Radar Target Detection with K-Nearest Neighbor Manifold Filter on Riemannian Manifold

In this paper, we propose a K-nearest neighbor manifold filter on the Riemannian manifold and apply it to signal detection within clutter. In particular, the correlation and power of sample data in each cell are modeled as an Hermitian positive definite (HPD) matrix. A K-nearest neighbor filter that...

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Main Authors: Dongao Zhou, Weilong Yang, Zhaopeng Liu, Manhui Sun
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:Advances in Mathematical Physics
Online Access:http://dx.doi.org/10.1155/2024/9257485
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author Dongao Zhou
Weilong Yang
Zhaopeng Liu
Manhui Sun
author_facet Dongao Zhou
Weilong Yang
Zhaopeng Liu
Manhui Sun
author_sort Dongao Zhou
collection DOAJ
description In this paper, we propose a K-nearest neighbor manifold filter on the Riemannian manifold and apply it to signal detection within clutter. In particular, the correlation and power of sample data in each cell are modeled as an Hermitian positive definite (HPD) matrix. A K-nearest neighbor filter that performs the weight average of the set of K-nearest neighbor HPD matrices of each HPD matrix is proposed to reduce the clutter power. Then, the clutter covariance matrix is estimated as the Riemannian mean of a set of secondary HPD matrices. Signal detection is considered as distinguishing the matrices of clutter and target signal on the Riemannian manifold. Moreover, to speed up the convergence of matrix equation of Riemannian mean, we exploit a strategy to choose the initial input matrix and step size of this equation. Numerical results show that the proposed detector achieves a detection performance improvement over the conventional detector as well as its state-of-the-art counterpart in nonhomogeneous clutter.
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institution Kabale University
issn 1687-9139
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spelling doaj-art-7801427c61b94731b00c45bf8509fd612025-02-03T11:27:57ZengWileyAdvances in Mathematical Physics1687-91392024-01-01202410.1155/2024/9257485Radar Target Detection with K-Nearest Neighbor Manifold Filter on Riemannian ManifoldDongao Zhou0Weilong Yang1Zhaopeng Liu2Manhui Sun3Academy of Military ScienceAcademy of Military ScienceAcademy of Military ScienceAcademy of Military ScienceIn this paper, we propose a K-nearest neighbor manifold filter on the Riemannian manifold and apply it to signal detection within clutter. In particular, the correlation and power of sample data in each cell are modeled as an Hermitian positive definite (HPD) matrix. A K-nearest neighbor filter that performs the weight average of the set of K-nearest neighbor HPD matrices of each HPD matrix is proposed to reduce the clutter power. Then, the clutter covariance matrix is estimated as the Riemannian mean of a set of secondary HPD matrices. Signal detection is considered as distinguishing the matrices of clutter and target signal on the Riemannian manifold. Moreover, to speed up the convergence of matrix equation of Riemannian mean, we exploit a strategy to choose the initial input matrix and step size of this equation. Numerical results show that the proposed detector achieves a detection performance improvement over the conventional detector as well as its state-of-the-art counterpart in nonhomogeneous clutter.http://dx.doi.org/10.1155/2024/9257485
spellingShingle Dongao Zhou
Weilong Yang
Zhaopeng Liu
Manhui Sun
Radar Target Detection with K-Nearest Neighbor Manifold Filter on Riemannian Manifold
Advances in Mathematical Physics
title Radar Target Detection with K-Nearest Neighbor Manifold Filter on Riemannian Manifold
title_full Radar Target Detection with K-Nearest Neighbor Manifold Filter on Riemannian Manifold
title_fullStr Radar Target Detection with K-Nearest Neighbor Manifold Filter on Riemannian Manifold
title_full_unstemmed Radar Target Detection with K-Nearest Neighbor Manifold Filter on Riemannian Manifold
title_short Radar Target Detection with K-Nearest Neighbor Manifold Filter on Riemannian Manifold
title_sort radar target detection with k nearest neighbor manifold filter on riemannian manifold
url http://dx.doi.org/10.1155/2024/9257485
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AT weilongyang radartargetdetectionwithknearestneighbormanifoldfilteronriemannianmanifold
AT zhaopengliu radartargetdetectionwithknearestneighbormanifoldfilteronriemannianmanifold
AT manhuisun radartargetdetectionwithknearestneighbormanifoldfilteronriemannianmanifold