Background agnostic CPHD tracking of dim targets in heavy clutter

Detection and tracking of dim targets in heavy clutter environments is a daunting theoretical and practical problem. Application of the recently developed Background Agnostic Cardinalized Probability Hypothesis Density (BA-CPHD) filter provides a very promising approach that adequately addresses all...

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Main Authors: El-Fallah, A., Zatezalo, A., Mahler, Ronald, Mehra, R., Pereira, W.
Format: Conference Paper
Published: 2013
Online Access:http://hdl.handle.net/20.500.11937/55887
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author El-Fallah, A.
Zatezalo, A.
Mahler, Ronald
Mehra, R.
Pereira, W.
author_facet El-Fallah, A.
Zatezalo, A.
Mahler, Ronald
Mehra, R.
Pereira, W.
author_sort El-Fallah, A.
building Curtin Institutional Repository
collection Online Access
description Detection and tracking of dim targets in heavy clutter environments is a daunting theoretical and practical problem. Application of the recently developed Background Agnostic Cardinalized Probability Hypothesis Density (BA-CPHD) filter provides a very promising approach that adequately addresses all the complexities and the nonlinear nature of this problem. In this paper, we present analysis, derivation, development, and application of a BA-CPHD implementation for tracking dim ballistic targets in environments with a range of unknown clutter rates, unknown clutter distribution, and unknown target probability of detection. The effectiveness and accuracy of the implemented algorithms are assessed and evaluated. Results that evaluate and also demonstrate the specific merits of the proposed approach are presented. © 2013 SPIE.
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spelling curtin-20.500.11937-558872017-09-13T16:10:51Z Background agnostic CPHD tracking of dim targets in heavy clutter El-Fallah, A. Zatezalo, A. Mahler, Ronald Mehra, R. Pereira, W. Detection and tracking of dim targets in heavy clutter environments is a daunting theoretical and practical problem. Application of the recently developed Background Agnostic Cardinalized Probability Hypothesis Density (BA-CPHD) filter provides a very promising approach that adequately addresses all the complexities and the nonlinear nature of this problem. In this paper, we present analysis, derivation, development, and application of a BA-CPHD implementation for tracking dim ballistic targets in environments with a range of unknown clutter rates, unknown clutter distribution, and unknown target probability of detection. The effectiveness and accuracy of the implemented algorithms are assessed and evaluated. Results that evaluate and also demonstrate the specific merits of the proposed approach are presented. © 2013 SPIE. 2013 Conference Paper http://hdl.handle.net/20.500.11937/55887 10.1117/12.2017994 restricted
spellingShingle El-Fallah, A.
Zatezalo, A.
Mahler, Ronald
Mehra, R.
Pereira, W.
Background agnostic CPHD tracking of dim targets in heavy clutter
title Background agnostic CPHD tracking of dim targets in heavy clutter
title_full Background agnostic CPHD tracking of dim targets in heavy clutter
title_fullStr Background agnostic CPHD tracking of dim targets in heavy clutter
title_full_unstemmed Background agnostic CPHD tracking of dim targets in heavy clutter
title_short Background agnostic CPHD tracking of dim targets in heavy clutter
title_sort background agnostic cphd tracking of dim targets in heavy clutter
url http://hdl.handle.net/20.500.11937/55887