Laser radar target detection based on fractional Brownian motion model

The fractal characteristics of the laser radar s echo and duller are researched and analyzed. Based on the fraction Brownian motion (FBM) model and analysis of different signal-to-noise ratio (SNR) of the laser radar echo, it proves that the laser radar echo data can be processed has the characteristic of Brownian motion. Because the clutter of the laser radar has increment self-similar characteristic of Brownian motion, it can match the fractal Brownian motion. So the laser radar echo data can be processed by adopting the Brownian motion model. When the SNR of the target echo is small, the fractal dimension of the clutter and target echo is similar. The target can not be detected by the single fractal dimension. But the fractal dimension of the clutter and target is different in the different fractal scale. A method to detect the target by the characteristic of the different fractal dimension of the target and the clutter is advised. This method is called target detect algorithm based on multi fractal dimension. The theory and experiment result shows that this algorithm is reliable and accurate.