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A Lower Dimensional MLE Algorithm for Distributed Source Parameter Estimation

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2 Author(s)
Qiang Li ; Coll. of Marine, Northwestern Polytech. Univ., Xi'an, China ; Hang Chen

In the area of the distributed sources parameter estimation, the conventional maximum likelihood estimation (MLE) algorithm, which being called 4D-MLE here, is a four dimensional nonlinear optimization problem, therefore its computation cost is very large. A lower dimensional MLE algorithm, which being simplified to three dimensional nonlinear optimization problem, is proposed. It is called 3D-MLE. Both of the two algorithms use the Newton type search algorithm to find the globe optimum. In a single search process, the 3D-MLE can reduce the inverse computation of covariance matrix for 51 times and matrix multiplication for 87 times than the 4D-MLE. The Cramer-Rao Bound (CRB) of the new MLE algorithm is shown, its computation cost is reduced also. The computer simulation validates that, the estimation accuracy of the 3D-MLE is similar to the 4D-MLE. The new algorithm not only reduces the computation cost but also avoids the loss of performance.

Published in:

Image and Signal Processing, 2009. CISP '09. 2nd International Congress on

Date of Conference:

17-19 Oct. 2009