2D High-precision Direction Of Arrival Estimation Based On Uniform Rectangular Array

In the field of array signal processing,Direction of Arrival(DOA)estimation is an important research direction.At present,the DOA estimation algorithm is mostly for onedimensional space domain,but the study of two-dimensional DOA estimation is obviously more practical,although the one-dimensional DOA algorithm can be extended directly to the two-dimensional DOA estimation,but it will also bring about computational complexity and practical reduction and so on.In this paper,the following research work is carried out in view of the shortcomings in the application of DOA estimation algorithm to 2D DOA estimation:Using uniform rectangular array to estimate the arrival angle of signal in twodimension,the traditional DOA estimation algorithms,such as Bartlett algorithm,Capon algorithm and MUSIC algorithm,are studied,and the simulation and comparison show that these algorithms have poor performance when the signal noise is low or the number of snapshots is low.We also studied DOA estimation based on compressive sensing,such as SVD algorithm,FOCUSS algorithm,OMP algorithm and BCS algorithm.The simulation results show that these algorithms can get good estimation results without many snapshots.In this paper,for the problem of highly computational complexity when we directly apply the compressive sensing class algorithm to two-dimensional DOA estimation,we reduce the dimensional by using the separable array manifold technique.We proposed the multi-snapshot processing method by using the space-time equivalence of the uniform linear subarray in the uniform rectangular array when receiving signal.Through theoretical analysis and simulation,it is shown that the dimensional reducing method significantly reduces the computational complexity of these algorithms.And simulation also verifies the effectiveness of the multi-snapshot processing method.In addition,in this paper,in view of the grid mismatch of compressive sensing DOA algorithm,we introduces the off-grid approximation model based on first-order Taylor expansion.Combined with the separable array manifold technique,we studied the twodimensional off-grid DOA estimation algorithm.For the off-grid coupling problem in the algorithm,and the problem that the algorithm gives Gaussian prior distribution to grid deviation value which is not realistic,we proposed an improved two-dimensional off-grid DOA estimation model and we set the uniform prior distribution for grid deviation.The simulation experiment shows that the two-dimensional off-grid DOA estimation algorithm proposed in this paper effectively solves the problem of off-grid coupling and improves the estimation accuracy.