Parameter Estimation Of Distributed Sources

The targets have their actual "size" other than a point, so using the distributed model to describe the target can be more exactly fixed with the true target than a point source, can more satisfy the request of the modern weapons to target identification and attack with precision. The thesis studies parameter estimation of distributed sources, which comes from the national defense science technology fund. It has great meaning on theory and in practice.The thesis analyzes the methods for parameter estimation of distributed sources in detail, and low complexity estimators, comes up with RELAX in parameter estimation and robust method of high resolution parameter estimators for distributed sources, and gives theory analysis and simulation results. The main work is:1) This text gives a study of the signal models of two kinds of distributed sources: coherent distributed sources and incoherent distributed sources, analyzes eigenvalue distribution of correlation matrix.2) Systematically introduced parameter estimation of distributed sources on the base of models, including the maximum likelihood estimate, least squares estimator, DSPE, DISPARE, etc. 3) Studied four low complexity algorithms: one order approximation, two point sources approximation, traditional beamforming and RELAX of parameter estimation. All this are suboptimal algorithms, but have low complexity, so are of great value in practice. It is proved that Traditional beamforming is consistency. RELAX can simplify the process when there are mare than one source to be estimated.4) Presented method of improving DOA estimation performance of distributed sources via projection pretransformation.5) Finally the study result is applied to beamforming of smart antenna and missile fuze system, and the simulation results illustrate that distributed sources are more accurate than point sources with improving effects.