Contribution of the fractal dimension to multiscale adaptive filtering of SAR imagery

Germain, Mickaël; Bénié, G.B.; Boucher, Jean‐Marc; Foucher, Samuel; Fung, K. Fung Kee; Goı̈ta, Kalifa

doi:10.1109/tgrs.2003.811695

Cited by 16 publications

(8 citation statements)

References 18 publications

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“…New data sets will have fractal features which will make it possible to define clearly the source of emission. The fractal features and the theory of fractals is adopted by researchers especially in the field of SAR (Synthetic Aperture Radar) image transformation [13,14], acoustic signal transformation and the analysis of radar signals. New possibilities of Digital Signal Processing (DSP) in Frequency Modulated Continuous Wave (FMCW) radar and fractal image compression is a promising brand new compression method [15,16].…”

Section: Specific Identification Of Emitter Sources Extraction Of Frmentioning

confidence: 99%

Identification of emitter sources in the aspect of their fractal features

Dudczyk¹,

Kawalec²

2013

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. This article presents the procedure of identification radar emitter sources with the trace distinctive features of original signal with the use of fractal features. It is a specific kind of identification called Specific Emitter Identification, where as a result of using transformations, which change measure points, a transformation attractor was received. The use of linear regression and the Lagrange polynomial interpolation resulted in the estimation of the measurement function. The method analysing properties of the measurement function which has been suggested by the authors caused the extraction of two additional distinctive features. These features extended the vector of basic radar signals' parameters. The extended vector of radar signals' features made it possible to identify the copy of radar emitter source.

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Section: Specific Identification Of Emitter Sources Extraction Of Frmentioning

confidence: 99%

Identification of emitter sources in the aspect of their fractal features

Dudczyk¹,

Kawalec²

2013

Bulletin of the Polish Academy of Sciences: Technical Sciences

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“…New data sets will have fractal features which will make it possible to define clearly the source of radar emission. The fractal features and the theory of fractals is adopted by researchers, especially in the field of SAR (Synthetic Aperture Radar) image transformation [8,9], acoustic signal transformation and the analysis of radar signals. New possibilities of Digital Signal Processing (DSP) in Frequency Modulated Continuous Wave (FMCW) radar and fractal image compression is a promising brand new compression method [10,11].…”

Section: Defining the Transformation Attractor And Distinctive Featurmentioning

confidence: 99%

Specific Emitter Identification Based on Fractal Features

Dudczyk¹

2017

Fractal Analysis - Applications in Physics, Engineering and Technology

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If we take into consideration the fact that the radar signal recognition and identification process is an integral part of contemporary combat operations, the importance of the fractal analysis increases significantly. For this reason, the fractal analysis is used in the process of radar sources identification on the contemporary battlefield. Radar Signal Recognition (RSR) with the use of classical methods, that is based on statistical analysis of basic measurable parameters of a radar signal, such as Radio Frequency (RF), Amplitude (A), Pulse Width (PW) or Pulse Repetition Interval (PRI) is not enough to carry out the distinction process of particular copies of the same radar type. Only by this approach, the identification process of particular copies in a set of the same type emitters can be carried out. As a result, it is possible to maximize Correct Identification Coefficient (CIC) in the final stage of the recognition process, which is realized in Electronic Warfare (EW) systems. One of the most important elements of the whole recognition and identification process, which is realized in ELectronic INTelligence (ELINT) battlefield system, is building a measurement data vector, then a radar's metrics and the same database. This approach is called Specific Emitter Identification (SEI).

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“…New data sets will have fractal features which will make it possible to dene clearly the source of emission. The fractal features above and the theory of fractals is adopted by researchers especially in the eld of synthetic aperture radar (SAR) image transformation [4,5], acoustic signal transformation and the analysis of radar signals. As the authors of this article claim, the identication of emitter sources based on classical methods of the analysis of basic parameters is currently inecient.…”

Section: Introductionmentioning

confidence: 99%

Fractal Features of Specific Emitter Identification

Dudczyk

Kawalec

2013

Acta Phys. Pol. A

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This article presents the issues connected with emitter sources identication with low distinctive primary features of a signal. It is a specic type of identication called specic emitter identication, which distinguishes dierent copies of the same type of emitter. The term of specic emitter identication was presented on the basis of fractal features received from the transformation of measurement data sets. The use of linear regression and Lagrange polynomial interpolation resulted in the estimation of measurement function. The method analysing properties of measurement function which was suggested by the authors caused the extraction of two additional distinctive features. The features above extended the vector of basic radar signals' parameters. The extended vector of radar signals' features made it possible to identify the copy of emitter source.

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Contribution of the fractal dimension to multiscale adaptive filtering of SAR imagery

Cited by 16 publications

References 18 publications

Identification of emitter sources in the aspect of their fractal features

Identification of emitter sources in the aspect of their fractal features

Specific Emitter Identification Based on Fractal Features

Fractal Features of Specific Emitter Identification

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