Angle Estimation for Adaptive Linear Array using PCA-GS-ML Estimator

作者:Wu, Jianxin*; Wang, Tong; Bao, Zheng
来源:IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(1): 670-677.
DOI:10.1109/TAES.2013.6404132

摘要

The maximum likelihood (ML) angle estimator can yield optimal angle estimation performance. In the work presented here, a fast algorithm for solving the global optimal solution of the ML angle estimator based on principal component analysis (PCA) and grid search (GS) is developed. Utilizing the low-rank property of the mainbeam steering matrix, the log-likelihood function can be decomposed as a combination of the relevant quantities of basis vectors of the low-rank subspace. Thus, evaluation of the log-likelihood function can be realized in a lower dimensional space. Although GS is also required, the computational complexity can be greatly reduced, and the global optimal solution can be obtained.

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