Abstract
Beamspace MUSIC (multiple signal classification) algorithm is often used to solve the DOA (direction of arrival) estimation problem to take advantage of the benefits of beamspace operations, such as reduced computation complexity, reduced sensitivity to system errors, reduced resolution threshold, reduced bias in the estimate, and so on. However, this method will fail to work properly when the source signals are coherent or strongly correlated, which are often encountered in sonar or radar environment. This paper uses the forward-backward spatial smoothing technique as the preprocessor of beamspace MUSIC for linear arrays, after which the coherence of the source signals can be removed in the covariance matrix. We show by computer simulation that the resolution of DOA estimation using beamspace MUSIC after spatial smoothing is better than using element space MUSIC after spatial smoothing. We also show that the beamspace MSUIC using spatial smoothing is more robust than element space MUSIC when there are system errors in the linear array.
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