Research On Mutual Coupling Calibration And High Precision Angle Parameter Estimation Method Of Compact Array

Direction of arrival(DOA)estimation is a significant research branch in array signal processing,which aims to determine the direction of signal source by utilizing the signals received by antenna array.DOA estimation has been a research hotspot in this field due to its broad potential applications in radar detection,electronic countermeasures,and other fields.In recent years,massive MIMO technology has gained significant attention in wireless communication systems.To reduce the system size,the inter-element spacing in the array is typically smaller than the conventional half-wavelength,resulting in a dense array configuration.This configuration is commonly referred to as a compact array.For compact arrays,the mutual coupling effect in the array is not negligible in practical application,which will significantly degrade the performance of ideal DOA estimation algorithm.This thesis centers on the study of mutual coupling correction methods and robust DOA estimation method of compact array under mutual coupling conditions.The specific work is as follows.An improved iterative DOA estimation algorithm is proposed to solve the direction finding problem of compact array in the case of mutual coupling.Based on the inherent structure of mutual coupling coefficient matrix of compact array,this algorithm separates a new direction matrix that is not affected by mutual coupling by transforming the product of the mutual coupling matrix and the signal steering vector,so as to preliminatively realize the estimation of DOA.Subsequently,based on the matrix’s eigendecomposition,the coupling coefficient is estimated and compensated into the spatial spectrum function to achieve higher precision DOA estimation.Finally,the above steps are iterated to continuously optimize the estimation results until the termination condition is met.The simulation results demonstrate the effectiveness of the proposed algorithm in achieving accurate estimation of both the angles and mutual coupling parameters.Compared to existing algorithms,this algorithm exhibits higher estimation accuracy,particularly under strong mutual coupling conditions where it significantly improves the estimation performance.A dimensionality reduction sparse off-grid angle estimation algorithm is proposed,so as to address the challenges associated with direction finding in bistatic MIMO radar based on compact array in the context of mutual coupling.Leveraging the principles of compressed sensing theory,the algorithm converts the two-dimensional angle estimation problem into two independent one-dimensional angle estimation problems by the transformation of signal model,and realizes the effective sparse representation of bistatic MIMO radar.The off-grid vector solved by gradient descent method is compensated into the signal model to solve the grid mismatch problem.The simulation results demonstrate that the proposed algorithm can effectively realize the DOD and DOA estimation of multiple targets and complete the correct pairing.In comparison with the existing methods,the proposed algorithm exhibits obvious accuracy advantages,and can significantly improve the degradation of angle estimation accuracy caused by severe conditions such as strong mutual coupling,low signal-to-noise ratio and small number of pulses.