Coherent Long-Time Integration and Bayesian Detection With Bernoulli Track-Before-Detect

Uney, Murat ORCID: 0000-0001-6561-0406, Horridge, Paul, Mulgrew, Bernard and Maskell, Simon ORCID: 0000-0003-1917-2913 (2023) Coherent Long-Time Integration and Bayesian Detection With Bernoulli Track-Before-Detect. IEEE SIGNAL PROCESSING LETTERS, 30. pp. 239-243.

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Official URL: http://dx.doi.org/10.1109/lsp.2023.3253039

Abstract

We consider the problem of detecting small and manoeuvring objects with staring array radars. Coherent processing and long-time integration are key to addressing the undesirably low signal-to-noise/background conditions in this scenario and are complicated by the object manoeuvres. We propose a Bayesian solution that builds upon a Bernoulli state space model equipped with the likelihood of the radar data cubes through the radar ambiguity function. Likelihood evaluation in this model corresponds to coherent long-time integration. The proposed processing scheme consists of Bernoulli filtering within expectation maximisation iterations that aims at approximately finding complex reflection coefficients. We demonstrate the efficacy of our approach in a simulation example.

Item Type:	Article
Uncontrolled Keywords:	Bernoulli filter, coherent detection, long-time integration, staring-array radar, track-before-detect
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	04 Apr 2023 10:57
Last Modified:	20 Apr 2023 18:52
DOI:	10.1109/LSP.2023.3253039
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3169446