Abstract
In the context of coherent signal classification, spatial smoothing is necessary for the application of the eigen-based direction of arrival (DOA) estimation methods. However, the currently known spatial smoothing algorithms not only reduce the effective aperture of the array, but also do not consider the cross correlations of the subarray outputs. An improved spatial smoothing algorithm which can fully utilize the correlations of the array outputs and produce a more stable estimate of the covariance matrix is presented. Simulation results are provided to verify the theoretical prediction. The superiority of this method over the conventional methods is obvious, especially when the SOSR (subarray to overall size ratio) is small. >
Published Version
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