Signal fusion‐based targets detection in the presence of clutter and subspace interference for multiple‐input‐multiple‐output radar
Author(s) -
Li Zhihua,
Su Hongtao,
Zhou Shenghua,
Hu Qinzhen
Publication year - 2019
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2018.5012
Subject(s) - clutter , interference (communication) , subspace topology , computer science , radar , fusion , signal (programming language) , artificial intelligence , sensor fusion , signal subspace , pattern recognition (psychology) , telecommunications , noise (video) , channel (broadcasting) , image (mathematics) , programming language , linguistics , philosophy
In this study, a signal fusion‐based target detection algorithm for frequency diversity multiple‐input‐multiple‐output radar in the presence of clutter and subspace interference is investigated. Remarkably, the proposed algorithm can not only ensure a unique solution for the involved optimisations but also get a good detection performance at a low communication cost. Furthermore, the proposed detector processes a constant false alarm rate with respect not only to the unknown spectral properties of the unstructured interference but also to the structured interference distribution. Simulation experiences in several scenarios indicate that the proposed algorithm has significant improvement in detection performance over conventional detection algorithms.
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