与均匀阵列相比,稀疏阵列可以使天线阵列成本降低,减少数据处理,同时带来更大的阵列孔径提高信号解析能力,在信号处理中有着广泛的应用.但是由于其排布的不规则性,计算量较大,二维面阵合成协方差矩阵存在空洞,对角度估计的准确性造成负面影响,增强了系统对噪声的敏感度.为了克服这些问题,本文提出了一种新的角度估计方法,采用截断核范数以降低噪声的影响,并通过ℓp范数优化提升信号的稀疏表示,利用交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)算法构造子问题恢复出完整的阵列信号.随后采用子阵划分技术和基于最小二乘的传播算子模型(Propagator Method,PM)对恢复的信号处理,精确估计信号源的方位和俯仰角.仿真结果表明,所提出的角度估计算法在角度精度和时间复杂度方面具有优越性.
An Sparse Planar Array DOA Estimation Algorithm Based on Truncated Nuclear Norm and Propagator Method
Compared with uniform arrays,sparse arrays can reduce the cost of antenna arrays,decrease data pro-cessing,and provide a larger array aperture to improve the signal analysis capability,resulting in widespread applica-tions in signal processing.However,due to the irregularity of their arrangement,sparse arrays involve significant compu-tational complexity.There are gaps in the synthesis of the covariance matrix for two-dimensional array,which has a nega-tive impact on the accuracy of direction-of-arrival(DOA)estimation and increase the system's sensitivity to noise.To overcome these problems,a novel angle estimation method is proposed in this paper.This method adopts truncated nuclear norm to mitigate the influence of noise,and further improves the sparse representation of signals by norm optimi-zation.The complete array signal is subsequently recovered by using the alternating direction method of multipliers(ADMM)algorithm to construct the sub-problems.Additionally,this method employs the subarray partitioning tech-nique and the propagator method(PM)based on the least squares for signal recovery processing,enabling accurate esti-mation of the azimuth and elevation angles of signal sources.The simulation results demonstrate the superiority of the proposed DOA estimation algorithm in terms of angle accuracy and time complexity.
ℓp-normtruncated nuclear normsubarray partitionmatrix completiontwo-dimensional DOA estimation
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