Single-Channel Compressive Sensing for DOA Estimation via Sensing Model Optimization - International Journal of Communications, Network and System Sciences

IJCNS > Vol.10 No.5, May 2017

Single-Channel Compressive Sensing for DOA Estimation via Sensing Model Optimization ()

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DOI: 10.4236/ijcns.2017.105B019 1,024 Downloads 2,034 Views

Author(s)

Hongtao Li, Zeshi Yuan

Affiliation(s)

Nanjing University of Science and Technology, Nanjing, China.

ABSTRACT

The performance of multi-channel Compressive Sensing (CS)-based Direction-of-Arrival (DOA) estimation algorithm degrades when the gains between Radio Frequency (RF) channels are inconsistent, and when target angle information mismatches with system sensing model. To solve these problems, a novel single-channel CS-based DOA estimation algorithm via sensing model optimization is proposed. Firstly, a DOA sparse sensing model using single-channel array considering the sensing model mismatch is established. Secondly, a new single-channel CS-based DOA estimation algorithm is presented. The basic idea behind the proposed algorithm is to iteratively solve two CS optimizations with respect to target angle information vector and sensing model quantization error vector, respectively. In addition, it avoids the loss of DOA estimation performance caused by the inconsistent gain between RF channels. Finally, simulation results are presented to verify the efficacy of the proposed algorithm.

KEYWORDS

Compressive Sensing, Direction-of-Arrival Estimation, Single-Channel, Mismatching Error

Share and Cite:

Li, H. and Yuan, Z. (2017) Single-Channel Compressive Sensing for DOA Estimation via Sensing Model Optimization. International Journal of Communications, Network and System Sciences, 10, 191-201. doi: 10.4236/ijcns.2017.105B019.

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