On optimal dimension reduction for sensor array signal processing
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This paper treats data reduction in array processing for the spatially colored noise case. The purpose is to reduce the computational complexity of the applied signal processing algorithms by mapping the data into a space of lower dimension by means of a linear transformation. We discuss ways to implement the transformation and show that it suffices to estimate the array covariance matrix instead of the noise covariance matrix in the design process of the optimal transformation. Computer simulations are given that illustrate the problem of interference from out-of-band-sources that result when a beamspace transformation is designed to focus on a particular sector. The presents an dynamic state estimator. The method uses ANN based bus load prediction for the prediction step in the DSE.