Research On Algorithms Of Array Signal Processing In Smart Antenna

For the disadvantages of low accuracy and rapid decrease of algorithms’performance in the situation of low Signal Noise Radio (SNR) incoming signals for the key technologies in smart antenna, which are called estimation of direction of arrival (DOA) and estimation of source association(which path belonging to which emission source under multipath propagation), we have done some rewarding researches, in general, the issues of estimation of DOA in coherent signal based on uniform circular array (UCA) and estimation of source association based on cyclostationary signal have been researched in this paper and the primary work is described as follows:1、A new algorithm aiming at improving the estimation accuracy of direction of arrival (DOA) based on uniform circular array (UCA) has been proposed in this paper. Firstly, shifting the mathematical mode of array received signals at the z axis and x axis respectively, then, two new full rank Toeplitz matrices relating the information of DOA estimation have been reconstructed, so the purpose of decorrelation has been achieved. Through the different property of rotation factor at z axis and x axis successively, we obtain the estimation of pitch angle firstly, and then the estimation of azimuth angle. Result analysis of simulation showed the validity of the DOA estimation of coherent signal, as well as the strong coherent and low SNR incoming signals.2、As the DOAs of multipath signal have been known, we develop a new method to solve the issue of which path belonging to which emission source under multipath propagation, i.e., estimation of source association. To improve the performance of source association estimation which is related closely to the time difference of arrival (TDOA), we propose a new TDOA estimation algorithm with a weighted linear combination of cyclic correlation functions based on multi-cycle frequencies. The proposed TDOA estimation algorithm can overcome the disadvantage of low accuracy in conventional single-cycle algorithms for utilizing the useful information from other cycle frequencies. Several simulations have been performed to analyze the performance of this algorithm, and the results verify the effectiveness of the new method.3、As the DOAs of multipath signal have been known, aiming at solving the contradiction between convergence rate and steady state error in least mean square (LMS) algorithm, a new variable step size LMS adaptive filtering algorithm based on modified secant integral function has been proposed. It utilizes the error correlative value to adjust the parameters of adaptive filter and makes the algorithm have a great step size in initial stage to guarantee a rapid convergence speed and a small step size when the error signal closed to zero to guarantee a tiny maladjustment, so the new algorithm can get a good balance between convergence speed and steady-state error. Throughout the theoretical analysis and MATLAB simulation, the results show that the new improved variable step size algorithm has a better performance in convergence rate, steady state error and anti-jamming capability compared to other algorithms, especially in the case of eliminating noise fluctuation.