Abstract:
Compressed Sensing (CS) has provided a viable approach to undersample a sparse signal and reconstruct it perfectly. In this paper, the simulation results of a frequency-m...Show MoreMetadata
Abstract:
Compressed Sensing (CS) has provided a viable approach to undersample a sparse signal and reconstruct it perfectly. In this paper, the simulation results of a frequency-modulated continuous-wave (FMCW) radar, which employs a CS based data acquisition and reconstruction algorithm to recover a sparse 2-D target frame using fewer number of scans are presented. A 16-element antenna array based on digital beamforming approach is used on the receiver end to obtain random spatial measurements of the target frame, which is the key to compressed sensing. A linear relationship is established between the total received FMCW beat signal for each scan and the 2-D sparse target frame using a basis transform matrix. Simulations of the proposed radar are performed in MATLAB and the reconstruction results for different noise levels are presented.
Date of Conference: 26-29 January 2020
Date Added to IEEE Xplore: 19 March 2020
ISBN Information: