@inproceedings{380cfd145c4c45ed90241ecf8d1feeb8,
title = "Adaptive matching pursuit method based on auxiliary residual for sparse signal recovery",
abstract = "Greedy pursuit methods are widely used for compressive sensing (CS) and sparse signal recovery due to their low computational complexity. In this paper an adaptive matching pursuit is proposed, which is based on the backtracking-based adaptive orthogonal matching pursuit (BAOMP) and uses auxiliary residual to make correlation test to add more correct atoms per iteration. The proposed method can be regarded as an improved BAOMP. The simulation results show that it has better performance to those of some other greedy pursuit methods. Finally the experiment of CS-based ISAR imaging verifies the effectiveness of the proposed method.",
author = "Juan Zhao and Xia Bai",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 ; Conference date: 18-11-2019 Through 21-11-2019",
year = "2019",
month = nov,
doi = "10.1109/APSIPAASC47483.2019.9023284",
language = "English",
series = "2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "774--778",
booktitle = "2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019",
address = "United States",
}