A Variable-Order FLOM Algorithm for Heavy-Tailed Clutter Suppression

Y. Rosa Zheng, Missouri University of Science and Technology

This document has been relocated to http://scholarsmine.mst.edu/ele_comeng_facwork/1409

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The normalized fractionally-lower order moment (FLOM) algorithm exhibits fast convergence but high excess mean squared error (MSE) when the order is less than 2. This paper proposes a method using variable order moments to adaptively changing the order during adaptation, thus achieving both fast initial convergence and low excess MSE in the steady state. The algorithm is applied to both Gaussian and heavy-tailed non-Gaussian clutter suppression in phased array applications. The results show better performances of the proposed algorithm over the normalized FLOM and normalized Least Mean Square (NLMS) algorithms. The proposed algorithm also performs well in other adaptive filtering applications such as system identification and noise/echo suppression.