Improvement And Research Of MUSIC Algorithm For DOA Estimation In Smart Antenna

As the key technique of the third generation mobile communication, smart antenna has got broad attentions in recent years. Smart antenna provides an efficient approach to solve frequency resource deficiency, improve the capacity and quality of mobile communication systems, and achieve anti-jamming and antimultipath. And the direction of arrival(DOA) estimation is an important aspect in the smart antenna research. Whether in the separation of uplink multi-user signals or in the downlink selective launch, the measurement of user signal's DOA is the essential premise to realize the directional launch of smart antenna.Among the algorithms of DOA estimation, as the super-resolution spatial spectrum estimation technique, Multiple Signal Classification(MUSIC) algorithm is one of the most classical algorithms. In the given precondition and meeting adaptive conditions, MUSIC algorithm can accurately estimate signal's DOA, and has very high resolution ability and estimation precision. However, when the system sample number and the number of antenna array elements are finite, or SNR is low and the incident signals are correlated or coherent,the performance of the algorithm sharply decreases and the algorithm even becomes invalid. Due to the limitation of this algorithm, this dissertation proposes two improved methods: one-dimension noise subspace-based spatial spectrum estimation algorithm and Improved MUSIC algorithm.One-dimension noise subspace-based method always assumes that only the minimum eigenvalue of the signal covariance matrix is the noise eigenvalue, and the corresponding eigenvector is the true noise vector and constructs the one-dimension noise subspace. Through MATLAB simulations, this improved algorithm can not only achieve the same resolution ability as the conventional MUSIC algorithm in ideal conditions, but also acquire the resolution ability and estimation precision that MUSIC algorithm can't obtain in the nonideal condition of so-called signal eigenvalue leakage. At the same time, the computational complexity is decreased.Improved MUSIC algorithm decomposes the signal covariance matrix and then make the signal subspace be orthogonal to the noise subspace by...