Research Of Unknown Radar Signal Sorting Algorithm

Radar signal sorting plays an important part in the radar signal processing system and has been an extremely important factor of future war. By radar signal sorting, we can accurately identify various radars and their parameters which are placed to the radar library to make further processing, such as locating and tracking and analysis. With the rapid development of radar signal generation technology and processing technology, the new system radar has replaced the traditional conventional radar, so radar signal environment has become increasingly complex and volatile confrontation. How to sort the radar signal accurately in an increasingly complex environment has become the focus of attention at home and abroad.This paper introduces PRI sorting algorithms and makes a brief explanation for advantages and disadvantages of each algorithm.Since then, two new clustering algorithms have been applied to the field of unknown radar signal sorting. A grid-based density clustering algorithm uses the grid meshing technology to divide the data space into subspaces. Then we map the PDW stream to each grid cell, and adopt the grid-based density cluster method to achieve PDW stream sorting. Compared with the traditional support vector clustering algorithm, the improved support vector clustering algorithm uses support vector instead of all samples of data sets to reduce the incidence matrix of the scale during the cluster assignment phase. At the same time, the improved algorithm applies the centre merged together algorithm to relieve nuclear function parameters q to affect the outcome, which makes clustering precision has become much. These two algorithms simulation results effectively demonstrate that they can achieve the accurate sorting even in a complex environment.