Joint estimation of DOA and channel errors with sparse recovery for SKA low-frequency array

Abstract

Here, the authors present an improved and fast sparse recovery method for joint estimation of channel errors and direction of arrival (DOA) for square kilometre antennas low-frequency array. Since this array is formed of a large number of antennas and distributed in a very large space, array calibration is a vital step to provide accurate signal information. Then, channel errors are the concerns here, which are assumed to be localised in a priori known interval. To achieve the joint estimation, an approach is proposed by using the alternative optimisation strategy, which theoretically gives convergence results. In detail, the basis pursuit de-noising (BPDN) algorithm and the proximal algorithm are used to estimate the DOA and the array errors, respectively, and the final results are obtained by alternatively solving these two algorithms. Finally, numerical simulation results are presented to demonstrate the effectiveness of their proposed method.

Keywords

• array signal processing
• antenna arrays
• calibration
• direction-of-arrival estimation
• optimisation
• convex programming
• radiotelescopes
• iterative methods
• doa
• array errors
• joint estimation
• channel errors
• improved recovery method
• fast sparse recovery method
• square kilometre antennas low-frequency array
• array calibration
• accurate signal information
• basis pursuit de-noising algorithm