# A New Atomic Norm for DOA Estimation With Gain-Phase Errors

arXiv: https://arxiv.org/abs/1910.02207 · HTML: https://mlsanity.com/paper/1910.02207/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Oct 2019.

## Built on by (most cited first, 2 of 2)

- [Multi-Antenna Dual-Blind Deconvolution for Joint Radar-Communications via SoMAN Minimization](https://mlsanity.com/paper/2303.13609/) (2023)
- [DOA Estimation from One-Bit Magnitude-Only Measurements via Sign-Consistency Optimization](https://mlsanity.com/paper/2607.12491/) (2026)

## Abstract (arXiv)

The problem of direction of arrival (DOA) estimation has been studied for decades as an essential technology in enabling radar, wireless communications, and array signal processing related applications. In this paper, the DOA estimation problem in the scenario with gain-phase errors is considered, and a sparse model is formulated by exploiting the signal sparsity in the spatial domain. By proposing a new atomic norm, named as GP-ANM, an optimization method is formulated via deriving a dual norm of GP-ANM. Then, the corresponding semidefinite program (SDP) is given to estimate the DOA efficiently, where the SDP is obtained based on the Schur complement. Moreover, a regularization parameter is obtained theoretically in the convex optimization problem. Simulation results show that the proposed method outperforms the existing methods, including the subspace-based and sparse-based methods in the scenario with gain-phase errors.