A Sparsity-Based Passive Multistatic Detector

In this paper, we examine the problem of target detection for the multistatic passive radar. Passive radar systems leverage the existing wireless sources, such as radio/TV stations and cellular signals that are referred to as illuminators of opportunity (IOs), to illuminate the environment and provi...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2019-12, Vol.55 (6), p.3658-3666
Main Authors: Zhang, Xin, Sward, Johan, Li, Hongbin, Jakobsson, Andreas, Himed, Braham
Format: Article
Language:English
Subjects:
Cellular radio
Computer simulation
Delays
Detectors
Doppler effect
Eigenvalues and eigenfunctions
Frequency modulation
Generalized likelihood ratio test (GLRT)
Illuminators
Matematik
Mathematics
multistatic passive radar
Natural Sciences
Naturvetenskap
Passive radar
Probability Theory and Statistics
Radar equipment
Receivers
Sannolikhetsteori och statistik
Sensors
sparse signal
Sparsity
Surveillance radar
Target detection
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we examine the problem of target detection for the multistatic passive radar. Passive radar systems leverage the existing wireless sources, such as radio/TV stations and cellular signals that are referred to as illuminators of opportunity (IOs), to illuminate the environment and provide surveillance functions. Usually, these IO source signals are sparse or locally sparse in the frequency domain. We develop a passive multistatic detector by exploiting the sparsity or local sparsity of the IO signals. To improve the computational efficiency, two fast implementations of the proposed detector are also introduced. Simulation results show that the proposed approaches outperform the conventional passive detection methods that model the IO signals as unknown without any specific structures.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2019.2895710