Time-averaged subspace methods for radar clutter texture retrieval

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

doi:10.1109/78.942618

Time-averaged subspace methods for radar clutter texture retrieval

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

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

24 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 language	English (US)
Pages (from-to)	1886-1898
Number of pages	13
Journal	IEEE Transactions on Signal Processing
Volume	49
Issue number	9
DOIs	https://doi.org/10.1109/78.942618
State	Published - 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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title = "Time-averaged subspace methods for radar clutter texture retrieval",

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.",

keywords = "Clutter cancellation, Frequency estimation, High-resolution radar, MUSIC and ESPRIT methods, Multiplicative noise, Radar clutter, Texture retrieval",

author = "Fulvio Gini and Giannakis, {Georgios B.} and Maria Greco and {Tong Zhou}, G.",

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.",

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AU - Gini, Fulvio

AU - Giannakis, Georgios B.

AU - Greco, Maria

AU - Tong Zhou, G.

N1 - 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.

PY - 2001/9

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N2 - 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.

AB - 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.

KW - Clutter cancellation

KW - Frequency estimation

KW - High-resolution radar

KW - MUSIC and ESPRIT methods

KW - Multiplicative noise

KW - Radar clutter

KW - Texture retrieval

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Time-averaged subspace methods for radar clutter texture retrieval

Abstract

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Keywords

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