Small Target Detection In Sea Clutter Based On Fractal Theory

Sea clutter is the backscatter echo of the local sea level to the radar launch signal, which is influenced by the sea breeze and the waves. Sea clutter characteristics can be used to analyze the ocean state, to achieve sea level or low altitude small target detection. In some cases, whether there is a small target in the sea can not rely solely on the amplitude of the echo to determine the use of a variety of signal processing process for the sea clutter data preprocessing is conducive to the sea clutter background detection of the target. It is the main research content of this paper to study the internal physical characteristics of sea clutter by using multiple fractal theory. It is the main research content of this paper to complete the small target detection by the fractal difference between target signal and sea clutter signal.Based on the analysis of the characteristics of the sea clutter signal by the detrended fluctuation analysis,the fractal characteristics of the sea clutter are studied.In the process of calculating the Hurst index, according to the influence of the scale-free interval selection on the fractal parameter extraction, an improved scale-Selection method, the more accurate Hurst index is successfully extracted, which effectively distinguishes the target sequence from the sea clutter sequence.In order to reduce the influence of complex sea conditions on small target detection in sea clutter background and improve the accuracy of weak signal detection, the fractal characteristics of sea clutter data under high scale condition are analyzed by multifractal detrended fluctuation analysis. Extended to [-30,30], the estimation of multifractal parameters is studied, and a small target detection method for sea clutter based on high scale fractal difference is proposed. The experimental results show that when the high scale index is selected, the proposed method can effectively distinguish the fractal difference between the moving target and the pure sea clutter,and complete the target detection.Based on the basic principle of double-tree complex wavelet transform, a fractal feature algorithm based on double-tree complex wavelet transform is proposed. The non _ stationary time series is decomposed by the anti - aliasing and translation invariance of double - tree complex wavelet transform to complete the multi - analysis. Based on the relationship between the scale index and the curve, the generalized Hurst exponent is obtained by local integral method. Finally, the algorithm is applied to the actual sea clutter data and it is found that the detection probability has been improved obviously under the same false alarm probability.