Detection of radar targets by means of fractal error

Fractals provide a good description of natural scenes and objects based on their statistically self-similar property. They are also used to discriminate natural or man-made objects because natural objects have a better fitting to the fractional Brownian motion (fBm) model than artificial objects. Sea clutter as natural phenomena well fit to the fBm to induce little error. On the other hand, targets as man-made objects induce much more error because they Frequently deviate from the fBm model. Therefore, the fractal error has a good characteristic to detect targets buried in clutter. We modified the fractal error defined by Cooper to be suitable for radar image processing. For the X-band radar image, the performance of our proposed method is comparable to that of the Cooper's method. For the millimeter wave (MMW) radar images, our method is better than the Cooper's one.