Various techniques for detecting anomalous reflective objects that extend a few tens of pixels in a SAR image are discussed. These techniques assume some prior knowledge of the object, to make the detection process robust and minimize false alarms. The basis of the method is a CFAR technique that assumes Weibull clutter statistics. The method is then augmented using knowledge of the shadow cast by the object, change detection, and information from terrain databases. Examples using a simulated SAR image are given.
A model for the signal returns from terrain features for a Synthetic Aperture Radar is developed. A standard range-azimuth geometry is used to divide the surface area into cells for which clutter returns are generated. This geometry is extended to a spherical Earth to introduce effects due to varying terrain height and slope, and to determine areas of shadow. The calculation of phase variation in the returned pulses at the IQ level required to successfully form a SAR is discussed. The technique is illustrated with an example which demonstrates the effect of look angle on SAR images.
Performance in an MPRF mode of an airborne pulse-Doppler radar is limited by the presence of surface clutter. Analysis of the behavior of clutter and noise data collected from an experimental radar system is performed and compared with the results of simulations. The suitability of the Weibull distribution in representing the statistical behavior of real and simulated data, as input to a CFAR thresholding scheme, is assessed.
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