'Middle East Technical University, Faculty of Architecture'
Abstract
Handling of unknown correlation in the target information obtained from different sources is an important problem for consistent track fusion. Chernoff fusion technique is one of the popular approaches which produce conservative fusion results to bring this consistency. This method is based on exponential scaling of the input functions and it provides an analytical solution when input functions are Gaussian densities. The thesis mainly discusses the extension of the Chernoff fusion method to Gaussian Mixtures in a consistent and robust way and proposes an approximate approach for the computation of the fused output. The exponential scaling, required for Chernoff fusion, is based on a sigma-point approximation of the underlying functions. The resulting general fusion rule yields a closed form problem formulation that gives the fused function as a Gaussian mixture. Effectiveness of the fusion method is presented for simple but illustrative density fusion problems and compared to the optimal solutions and exact numerical Chernoff fusion. The technique is applied to the IMM filter used in target tracking problems. The results show the effectiveness of the method. The second application of the method is to fuse the PHD filter outputs that are Gaussian Mixture intensities. PHD filters are again used in target tracking. Different fusion architectures are investigated and their results are compared with each other. The comparison is also made with other available methods whenever they are applicable.Ph.D. - Doctoral Progra
