Research On Parallel Architectures For Subspace-Based Super Resolution Algorithms

The main goal of spatial spectral estimation is to study all the algorithms about increasing the accuracy, the angle resolution, and the operation speed in estimating the angles of the spatial signals within bandwidth.During many direction-of-arrival estimation algorithms, subspace-based method is widely used because of the clearness of the physical concept and well estimation performance. Two kinds of the most representative methods are: Multiple Signal Classification (MUSIC) method and Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) method.Nevertheless, it needs huge quantity of computation, which baffles its further application in Modern Radar signal processing which has a high requirement on the speed of processing. Therefore, it is very necessary to study its high-speed implement methods. This article focuses on highly effective of high resolution approach from the aspect of parallel method. The parallel algorithms for sensor array processing algorithm of high-speed realization are complicated, not only depend on the performance of the chips, but also rely on the steps of the algorithm itself.Starting from MUSIC algorithm, this article made improvement in the stage of covariance matrix decomposition. After analyzing the structure of the array, found a simple and effective method of real value preprocessing, which changed this method from the plural field to the real field, thus reduced the computation greatly with little performance loss. Then selected two eigenvalue decompose methods which are suitable for prarllel proposing.According to the theoretical basis, this article developed parallel architecture for MUSIC algorithm, during the three stage of MUSIC algorithm: data covariance matrix stage, covariance matrix decomposition stage, power method stage, makes the parallelization improvement separately, thus improve the original method in real time. The effectiveness of the parallel algorithm has been verified through the simulations. At the same time, the advantages and disadvantages of the parallel algorithm has discussed by compared with the MUSIC method.After obtaining the parallel MUSIC algorithm, this article extends this approach to the ESPRIT algorithm. The parallel ESPRIT algorithm and the parallel MUSIC algorithm are similar except the stage of decomposition, where the ESPRIT algorithm involves decomposition of a generalized asymmetric matrix. This article has used the Lanczos method and the belt zero point displacement's QR method based on the QR method's foundation. The simulation results indicate the feasibility of the application of this method.