D Doa Estimation Of High-speed Parallel Implementation

Array signal processing and its application has been one of the focuses in signal processing field. By sampling and processing signal both in time domain and in spatial domain, the information of interested contained in the signal can be exploited sufficiently. It is widely applicated in radar,sonar and communications. DOA estimation and beamforming technique is two most important aspects of array signal processing, and DOA estimation is the central problem in spatial spectrum estimation.There are mainly two type of algorithms used for spatial spectrum estimation: one is those based on Bayesian Maximum Likelihood method, like the ML (Maximum Likelihood) algorithm, Maximum Entropy method and etc., the others are based on the spatial decomposition or projection of correlation matrix, this kind of algorithm include Vector Characterization Method, MUSIC (Multiple Signal Classification) algorithm, Projection Matrix Method, etc. MUSIC is a classical spatial spectrum estimation algorithm that has a super high resolution and is widely used today, however, it cannot estimate DOA of signals that are correlated. The ML algorithm can be used for the DOA estimation of correlated signals, but it has a huge computational load. Fortunately, we can solve this problem by using AP (Alternating Projection) algorithm, by this way; the computational load can reduce dramatically.DOA estimation is mostly research base on linear array, because of the limitation of linear, it can estimate the azimuth only;solid array can estimate the azimuth and elevation,in this paper, the solid array is used for DOA estimation; when the signal sources are uncorrelated, the MUSIC algorithm is chosen, using MDL/AIC algorithm,we attain the signal number of sources. By further study the array geometry and MUSIC algorithm, a couple of methods are proposed, which can decrease the amount of calculation of DOA estimation. When the signal sources are correlated, a more efficient algorithm is proposed, which integrate the MUSIC and ML-AP algorithm. Also, the eigndecomposition algorithm, which is needed in MUSIC algorithm is introduced.In order to make the DOAs estimation faster, this paper discuss how to used multiple DSPs to parallel implement the algorithm. The above-mentioned algorithm and their implementation procedures are fully discussed in this paper.