High Resolution Compressed Sensing Radar using Difference Set Codes
Abstract
In this paper, we consider compressive sensing (CS)-based recovery of delays and Doppler frequencies of targets in high resolution radars. We propose a novel sub-Nyquist sampling method in the Fourier domain based on difference sets (DS), called DS-sampling, to create dictionaries with highly incoherent atoms. The coherence of the dictionary reaches the Welch minimum bound if the DS-sampling is employed. This property let us to implement sub-Nyquist high resolution radars with minimum number of samples. We also develop a low complexity recovery method, based on structured CS and propose a new waveform, called difference set--frequency coded modulated (DS-FCM) waveform, to boost the recovery performance of the sub-Nyquist radar in noisy environments. The proposed method solves some of the common problems in many CS-based radars and overcome disadvantages of the conventional Nyquist processing, i.e. matched filtering in high resolution radar systems. The proposed method allows us to design sub-Nyquist radars, which require less than 2% of Nyquist samples and recover targets without resolution degradation in comparison to the conventional Nyquist processing.
Cite
@article{arxiv.1605.05379,
title = {High Resolution Compressed Sensing Radar using Difference Set Codes},
author = {Iman Taghavi and Mohamad F. Sabahi and Farzad Parvaresh and Mohsen Mivehchy},
journal= {arXiv preprint arXiv:1605.05379},
year = {2018}
}
Comments
There is no clear definition for the proposed modified DF. - There are some problems with the DS-FCM waveform, like PAPR issues which should be discussed. - The performance of recovery algorithms in noisy setting needs a mathematical proof