proposed in order to estimate systematic errors of a MMW radar/IR imaging composite system accurately. An error estimation model was formulated based on measurement noises in polar coordinates, then the criterion function and the corresponding negative log likelihood function were given. The algorithm was implemented using a recursive two-step optimization that involves a modified Gauss-Newton procedure. Simulation results show that the UCM-EML algorithm is better than the exact maximum likelihood (EML) algorithm and the modified exact maximum likelihood (MEML) algorithm on performance and convergence rate.

引用

页码：372 / 377

页数：5

共 12 条

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