A Robust Direct Data Domain Least Squares Beamforming With Sparse Constraint

Abstract

Abstract-A robust direct data domain least squares (D 3 LS) beamforming algorithm that is capable of reducing the sidelobe level of the beam pattern is presented. By exploiting the sparsity of the desired beam pattern, the proposed method can enhance the performance with its lower sidelobe level and deeper null for interference while the robustness against steering vector mismatch is increased when a proper regularization parameter is selected. Simulation results demonstrate the effectiveness of the proposed method.

Hardware Implementation and RF High-Fidelity Modeling and Simulation of Compressive Sensing Based 2D Angle-of-Arrival Measurement System for 2–18 GHz Radar Electronic Support Measures

“…To estimate SOI AoA in a non-stationary environment, the Direct Data Domain (D3) method was introduced in [ 26 , 27 , 28 , 29 , 30 ], and it was applied to 2D AoA measurement for RESM application. Wu et al [ 31 ] introduced a D3-based 2D AoA estimator operating from 6 to 18 GHz and focused on measuring the low probability of intercept radar signals [ 1 , 32 ].…”

Robustness D3LS beamforming algorithm against the uncertainties in a uniform linear array radar of dipole antenna

“…In this approach, the data are analyzed from a single snapshot, and the interferences are canceled by determining the weights without having to estimate the covariance matrix. 5,6 To overcome these problems in statistical methods, non-statistical method of D 3 LS was presented by Sarkar et al 7 This method is well suited for real-time applications. Moreover, due to focusing only on a single data sample for processing, it has less computational volume and complexity than statistical methods.…”

“…Unlike the statistical approach, deterministic or adaptive algorithms can be performed in real time and were developed for the scenarios where the signal of interest is known as prior information. In this approach, the data are analyzed from a single snapshot, and the interferences are canceled by determining the weights without having to estimate the covariance matrix 5,6 . To overcome these problems in statistical methods, non‐statistical method of D 3 LS was presented by Sarkar et al 7 This method is well suited for real‐time applications.…”