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Robust variability index CFAR for non-homogeneous background

Subramanyan, Narasimhan Raman and Kalpathi, Ramakrishnan R. and Vengadarajan, A. (2019) Robust variability index CFAR for non-homogeneous background. In: IET RADAR SONAR AND NAVIGATION, 13 (10). pp. 1775-1786.


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Official URL: http://dx.doi.org/10.1049/iet-rsn.2018.5435


Radar signal detection using constant false alarm rate (CFAR) detectors encounters many non-ideal situations making it difficult to characterise the background. These include the presence of multiple targets, clutter edges and their combination in the reference window. Designing an efficient CFAR for these situations is a non-trivial problem. Algorithms based on ordered statistics (OS), outlier rejection using sorting and sample by sample hypothesis testing, variability index (VI), ordered data VI are proposed in the literature. These approaches require expensive sorting or prior information on the depth of censoring. In this study, the authors propose robust VI CFAR (RVI-CFAR) that obviates sorting. RVI-CFAR computes the threshold in multiple stages. The first stage uses VI-CFAR to determine an adaptive threshold. Outlier rejection in the computation of background, mean ratio (MR) and VI is carried out in subsequent stages. The updated MR and VI statistics are used to refine switching decisions at every stage of processing. RVI-CFAR exhibits low CFAR loss in homogeneous and multiple target scenarios, meanwhile achieving superior performance compared to other censored CFAR techniques. The proposed RVI-CFAR is evaluated and shown to be robust for all the cases of non-homogeneity compared to OS CFAR.

Item Type: Journal Article
Additional Information: Copyright of this article belongs to IEEE.
Keywords: statistical analysis; radar signal processing; radar clutter; radar detection; robust variability index CFAR; nonhomogeneous background; radar signal detection; constant false alarm rate detectors; nonideal situations; clutter edges; reference window; efficient CFAR; outlier rejection; sample hypothesis testing; ordered data VI; robust VI CFAR; homogeneous target scenarios; multiple target scenarios; censored CFAR techniques; OS CFAR; RVI-CFAR; ordered statistics
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 13 Feb 2020 10:57
Last Modified: 13 Feb 2020 10:57
URI: http://eprints.iisc.ac.in/id/eprint/63844

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