Open AccessParametric detector for subspace‐based distributed target detection in the presence of signal mismatch
Author(s) -
Xu Kaiming,
Deng Yunkai,
Yu Zhongjun,
Xu Zheng
Publication year - 2022
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/ell2.12390
Subject(s) - detector , scalar (mathematics) , parametric statistics , subspace topology , detection theory , algorithm , signal (programming language) , computer science , signal subspace , physics , electronic engineering , mathematics , artificial intelligence , telecommunications , engineering , statistics , noise (video) , geometry , image (mathematics) , programming language
In this letter, the authors investigate the problem of subspace‐based distributed target detection when signal mismatch arises. To solve the problem, a simple and effective detector is introduced, which is parameterised by a non‐negative scalar. By adjusting the scalar, the proposed detector can flexibly change its detection properties for mismatched signals. In particular, the proposed detector with a small scalar is robust to signal mismatch, while the detector with a large scalar is selective. Moreover, the proposed detector with an appropriate scalar can provide higher probability of detection than the existing detectors in the absence of signal mismatch. Both simulated and real data confirm the effectiveness of the proposed detector.