Compressive sensing based high-resolution passive bistatic radar

Muhammad Abdul Hadi*, Muhammad Naveed Tabassum, Saleh Alshebeili

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)

Abstract

Passive bistatic radar (PBR) systems using different communication signals can only offer low-resolution target detection due to their inherent low bandwidth. In this paper, compressive sensing (CS) is applied to multichannel FM and GSM PBR to achieve improved range-Doppler resolutions and avoid some limitations of classical multiband PBR processing. In CS context, block-structured time-domain dictionary which is formed from multichannel signals suffers from coherence when fine range resolution is employed. To overcome such a pitfall, this work first transforms the dictionary to spectral domain where only the most important spectral components are retained. Principle component analysis followed by a whitening method are then applied to this spectrally transformed data in order to reduce the dimensionality of problem, thereby reducing the dictionary size and most importantly fulfilling the required condition of dictionary incoherence for better CS-based recovery. Two different block-structured dictionary formations are tested. The performance of the recovery of spatially close targets, in both FM and GSM PBR setups, are reported.

Original languageEnglish
Pages (from-to)635–642
Number of pages8
JournalSIGNAL, IMAGE AND VIDEO PROCESSING
Volume11
Issue number4
Early online date4 Nov 2016
DOIs
Publication statusPublished - May 2017
MoE publication typeA1 Journal article-refereed

Keywords

  • Compressive sensing
  • Convex optimization
  • Enhanced PCA
  • Radar
  • Sparsity

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