Effect of subarray size on direction estimation of coherent cyclostationary signals based on forward-backward linear prediction
The effect of subarray size (equal to the order of the prediction model plus one) on the estimation performance of a previously proposed forward-backward linear prediction (FBLP) based cyclic method is investigated. This method incorporates ail overdetermined FBLP model with a subarray scheme and is used to estimate the directions-of-arrival (DOAs) of coherent cyclostationary signals impinging on a uniform linear array (ULA) from the corresponding polynomial or spectrum formed by the prediction coefficients. However, the decorrelation is obtained at the expense of a reduced working array aperture, as it is with the spatial smoothing (SS) technique. In this paper, an analytical expression of the mean-squared-error (MSE) of the spectral peak position is derived using the linear approximation for higher signal-to-noise ratio (SNR). Then the subarray size that minimizes this approximate MSE is identified. The effect of subarray size on the DOA estimation is demonstrated and the theoretical analysis is substantiated through numerical examples.
linear prediction spatial smoothing cyclostationarity directions-of-arrival estimation taylor series expression