Multifunctional Radar Signal Sorting Based on ILPVG Network

In order to solve the problem of which complex network is more effective for multifunction radar signal sorting, an improved limited penetrable visual graph (ILPVG) algorithm is proposed, and different complex network building algorithms are used to analyze the network model according to the topological attributes and centrality indicators of the complex network. Then, the radar signal sorting results are obtained by detecting the community structure through label propagation algorithm and density peak clustering algorithm. Simulation results show that the complex networks based on ILPVG algorithm and limited penetrable visual graph (LPVG) algorithm are higher than other networks in terms of network connectivity and compactness in the multifunction radar sorting scenario. The sub-community results and radar sorting accuracy obtained by the ILPVG network through the label propagation algorithm are higher than those of other networks, and the radar signal sorting accuracy is 3. 46% higher than that of LPVG, and significantly better than those of sorting methods based on the k-means and density-based spatial clustering of applications with noise algorithm, which indicates the effectiveness and superiority of the ILPVG algorithm in radar signal sorting.