Underwater Acoustic Matched Field Imaging Based on Compressed Sensing

Sensors

Huichen Yan¹  Jia Xu²  Teng Long²  Xudong Zhang¹ 

[1] Department of Electronic Engineering, Tsinghua University, Beijing 100084, China; E-Mails:;School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China; E-Mail:

关键词: matched field processing (MFP);    compressed sensing (CS);    wave propagation;    coherence parameter;    coherence-excluding coherence optimized orthogonal matching pursuit (CCOOMP);   

DOI  :  10.3390/s151025577

来源: mdpi

【 摘 要 】

Matched field processing (MFP) is an effective method for underwater target imaging and localizing, but its performance is not guaranteed due to the nonuniqueness and instability problems caused by the underdetermined essence of MFP. By exploiting the sparsity of the targets in an imaging area, this paper proposes a compressive sensing MFP (CS-MFP) model from wave propagation theory by using randomly deployed sensors. In addition, the model’s recovery performance is investigated by exploring the lower bounds of the coherence parameter of the CS dictionary. Furthermore, this paper analyzes the robustness of CS-MFP with respect to the displacement of the sensors. Subsequently, a coherence-excluding coherence optimized orthogonal matching pursuit (CCOOMP) algorithm is proposed to overcome the high coherent dictionary problem in special cases. Finally, some numerical experiments are provided to demonstrate the effectiveness of the proposed CS-MFP method.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.