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Received: 2006-03-02

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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.101 P.213~218


A new approach for target motion analysis with signal time delay

Author(s):  Xue An-Ke, Guo Yun-Fei

Affiliation(s):  Institute of Intelligence Information and Control Technology, Hangzhou Dianzi University, Hangzhou 310018, China; more

Corresponding email(s):   akxue@hdu.edu.cn, zizhe_yjys@yahoo.com.cn

Key Words:  Target motion analysis (TMA), Signal time delay, IRPUKF

Xue An-Ke, Guo Yun-Fei. A new approach for target motion analysis with signal time delay[J]. Journal of Zhejiang University Science A, 2006, 7(101): 213~218.

@article{title="A new approach for target motion analysis with signal time delay",
author="Xue An-Ke, Guo Yun-Fei",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T A new approach for target motion analysis with signal time delay
%A Xue An-Ke
%A Guo Yun-Fei
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 101
%P 213~218
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.AS0213

T1 - A new approach for target motion analysis with signal time delay
A1 - Xue An-Ke
A1 - Guo Yun-Fei
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 101
SP - 213
EP - 218
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.AS0213

A new approach is proposed in this paper for the problem of the target motion analysis (TMA) with signal propagation time delay. This problem is an unobservable tracking problem in which the acoustic signal transmits with time delay. We present an intelligent range parameterized unscented Kalman filter (IRPUKF) algorithm to estimate the state of the nonlinear unobservable tracking system and propose a recursive model parameter online adjustment method to deal with the time delay in signal propagation. In a simulation of tracking target using a maneuvering acoustic sensor with signal time delay case study, the effectiveness and efficiency of the proposed algorithm is testified to perform better, compared with the range parameterized extended Kalman filter (RPEKF) algorithm.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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