On the Target Detection in OFDM Passive Radar Using MUSIC and Compressive Sensing

Watcharapong Ketpan, Seksan Phonsri, Rongrong Qian, Mathini Sellathurai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The passive radar also known as Green Radar exploits the available commercial communication signals and is useful for target tracking and detection in general. Recent communications standards frequently employ Orthogonal Frequency Division Multiplexing (OFDM) waveforms and wideband for broadcasting. This paper focuses on the recent developments of the target detection algorithms in the OFDM passive radar framework where its channel estimates have been derived using the matched filter concept using the knowledge of the transmitted signals. The MUSIC algorithm, which has been modified to solve this two dimensional delay-Doppler detection problem, is first reviewed. As the target detection problem can be represented as sparse signals, this paper employs compressive sensing to compare with the detection capability of the 2-D MUSIC algorithm. It is found that the previously proposed single time sample compressive sensing cannot significantly reduce the leakage from the direct signal component. Furthermore, this paper proposes the compressive sensing method utilizing multiple time samples, namely l1-SVD, for the detection of multiple targets. In comparison between the MUSIC and compressive sensing, the results show that l1-SVD can decrease the direct signal leakage but its prerequisite of computational resources remains a major issue. This paper also presents the detection performance of these two algorithms for closely spaced targets.

Original languageEnglish
Title of host publication2015 Sensor Signal Processing for Defence (SSPD)
PublisherIEEE
ISBN (Print)9781479974443
DOIs
Publication statusPublished - 2015
Event5th Sensor Signal Processing for Defence 2015 - Edinburgh, United Kingdom
Duration: 9 Sep 201510 Sep 2015

Conference

Conference5th Sensor Signal Processing for Defence 2015
Abbreviated titleSSPD 2015
CountryUnited Kingdom
CityEdinburgh
Period9/09/1510/09/15

ASJC Scopus subject areas

  • Signal Processing
  • Instrumentation

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