Performance Comparison of Time-Frequency Analysis Methods for Radar Signature Analysis

Choi, In-Sik; Rhee, Ill-Keun

doi:10.1109/fgcn.2008.6

“…Applications can be found ranging from speech enhancement in noise [7] to radar target analysis [8]. A common approach to adaptive time-frequency analysis involves a search for minimum entropy decompositions that concentrate power either in a small number of positions in the time-frequency plane, or a small number of coefficients in a multi-scale wavelet decomposition [9].…”

Section: Introductionmentioning

confidence: 99%

Contour representations of sound

Lim¹,

Shinn‐Cunningham

²

,

Gardner

³

2011

2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

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Abstract-Many signals are naturally described by continuous contours in the time-frequency plane, but standard time-frequency methods disassociate continuous structures into isolated "atoms" of energy. Here we propose a method that represents any discrete time-series as a set of time-frequency contours. The edges of the contours are defined by fixed points of a generalized reassignment algorithm. These edges are linked together by continuity such that each contour represents a single phase-coherent region of the timefrequency plane. By analyzing the signal across many time-scales, an over-complete set of contours is generated, and from this redundant set of shapes the simplest, most parsimonious forms may be selected. The result is an adaptive time-frequency analysis that can emphasize the continuity of long-range structure. The proposed method is demonstrated with a few examples.

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A lightweight UAV recognition algorithm based on micro-Doppler features

Wang

¹

,

Zhao

²

,

Luo

³

2021

2021 IEEE/CIC International Conference on Communications in China (ICCC)

1

0

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Sparse Contour Representations of Sound

Lim

¹

,

Shinn‐Cunningham

²

,

Gardner

³

2012

IEEE Signal Process. Lett.

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Abstract-Many signals are naturally described by continuous contours in the time-frequency plane, but standard time-frequency methods disassociate continuous structures into isolated "atoms" of energy. Here we propose a method that represents any discrete time-series as a set of time-frequency contours. The edges of the contours are defined by fixed points of a generalized reassignment algorithm. These edges are linked together by continuity such that each contour represents a single phase-coherent region of the timefrequency plane. By analyzing the signal across many time-scales, an over-complete set of contours is generated, and from this redundant set of shapes the simplest, most parsimonious forms may be selected. The result is an adaptive time-frequency analysis that can emphasize the continuity of long-range structure. The proposed method is demonstrated with a few examples.

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Performance Comparison of Time-Frequency Analysis Methods for Radar Signature Analysis

Cited by 3 publications

References 4 publications

Contour representations of sound

Contour representations of sound

A lightweight UAV recognition algorithm based on micro-Doppler features

Sparse Contour Representations of Sound

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