Abstract

Searching of the sea clutter mathematical model is carried out in this paper. It is suitable to create based on it algorithm for small slow moving targets detection by marine radars. The compound Gaussian model for modeling sea clutter amplitude stochastic distribution is selected as a result of the sources analysis, because it was confirmed by most of researches. The discussed in the literature model based on chaos theory is choosen as perspective alternative for stochastic model; its advantage of using it for such problems solution must be definitively proved or denied. It was proposed many different distributions for high resolution sea clutter amplitude data modeling. The most frequently reported in the literature are K, Log-Normal and Weibull distributions. K distribution belonging to a compound-Gaussian model has the most significant theoretical and experimental background. This distribution choice is physically explained basing on the processes taking place when electromagnetic waves scattered from capillarity and gravity sea waves create a composed echo. Signal representing this echo is the product of two random components, called texture and speckle. Texture is the result of scattering from gravity waves, has a Gamma pdf (in case of K distribution) and corresponds to slow-varying large-scale structure. Speckle is the result of scattering from isolated scatterers (capillarity waves), has a Rayleigh pdf and corresponds to rapid varying small-scale structure. So, K distribution envelope is a compound distribution consisting of a locally Rayleigh distribution speckle whose mean is modulated by a gamma distribution texture. All researches consider Rayleigh pdf for speckle. The lognormal, generalized Gaussian, inverse gamma and some other distributions were proposed for the texture. Due to literature analyses it is seen that texture distribution depends on radar range resolution, but strong dependence is not proved. Some scientists modified K distribution to K-A distribution consisting of the Rayleigh, gamma and Poisson distributions to describe better spikes appearence caused by whitecaps and bursts. Using of Weibull-Weibull (WW) and KK distributions was proposed for high grazing angle and high resolution sea clutter. Doppler characteristics of the sea clutter has been investigated by many researchers and now we have well developed theory. It is known empirical behavior of sea clutter doppler spectrum for different conditions – grazing angle, resolution, wind speed, polarisation and others. Lee, Walker and Ward models are used for sea clutter doppler spectrum describing. Fast moving targets can be effectively detected in heavy sea clutter by doppler radars. But existing theory cannot improve detection of slow moving small targets in heavy sea clutter, because slow moving targets have doppler shift compared to doppler shift of sea clutter. Correlation properties of high resolution sea clutter cannot be derived from its doppler spectrum. In alternative to stohastic model, many researches prefer deterministic model and use chaos theory to describe sea clutter. This choise is based on the fact that both hydrodynamic and electromagnetic therory relying on deterministic models only. If deterministic theory usefulness in applying to high resolution see clutter description be proved completely, it can lead to great progress for small targets in heavy sea clutter detection; because in this case sea clutter behavior can be predicted if initial conditions are precisely known. Using chaotic model for high resolution sea clutter description is highly disputed in recent years, and many researches have questioned first results of high resolution sea clutter describing with chaotic theory usage by Haykin. But great possibilities can give deterministic model for small targets detection definitively proving its ability to describe high resolution sea clutter data precisely causes different scientists to return to chaos theory again and again. Promising results in this field was obtained by using multifractal theory, but still there are not strong methodological background of using deterministic models for small slow moving targets in sea clutter detection, so it is required to make research to prove or deny deterministic models usefulness for high resolution sea clutter data description.

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