Research On DOA Estimation Algorithm For Sparse Array

With the rapid development of radar and smart antenna technology,higher requirements are put forward for high-precision target positioning technology.The sparse array is not restricted by the half-wavelength of the array element pitch,and it has the characteristics of high array aperture,large degree of freedom,and low mutual coupling effect between elements,which draws people's extensive attention in the industry.However,sparse arrays have serious ambiguity problems and are highly sensitive to amplitude and phase errors,which can easily lead to serious deviations in DOA estimation.Based on this problem,this paper has made relevant improvements to the DOA estimation algorithm under sparse arrays,as follows:1?A substrate-based DOA estimation algorithm for two-dimensional sparse arrays is proposed.Placing a substrate on the element of the sparse planar array and establishing a three-dimensional coordinate model.When the angle of the ambiguous signal is incident,the algorithm breaks the ambiguous array popularity by changing the equivalent position of the element to estimate the true arrival angle.Combining the suppression degree with media parameters(height,refractive index,etc.),by finding the optimal value of the suppression degree function within the constrained range,the substrate parameter value with the best suppression effect can be obtained.The results show that the maximum suppression of the ambiguous angle reaches 17 d B,and general ambiguity and complex ambiguity can be removed simultaneously.2?The two amplitude and phase error estimation algorithms in sparse array are improved.Firstly,the ISM amplitude and phase error estimation algorithm are combined with the substrate-based algorithm that can remove ambiguous angles in the two-dimensional sparse plane to remedy the defect that the assumptions of the ISM method are not satisfied in the sparse array;secondly,considering no auxiliary array elements,the iterative self-correction method is introduced into the amplitude and phase error estimation of the sparse array,and the joint decision of multiple sub-arrays is selected from the array to solve the problem of the iterative process converging to a false angle.Finally,the correct angle is obtained while estimating the amplitude and phase error,which improves the robustness of the algorithm.3?Sparse array DOA estimation algorithms based on compressed sensing is proposed.The substrate-deblurring algorithm and screening method based on the MUSIC algorithm framework are migrated to the OMP algorithm framework,and a dictionary that can accelerate the tracking process is designed from it,so that the efficiency of the wide-beam search process in the initial matching stage is 2 times as fast as that of the general hierarchical search method.The results show that in the case of single snapshot,the OMP algorithm with screening requires an SNR that is close to15 d B lower than MUSIC when the probability of success is 1,and the performance of the medium-based OMP algorithm is slightly improved compared to MUSIC.