Research On Direction Of Arrival Estimation Algorithm In Smart Antenna

Smart antenna is a popular technology in the third generation mobile communications system, which is capable of reducing the interference, extending the coverage area of system, increasing the system capacity and improving the usage of frequency resource. With the constant development of communication technology, the communication data transfer rate is becoming faster and faster. And the wireless channel condition is more and more complicated. The demand of limited spectrum resource is increasing. Smart antenna technology is a new solution to these issues. And it had become one of the hottest research fields of the fourth generation mobile communications system. As an important part of smart antenna techniques, Direction of arrival (DOA) estimation method attracted the attention of the industry.Through using the DOA estimation method, smart antenna can estimate the spatial information of users, and selectively receive or transmit multiple signals in the same channel. Therefore, the interference between the signals can be reduced, the capacity of the system can be increased and the quality of communication can be improved greatly. Classic MUSIC (Multiple Signal Classification) algorithm and ESPRIT (Estimating Signal Parameters via Rotational Invariance Techniques) algorithm are one-dimensional parameter (azimuth) signal DOA estimation methods, which have the common characteristic of lager amount of calculation. But the multi-dimensional parameters (azimuth, elevation angle, frequency and delay, etc.) signal DOA estimation methods have more applicable value than one-dimensional signal DOA estimation methods in the practical application. And two-dimensional parameters (azimuth, elevation angle) searching of DOA based on MUSIC algorithm have large amount of calculation. At the same time, one-dimensional DOA estimation methods based on linear array can be extended to the two-dimensional planar array or three-dimensional antenna array to achieve the estimation of multi-dimensional signal parameters. But the performance of algorithms has a great relationship with the structure of antenna array. And the electro-magnetic vector sensor array has a strong directional sensitivity and the amount of information about measuring. It can estimate the six-dimensional complex-vector signal and can improve the performance of scalar antenna array by making use of the polarization signal information. And now it is a research hotspot in the field of array signal processing.This paper mainly focuses on improving the classic DOA estimation algorithms and using MATLAB software to simulate these algorithms. The main work and achievements are:(1) The smart antenna technology is analyzed. And the concepts and principles of the electro-magnetic vector sensor array are described and compared with the traditional electro-magnetic scalar sensor array. The methods of DOA based on the electro-magnetic vector sensor array are studied emphatically.(2) The classic algorithms of smart antenna DOA estimation are described in details. And then MUSIC algorithm and ESPRIT algorithm are emphatically analyzed. By using the MATLAB software, the simulation platform is implemented. Then the classic MUSIC algorithm and ESPRIT algorithm are simulated respectively to verify the effectiveness of these algorithms. Some useful conclusions are obtained.(3) The genetic algorithm is studied. Then focusing on the niche method and a general process is discussed. The application of the algorithm in the estimation of spatial 2-D DOA is studied. The relationship between the different parameter settings and the algorithm performance is discussed and analyzed. And then the desired algorithm parameter settings are obtained.(4) An improved MUSIC algorithm is proposed to solve the estimation of 2-D DOA in this paper. One niche genetic algorithm is presented for MUSIC 2-D direction finding estimation method with electro-magnetic vector sensor arrays. The MUSIC algorithm combined with niche genetic algorithm makes full use of the characteristics of parallel search and intelligent convergence in genetic algorithm. Numerical simulations testified the validity of the niche genetic algorithm. Simulation results show that the RMS (Root Mean Square) bias performance of angle estimates obtained from MUSIC combined with niche genetic algorithm is worse than that from ESPRIT algorithm. But the RMS standard deviation performance of angle estimates obtained from MUSIC combined with niche genetic algorithm is better than that from ESPRIT algorithm.