Analysis of subspace-based direction of arrival estimation methods |
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Authors: | Bhaskar D Rao KVS Hari |
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Affiliation: | (1) AMES Department — System Science, University of California, 92093-0411 San Diego, La Jolla, California, USA |
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Abstract: | In this paper, a general framework for the analysis of eigen-based subspace methods is developed. It is shown that a two-step procedure can be effectively used to analyse subspace methods under fairly general conditions. The first step relates the errors in the covariance matrix to errors in the subspaces, and the second step relates error in the subspaces to the errors in the direction of arrival (doa) estimates. Combining these two steps along with the statistics of the data, expressions for the mean squared error in thedoa estimate are derived. The potential of the approach is demonstrated by analysing two subspace methods,music and the minimum-norm method. This work was supported by the USarmy Research Office under Grant No.daal-03-90-g-0095. |
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Keywords: | Array processing direction of arrival estimation subspace methods statistical analysis |
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