A nonlinear estimation algorithm and its optical implementation for target tracking in clutter environment

被引：0
|
作者：
Chun, Joohwan [1 ]
Kailath, Thomas [2 ]
Son, Jung Yong [3 ]
机构：
[1] Scientific Computing Laboratory, Dept. of Electrical Engineering, Korea Adv. Inst. Sci. and Technol., 373-1 Kusong-dong, Yusong-gu, Taejon 305-701, Korea, Republic of
[2] Information Systems Laboratory, Stanford University, Stanford, CA 94305, United States
[3] 3-D Imaging Media Center, Korea Inst. of Science and Technol., P.O. Box 131 Cheongryang, Seoul, Korea, Republic of
来源：
Japanese Journal of Applied Physics, Part 1: Regular Papers and Short Notes and Review Papers | 2003年 / 42卷 / 2 A期
关键词：
Algorithms - Clutter (information theory) - Computer simulation - Estimation - Infrared detectors - Kalman filtering - Optical devices - Optimization - Probability density function;
D O I：
10.1143/jjap.42.466
中图分类号：
学科分类号：
摘要：
The two-dimensional tracking problem in a clutter environment is solved in the discrete-time Bayes optimal (nonlinear, and non-Gaussian) estimation framework. The proposed method recursively finds the probability density functions of the target position and velocity. With our approach, the nonlinear estimation problem is converted into simpler linear convolution operations that can be implemented with optical devices efficiently. We present a possible optical implementation architecture, and its functionality is verified through computer simulation.
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页码：466 / 470
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