We propose a novel system architecture that employs a matching pursuit-based basis selection algorithm for directions of arrival estimation. The proposed system does not require a priori knowledge of the number of angles to be resolved and uses very small number of snapshots for convergence. The performance of the algorithm is not affected by correlation in the input signals. The algorithm is compared with well-known directions of arrival estimation methods with different branch-SNR levels, correlation levels, and different angles of arrival separations.
A recent work explicitly models the discontinuous motion estimation problem in the frequency domain where the motion parameters are estimated using a harmonic retrieval approach. The vertical and horizontal components of the motion are independently estimated from the locations of the peaks of respective periodogram analyses and they are paired to obtain the motion vectors using a procedure proposed. In this paper, we present a more efficient method that replaces the motion component pairing task and hence eliminates the problems of the pairing method described. The method described in this paper uses the fuzzy c-planes (FCP) clustering approach to fit planes to three-dimensional (3-D) frequency domain data obtained from the peaks of the periodograms. Experimental results are provided to demonstrate the effectiveness of the proposed method.
In this paper, we propose a novel system architecture that employs matching pursuit algorithm for angle of arrival detection. Two different basis selection algorithms, namely matching pursuit and orthogonal matching pursuit are investigated. The complexity of the algorithms are comparable to that of a simple beamformer, however its resolution capabilities are shown to be much higher. The proposed system does not require apriori knowledge on the number of angles to be resolved and uses very small amount of snapshots for convergence. Also, the performance is not affected by the correlation of the signals to be resolved, and it does not have the maximum separation requirements that arise in the case of ESPRIT.
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