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A Sparsity-Based Passive Multistatic Detector

Zhang, Xin ; Swärd, Johan LU ; Li, Hongbin ; Jakobsson, Andreas LU orcid and Himed, Braham (2019) In IEEE Transactions on Aerospace and Electronic Systems 55(6). p.3658-3666
Abstract
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... (More)
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. (Less)
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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
IEEE Transactions on Aerospace and Electronic Systems
volume
55
issue
6
pages
3658 - 3666
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85071127370
ISSN
0018-9251
DOI
10.1109/TAES.2019.2895710
language
English
LU publication?
yes
additional info
This work was supported in part by the National Science Foundation under grant ECCS-1609393, in part by the Swedish Research Council, and in part by the Crafoord's and Carl Trygger's foundations.
id
d1c97f22-a178-48ff-9fd8-9cadb7f87e8a
date added to LUP
2019-05-30 21:12:30
date last changed
2022-06-30 17:47:21
@article{d1c97f22-a178-48ff-9fd8-9cadb7f87e8a,
  abstract     = {{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.}},
  author       = {{Zhang, Xin and Swärd, Johan and Li, Hongbin and Jakobsson, Andreas and Himed, Braham}},
  issn         = {{0018-9251}},
  language     = {{eng}},
  number       = {{6}},
  pages        = {{3658--3666}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Aerospace and Electronic Systems}},
  title        = {{A Sparsity-Based Passive Multistatic Detector}},
  url          = {{http://dx.doi.org/10.1109/TAES.2019.2895710}},
  doi          = {{10.1109/TAES.2019.2895710}},
  volume       = {{55}},
  year         = {{2019}},
}