Parameter Estimation In Target Positioning

Accurate target positioning technique has been developed rapidly and applied in many military and civilian areas in the past decades.Firstly, the thesis introduces some basic definitions of target positioning and some widely used mathematical methods used in parameter estimation of target positioning. Then, the thesis focuses its research on the following two applications of target positioning: one is missile tracking and positioning, and the other satellite interferometer.In the aspect of missile tracking and positioning, the problems of trajectory parameter accuracy in the system of positioning by range rate information are studied, the thesis first considers error propagation of polynomial algorithm in the new system, which provides backup for the observation station distribution in the new system. Then the thesis studies the problem of using point by point window sliding algorithm to overcome problems caused by polynomial approaching. At last, the thesis compares error propagation of different trajectory and different observation station distribution through computer simulations. Simulation results show that in the case of polynomial point by point window sliding algorithm, the accuracy of trajectory parameter is relatively high compared to the point to point algorithm.In the aspect of satellite interferometer, the problems of how to use information of control points to estimate baseline parameters are studied. The thesis first introduces linear model of baseline parameters and validates its validity in the formation flying pattern. Then an existing baseline estimation algorithm based on ground control points is studied and simulated through computer. Based on the shortage of the above algorithm in the new pattern, an algorithm of baseline parameter estimation based on positioning equations of control points is proposed and simulated. Simulation results show that baseline parameter estimation accuracy is very high in this new algorithm, the algorithm is feasible. At last, some classic algorithm of baseline estimation based on control points are compared and evaluated.