@inproceedings{5d9e911850a848f38668aec8f956256f,
title = "M-Estimator Based Robust Coarray Interpolation for DOA Estimation with Miscalibrated Sensors",
abstract = "This paper proposes a robust signal interpolation approach for direction-of-arrival (DOA) estimation when several sensors in a coprime array are not properly calibrated. In such case, the conventional interpolation approaches will lead to an inaccurate or even failed DOA estimation. In our proposed approach, observations obtained from the sensors without calibration are blindly treated as outliers. The interpolation problem is formulated as an atomic norm minimization (ANM) problem, where the M-estimator is employed as the regularization term to reduce the adverse impact of outliers. The DOA estimation results can be thus robustly obtained by applying the interpolated virtual signal matrix. Numerical experiments verify that our interpolation algorithm outperformance existing array interpolation methods in terms of robustness.",
keywords = "Atomic norm minimization (ANM), Calibration error, Coprime array, Mestimator, Robust DOA estimation, Virtual array interpolation",
author = "Jiaxun Kou and Chunlan Jiang and Ming Li",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 3rd International Conference on Unmanned Systems, ICUS 2020 ; Conference date: 27-11-2020 Through 28-11-2020",
year = "2020",
month = nov,
day = "27",
doi = "10.1109/ICUS50048.2020.9274909",
language = "English",
series = "Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "130--134",
booktitle = "Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020",
address = "United States",
}