Multiple Subspace-Based Target Detection in Deterministic Interference

Mengru Sun

doi:10.1109/LSP.2024.3491012

Multiple Subspace-Based Target Detection in Deterministic Interference

2024-01-01

0

PRE

AI

DOI：10.1109/LSP.2024.3491012

Original

Original request for help

Save

Abstract

En 中文

In this letter, the problem of detecting a multiple subspace-based target in the presence of deterministic interference is considered. To solve the problem, we utilize the Kullback-Leibler information criterion and model order selection rules to design detection schemes. The alternative hypothesis related to the most likely signal subspace is selected from multiple alternative hypotheses, and is tested versus the null hypothesis for target detection. Numerical examples verify the effectiveness of the proposed detection schemes, which can achieve the target detection and subspace-based target classification simultaneously.

Keywords:

Adaptive detection

deterministic interference

Kullback-Leibler information criterion

model order selection

multiple hypothesis test

Multiple Subspace-Based Target Detection in Deterministic Interference

Abstract

Journal

Organization