Sorting Technology Research, Dense Signal Environment

Signal sorting is a very important problem in electroniccountermeasures. Plane transformation and artificial intelligencesystem based on neural network are novel ways appeared in severalyears. But it is difficult to satisfy the conditions of these two methodsin practical application. Nowadays, cumulative difference histogram(CDIF) and sequential difference histogram (SDIF) are used widely inengineering-oriented application. In this thesis, these methods areintroduced, simulated and compared.The special radar signal environment we face in electronic warfareis high pulse-density and high pulse-losing probability. Under this kindof environment, due to losing and changing of pulse information, thevalidity of the conventional sorting algorithms falls a lot.This thesis is well researched for signal sorting under this kind ofsignal environment. A real-time signal sorting system is designed andthe sorting algorithm based on the probability statistics is improved.Besides, the two-step TOA difference correcting algorithm and theCDIF correcting algorithm are presented. The feasibility of this sortingsystem and the algorithms is verified by lots of simulated experiments.It is easy to implement the system and the algorithm because of theirdirect architecture, which is highly advantageous to real-time sorting.At last, the system is implemented by programming with VHDLlanguage and C language.