A Systematic Fusion Design Of Air Surveillance Radar's

This paper is based on data fusion theory. The design of radar data fusion system about air surveillance radar's was realized. This system includes several aspects such as error registration, data association and target state estimation.At first, the coordinate is changed and then the method about linear programming in radar measure ordination is used to estimate system error. The simulation results show that error correction can restrain random noise and estimate the systematic error of the radars well and truly.Secondly, a new algorithm about data association used "unitary association" combining with "dynamic subarea" in this paper is suggested which reduce the computable quantity and the error rate of data association. The system practical implementation capability is enhanced by the algorithm. We use the method to make process efficient and practical. Simultaneity, the grey system theory is applied into the fusion system to utilize efficiently air surveillance radar's data and to avoid the influence of bad data.Thirdly, in target tracking "blur similitude" and "unitary association" are taken to start track .The method of sequential filter in real time is used to make the tracks of all air surveillance radar's fuse favoring. When some special circs come, some superior analyses are used to solve the correlation of the dissimilar radars.All the methods mentioned in this paper are used to acquire a realizable data flow of software .And the course of target integration is simulated in C++ Builder.