Ocean Waves in K-distributed Clutter

<div> <div> <div> <p>Two examples of low grazing angle radar sea clutter, both well described by the compound K-distribution model, are studied. Pulse Doppler processing is applied to obtain two dimensional range-time textures for the intensity, centroid and width of the Doppler spectrum. The first example exhibits a monochromatic swell pattern, allowing phase averaging to be applied to the textures. The second example has a more typical ocean wave spectrum. The intensity textures are gamma distributed, consistent with the compound K-distribution model, but the Doppler spectrum centroid and width textures are also found to be gamma distributed. Based on this analysis, a new method for simulation of coherent radar sea clutter is proposed, where separate memoryless nonlinear transformations are applied to a simulated water surface to generate the spatially and temporally varying intensity, centroid and width of the Doppler spectrum. The method builds on the evolving Doppler spectrum model for radar sea clutter simulation and established methods for simulation of water surfaces. </p> </div> </div> </div>

Ocean Waves in K-distributed Clutter

<div> <div> <div> <p>Two examples of low grazing angle radar sea clutter, both well described by the compound K-distribution model, are studied. Pulse Doppler processing is applied to obtain two dimensional range-time textures for the intensity, centroid and width of the Doppler spectrum. The first example exhibits a monochromatic swell pattern, allowing phase averaging to be applied to the textures. The second example has a more typical ocean wave spectrum. The intensity textures are gamma distributed, consistent with the compound K-distribution model, but the Doppler spectrum centroid and width textures are also found to be gamma distributed. Based on this analysis, a new method for simulation of coherent radar sea clutter is proposed, where separate memoryless nonlinear transformations are applied to a simulated water surface to generate the spatially and temporally varying intensity, centroid and width of the Doppler spectrum. The method builds on the evolving Doppler spectrum model for radar sea clutter simulation and established methods for simulation of water surfaces. </p> </div> </div> </div>

Correlated Non-Coherent Radar Detection for Gamma-Fluctuating Targets in Compound Clutter

This work studies the problem of radar detection of correlated gamma-fluctuating targets in the presence of clutter described by compound models with correlated speckle. If the correlation is not accounted for in a radar model, the required signal-to-interference ratio for a given probability of detection will be incorrect, resulting in over-estimated performance. Although more generally applicable, the is focus on airborne maritime radar systems. Hence K-distributed sea clutter is used as the main example. Detection via square-law non-coherent pulse integration is formulated in a way that accommodates arbitrary partial correlation for both target radar cross-section (RCS) and clutter speckle. The obstacle to including this degree of generality in previous work was the fact that Swerling's original characterization of the standard RCS fluctuation classes as gamma distributions for the power is not sufficient for the inclusion of both correlation sources (i.e.target and clutter speckle) for gamma-fluctuating targets. An extension of the model is required at the quadrature component (i.e. voltage) level, as phase relationships can no longer be neglected. This is addressed in the present work, which not only postulates an extended model, but also demonstrates how to efficiently compute it, with and without a number of simplifying approximation schemes within the framework of the saddle-point technique.

Correlated Non-Coherent Radar Detection for Gamma-Fluctuating Targets in Compound Clutter

This work studies the problem of radar detection of correlated gamma-fluctuating targets in the presence of clutter described by compound models with correlated speckle. If the correlation is not accounted for in a radar model, the required signal-to-interference ratio for a given probability of detection will be incorrect, resulting in over-estimated performance. Although more generally applicable, the is focus on airborne maritime radar systems. Hence K-distributed sea clutter is used as the main example. Detection via square-law non-coherent pulse integration is formulated in a way that accommodates arbitrary partial correlation for both target radar cross-section (RCS) and clutter speckle. The obstacle to including this degree of generality in previous work was the fact that Swerling's original characterization of the standard RCS fluctuation classes as gamma distributions for the power is not sufficient for the inclusion of both correlation sources (i.e.target and clutter speckle) for gamma-fluctuating targets. An extension of the model is required at the quadrature component (i.e. voltage) level, as phase relationships can no longer be neglected. This is addressed in the present work, which not only postulates an extended model, but also demonstrates how to efficiently compute it, with and without a number of simplifying approximation schemes within the framework of the saddle-point technique.

Additional radar signature for waterborne object recognition

Subject and Purpose. The article is devoted to the radio recognition of moving waterborne objects (sea-going ships). The problem lies in the lack of radar signatures, which is especially true for coherent radar in continuous mode, implying that more signatures for the waterborne object recognition is highly needed. An additional signature can be gained just by means of a simple mathematical processing of target reflection signals. This is particularly important for radio recognition systems in current use because this will hardly complicate the system structure. Hence, it will not affect its cost either. Methods and Methodology. The method developed for the retrieval of an additional radar signature characteristic of waterborne objects moving across a rough sea surface is based on a simple mathematical processing of a signal reflected from the moving waterborne object and taken from the phase output of coherent radar. The method approbation is by the mathematical modeling of signals at the phase detector output in the event of three waterborne objects such that have identical scattering cross sections but different periods of the side and keel vibrations. Results. Based on the mathematical modeling results, it has been shown that each of the local scattering centers keeps the ratio of the linear speeds of side and keel vibrations approximately the same for the same object. But the employed ratio takes different values for different objects. Conclusion. Having a single standard coherent radar in continuous mode and guided by the developed methodology, one can gain an additional signature for the target recognition, which is a ratio of the linear speeds of side and keel vibrations of the target. The suggested methodology can be used for the radio recognition of waterborne objects moving across a rough sea surface.