Novel radar signal sorting method based on geometric covering

With the increase of complexity of electromagnetic environment and continuous appearance of advanced system radars, signals received by radar reconnaissance receivers become even more intensive and complex. Therefore, traditional radar sorting methods based on neural network algorithms and support vector machine (SVM) cannot process them effectively. Aiming at solving this problem, a novel radar signal sorting method based on the cloud model theory and the geometric covering algorithm is proposed. By applying the geometric covering algorithm to divide input signals into different covering domains based on their distribution characteristics, the method can overcome a typical problem that it is easy for traditional sorting algorithms to fall into the local extrema due to the use of complex nonlinear equation to describe input signals. The method uses the cloud model to describe the membership degree between signals to be sorted and their covering domains, thus it avoids the disadvantage that traditional sorting methods based on hard clustering cannot deinterleave the signal samples with overlapped parameters. Experimental results show that the presented method can effectively sort advanced system radar signals with overlapped parameters in complex electromagnetic environment.