Using fractal dimension to target detection in bistatic SAR data

This paper proposes an algorithm for estimating the fractal dimension of real sea bistatic synthetic aperture radar data. The algorithm is based on the use of the fractal dimension estimated by the box counting method to detect the sub-data which contain the targets. Based on this approach, the performance of the fractal detector proposed in this paper was demonstrated by the evaluation of the probability of detection by means of Monte Carlo simulation and was verified that we can use the fractal dimension to distinguish between targets and clutter, even for a small signal-to-noise ratio.