基于信号分解的海面微弱目标探测

Weak Target Detection in Sea Clutter Via Signal Decomposition

海面小目标的探测对于船舶、港口、海上钻井平台等的安全至关重要,然而由于海杂波具有非高斯、非线性和非平稳特性,导致雷达对于海面小目标的探测变得十分困难,为了有效地抑制海杂波,基于对海杂波特性以及目标特性的分析,该文提出了一种基于形态分量分析(Morphological component analysis,MCA)的方法来分离这两种不同的信号分量,MCA方法性能的好坏依赖于变换域的选择,该文利用相参积累后目标的稀疏性,从海杂波中有效地提取了目标信号。最后,利用实测数据验证了该方法的有效性。实验结果表明,该方法能有效抑制海杂波,提高雷达对海面小目标的检测性能。

Detection of a small target on the sea surface is very important for the security of drilling platform,ships,and port,etc.Due to the complex characteristics of sea clutter,such as non-Gaussian and non-stationary characteristics,radars can diffificultly detect weak,small targets on the sea surface.In order to suppress a sea clutter,based on the analysis of the sea clutter and target characteristic,this paper presents a method for separation of these two different backscatter signals by using the Morphological component analysis(MCA).A good performance of the MCA relies on the sparsity of different components in different transform domains.Thus,the target signal can be extracted from a sea clutter by using the target sparsity after the coherent integration.The proposed method is evaluated by the sea echo with the weak simulated target and real data.The obtained results show that the proposed method can effectively suppress the sea clutter and improve the performance of the weak target detection.