Regular Papers

International Journal of Control, Automation, and Systems 2024; 22(4): 1264-1276

https://doi.org/10.1007/s12555-022-0638-y

© The International Journal of Control, Automation, and Systems

Maritime Targets Tracking in Heavy-tailed Clutter With Unknown and Time-varying Density

Liwei Shi*, Yu Kuang, and Miaomiao He

Hangzhou Dianzi University

Abstract

In order to solve the problem of maritime targets tracking in heavy-tailed sea clutter with unknown and time-varying clutter density, a multi-scan clutter sparsity estimator based amplitude-aided probability hypothesis density (MCSE-APHD) method is proposed in this paper. Firstly, the proposed method eliminates the targetoriginated measurements from multi-scan cumulative measurement set and estimates the spatial distribution density of clutter online. And the estimated clutter density parameter is fed to the tracker. Secondly, the amplitude-aided likelihood function as well as the estimated clutter parameter is established to update the Gaussian mixture posterior intensity of the state using the probability hypothesis density algorithm. The simulation results verify the effectiveness of the proposed algorithm.

Keywords Amplitude information, clutter density estimation, heavy-tailed clutter, maritime targets tracking.

Article

Regular Papers

International Journal of Control, Automation, and Systems 2024; 22(4): 1264-1276

Published online April 1, 2024 https://doi.org/10.1007/s12555-022-0638-y

Copyright © The International Journal of Control, Automation, and Systems.

Maritime Targets Tracking in Heavy-tailed Clutter With Unknown and Time-varying Density

Liwei Shi*, Yu Kuang, and Miaomiao He

Hangzhou Dianzi University

Abstract

In order to solve the problem of maritime targets tracking in heavy-tailed sea clutter with unknown and time-varying clutter density, a multi-scan clutter sparsity estimator based amplitude-aided probability hypothesis density (MCSE-APHD) method is proposed in this paper. Firstly, the proposed method eliminates the targetoriginated measurements from multi-scan cumulative measurement set and estimates the spatial distribution density of clutter online. And the estimated clutter density parameter is fed to the tracker. Secondly, the amplitude-aided likelihood function as well as the estimated clutter parameter is established to update the Gaussian mixture posterior intensity of the state using the probability hypothesis density algorithm. The simulation results verify the effectiveness of the proposed algorithm.

Keywords: Amplitude information, clutter density estimation, heavy-tailed clutter, maritime targets tracking.

IJCAS
April 2024

Vol. 22, No. 4, pp. 1105~1460

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eISSN 2005-4092
pISSN 1598-6446