Research On Joint Parameters Estimation And Interference Suppression In Both Polarization And Space Domains

Comparing with the traditional scalar array, the advantage of the polarization sensitive array is that it could make use of the polarization information of the signals, and furthermore it could improve the estimation precision and interference suppression performance. However, most of the processing methods for polarization array are direct expansions of the methods for scalar sensor array instead of intensively researching on special structure of the polarization array, and a massive work is focused on improving the performance of the method for the polarization vector array signal processing. To solve this problem, joint parameters estimation and beamforming methods are to be studied. Based on quaternion model, new methods of parameters estimation and interference suppression with high efficiency and low complexity are proposed and simulated by using the orthogonal structure among the polarization elements.Aimed at the problem of parameters estimation for coherent signals, quaternion spatial smoothing algorithm and quaternion Toeplitz matrix reconstruction algorithm are proposed based on quaternion model. On this basis, the improved quaternion spatial smoothing algorithm and the improved vector matrix reconstruction algorithm are studied, and the decorrelation principles of these two algorithms are deduced respectively. The simulation results show that the improved algorithms possess better parameters estimation performance as well as better spatial resolution. Vector matrix reconstruction algorithm does not lose the effective aperture of the array. Therefore, compared with the spatial smoothing algorithm, it could estimate more parameters of the coherent signals.Aimed at the problem of parameters estimation for non-coherent signals, the dimensions of array signal processing are transformed to both polarization and spatial domains due to the introduction of polarization information, which results in increased computation and complexity. To solve this problem, the reduced dimensional MUSIC algorithm is proposed. By making full use of polarization information and spatial information,the polarization information is able to be separated from the spatial information, then MUSIC algorithm is used to estimate the spatial arrival angles and polarization parameters respectively, which reduces the computational complexity to a certain extent. On this basis, a reduced-dimensional Root-MUSIC algorithm with modulus constraint is proposed. Firstly, the Root-MUSIC algorithm is used to calculate the spatial arrival angles. Then the optimization function is established according to the modulus constraint, and the polarization parameters are obtained by closed form solution. The algorithm is applied to polarization uniform linear array and L-shaped array. The comparison analysis and simulation results are used to verify the superior performance of the proposed algorithms.For the beamforming in joint polarization and space domain, the principle and performance of the combined filter are introduced, and the maximum output signal to noise ratio is given. Based on the theory of eigen-subspace, the quaternion projection beamforming algorithm is studied. The models of amplitude and phase errors, coupling error and position error are introduced. The filtering performance of the algorithm is analyzed in the case of ideal conditions and the error conditions. The filtering performances of quaternion projection beamforming algorithm and quaternion MVDR algorithm are compared, and simulation results show that the quaternion projection beamforming algorithm is better than the quaternion MVDR algorithm. Hence the former algorithm could reduce the impact of errors to some extent.