We have proposed a novel method for Synthetic High Range Resolution (HRR) profiling, under the condition of missing frequency domain samples. This new approach estimates the autocovariance function (ACF) of the signal by valid sample pairs. Autocovariance matrix is formed from ACF estimations. Even with large part of data missing, new approach exhibits robust profiling result. Simulations are presented to show a advantage over other approaches in missing data case. Moreover, a real radar experiment was conducted to validate the new approach.
@article{arxiv.1410.7276,
title = {High Range Resolution Profiling in Missing Data Case: A New Approach},
author = {Yang Hu and Huadong Meng and Yimin Liu and Xiqin Wang},
journal= {arXiv preprint arXiv:1410.7276},
year = {2014}
}