Title :
An angle super-resolution approach of sparse acoustic vector array based on compressed sensing
Author :
Li Sun ; Hong Hong ; Chen Gu ; Yusheng Li ; Xiaohua Zhu
Author_Institution :
Sch. of Electron. & Opt. Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
In order to improve the Direction of Arrival (DOA) estimation performance of Acoustic Vector Sensor (AVS), an angle super-resolution approach based on Compressed Sensing (CS) is proposed. First, the CS theory is introduced into this field by exploiting the sparsity of target scene. Then, a joint sparse model along with Singular Value Decomposition (SVD) is utilized to accumulate signal power and reduce dimension. Finally, RMFOCUSS is utilized as a performance guaranteed recovery algorithms with available practicability for estimating targets angle. Compared with traditional methods, the proposed approach achieves better angle resolution in coping with both incoherent and coherent signals, also mitigates the high sidelobe problem caused by sparse array effectively.
Keywords :
acoustic signal processing; array signal processing; compressed sensing; direction-of-arrival estimation; signal resolution; singular value decomposition; AVS; CS theory; DOA; RMFOCUSS; SVD; angle superresolution approach; compressed sensing; dimension reduction; direction-of-arrival estimation performance improvement; high sidelobe mitigation problem; joint sparse model; signal power accumulation; singular value decomposition; sparse acoustic vector array; Acoustics; Arrays; Direction-of-arrival estimation; Estimation; Multiple signal classification; Signal resolution; Vectors; Acoustic Vector Sensor (AVS); Compressed Sensing (CS); Direction of Arrival (DOA); Sparse array;
Conference_Titel :
Digital Signal Processing (DSP), 2014 19th International Conference on
Conference_Location :
Hong Kong
DOI :
10.1109/ICDSP.2014.6900709