Extended Range Profiling in Stepped-Frequency Radar with Sparse Recovery
Information Theory
2010-11-19 v3 math.IT
Abstract
The newly emerging theory of compressed sensing (CS) enables restoring a sparse signal from inadequate number of linear projections. Based on compressed sensing theory, a new algorithm of high-resolution range profiling for stepped-frequency (SF) radar suffering from missing pulses is proposed. The new algorithm recovers target range profile over multiple coarse-range-bins, providing a wide range profiling capability. MATLAB simulation results are presented to verify the proposed method. Furthermore, we use collected data from real SF radar to generate extended target high-resolution range (HRR) profile. Results are compared with `stretch' based least square method to prove its applicability.
Cite
@article{arxiv.1009.4969,
title = {Extended Range Profiling in Stepped-Frequency Radar with Sparse Recovery},
author = {Yang Hu and Yimin Liu and Huadong Meng and Xiqin Wang},
journal= {arXiv preprint arXiv:1009.4969},
year = {2010}
}
Comments
3 pages, 3 figures