@inproceedings{1402356bb9e8407c839966d029b0a97b,
title = "A compound Gaussian-based waveform design approach for enhanced target detection in multistatic radar imaging",
abstract = "Much work has been done designing transmit waveforms for target identification, classification, and detection. In addition, these have also been studied in both single and multiple-antenna scenarios. In this work, we study the construction of a waveform when multiple radar sensors are used to image a target scene. The scene is assumed to have a prior distribution given by a Compound Gaussian (CG) - a model that has proven very useful in the field of image processing. Waveform optimization is done with the objective of optimizing mutual information, while reconstruction was performed using sparsity based reconstruction techniques. In our work, the waveform is tailored for a particular target of interest in the scene while suppressing the clutter. Using our waveform techniques, we demonstrate statistically significant improvements in the quality of the reconstructed image in peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM). We validate our algorithms using the MSTAR database.",
author = "Zacharie Idriss and Raj, {Raghu G.} and Narayanan, {Ram M.}",
note = "Funding Information: by the US Office of Naval Research Grant Publisher Copyright: {\textcopyright} 2109 SPIE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; Radar Sensor Technology XXIII 2019 ; Conference date: 15-04-2019 Through 17-04-2019",
year = "2019",
doi = "10.1117/12.2522428",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Ranney, {Kenneth I.} and Armin Doerry",
booktitle = "Radar Sensor Technology XXIII",
address = "United States",
}