Implementation of MWF based on noise subspace estimation

The interference suppression of GPS received signal is realized by utilizing array antenna in this paper, and time delay is introduced for signal processing, thus forming a spatial-time two dimension processing mode. To realize the two dimensional processing on interference suppression, the large amount of operation is a difficulty, so it is necessary to reduce the rank. Multistage Weiner Filter (MWF) is an effective way to reduce the rank of the filter, but a drawback exists, that the subspace rank of noise can't be estimated with the classical MWF method. The MWF is analyzed in this paper, and the analytical part of MWF is adopted to map the received signal into a new signal vector. Through analyzing the covariance matrix of the new signal vector, a robust method is proposed to estimate the subspace rank. Simulations show that the subspace rank can be estimated accurately by the proposed method. Comparing the proposed method with the traditional method of setting the threshold of MSE, the subspace rank estimated is more accurate and credible, and it exhibits superior anti-jam performance.