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- W2166114624 abstract "Maximum Likelihood Estimator (MLE) has been shown to be the best performance in Direction-Of-Arrival (DOA) estimation. However, the computational burden of a multidimensional grid search for MLE is very large. In order to resolve the question of computation burden, particle filtering methods are combined with maximum likelihood DOA estimator. A novel Maximum Likelihood DOA Estimator based on Particle Filtering (MLE-PF) is proposed. Numerical simulations illustrate the fact that MLE-PF keeps the perfect performance of MLE and reduces the computational complexity of MLE from O(L <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>K</sup> ) to O(K times N <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>s</sub> ). Also MLE-PF performs better than MUSIC and MiniNorm, especially in low SNRs." @default.
- W2166114624 created "2016-06-24" @default.
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- W2166114624 date "2007-01-01" @default.
- W2166114624 modified "2023-09-27" @default.
- W2166114624 title "Maximum Likelihood DOA Estimator Based on Particle Filtering" @default.
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- W2166114624 doi "https://doi.org/10.1109/icmlc.2007.4370556" @default.
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