Indukumar, KC and Reddy, VU (1993) Optimum Weighted Smoothing in Finite Data. In: IEEE Transactions on Signal Processing, 41 (6). 2265 -2269.
In this correspondence, we consider a generalized smoothing problem and develop a procedure to obtain a set of optimum weights which gives minimum mean-squared error (MSE) in the estimates of directions of arrival of signals in finite data when the signals are arbitrarily correlated. Using the optimum weights, we study the optimum tradeoff between the number of subarrays and the subarray size for a fixed total size of the array. The computation of optimum weights, however, requires full knowledge of the scenario. Since exact DOA’s, powers, and correlations of signals are unknown a priori, we give a method to estimate these weights from the observed finite data. We also show through empirical studies that the optimum weights can be approximated with Taylor weights which serve as near-optimum weights. Simulation results are included to support the theoretical assertions.
|Item Type:||Journal Article|
|Additional Information:||Copyright 1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Department/Centre:||Division of Electrical Sciences > Electrical Communication Engineering|
|Date Deposited:||22 Aug 2008|
|Last Modified:||19 Sep 2010 04:26|
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