@inproceedings{9b1781d2b32a4436b2b6dfd95bb62bab,
title = "Grid-refinement direction of arrival tracking via least square compressive sensing",
abstract = "In this paper, we propose a novel DOA tracking algorithm based on Least Square Compressive Sensing. The algorithm comes from the observation that a compressive sensing problem turns into a least square problem once the support is known. Utilizing the support from former time instant, compressive sensing recovery is performed on residual when least square residual is bigger than a threshold. In order to improve the resolution and decrease computation complexity, grid refinement is performed before least square. Under the assumption that the sparsity pattern of signal changes slowly, the grid refinement step is sufficient to track the DOA and the compressive sensing recovery step can be omitted in most of the time. Numerical results demonstrate that the proposed DOA tracking algorithm possess better performance and requires less computational complexity.",
keywords = "Compressive sensing, DOA tracking, Grid refinement, Least square",
author = "Yulong Gao and Deshun Hu and Yongkui Ma",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016 ; Conference date: 21-07-2016 Through 23-07-2016",
year = "2016",
month = dec,
day = "5",
doi = "10.1109/IMCCC.2016.13",
language = "英语",
series = "Proceedings - 2016 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "211--215",
editor = "Junbao Li",
booktitle = "Proceedings - 2016 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016",
address = "美国",
}