Time-averaged subspace methods for radar clutter texture retrieval

Fulvio Gini, Georgios B. Giannakis, Maria Greco, G. Tong Zhou

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Subspace approaches have become popular in the last two decades for retrieving constant amplitude harmonics observed in white additive noise because they may exhibit superior resolution over the FFT-based methods, especially with short data records and closely spaced harmonics. We demonstrate here that MUSIC and ESPRIT methods can also be applied when the harmonics are corrupted by white or wideband multiplicative noise. The application context is the retrieval of texture information from high resolution and low grazing angle radar clutter data affected by wideband colored speckle that is modeled as complex multiplicative noise. Texture information is fundamental for clutter cancellation and constant false alarm rate (CFAR) radar detection. A thorough numerical analysis compares the two subspace methods and validates the theoretical findings.

Original languageEnglish (US)
Pages (from-to)1886-1898
Number of pages13
JournalIEEE Transactions on Signal Processing
Volume49
Issue number9
DOIs
StatePublished - Sep 2001

Bibliographical note

Funding Information:
Manuscript received May 22, 2000; revised June 4, 2001. The work of F. Gini and M. Greco was supported by the Italian Space Agency (ASI) through Project ZODA900167. The associate editor coordinating the review of this paper and approving it for publication was Dr. Olivier Besson.

Keywords

  • Clutter cancellation
  • Frequency estimation
  • High-resolution radar
  • MUSIC and ESPRIT methods
  • Multiplicative noise
  • Radar clutter
  • Texture retrieval

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