A Computational Electromagnetics Framework for a Matched Illumination Approach to Waveform Optimization

Zacharie Idriss, Raghu G. Raj, Ram M. Narayanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, a waveform is tailored to increase target information at the receiver by removing the effects of clutter such as signal-dependent ground bounce in downward looking ground penetrating radar (GPR). The scene is modeled from an electromagnetic perspective where the scattering equations are discretized and solved using the Method of Moments (MoM). In order to apply the waveform optimization to better detect buried scatterers in the presence of ground bounce, the electromagnetic scattering equations are solved for a variety of simple geometric shapes at various pose angles in a specified soil environment. The ground is modeled as being a correlated random Gaussian surface, therefore Monte Carlo runs are carried out to get an average surface roughness for the waveform optimization. The results show that a waveform optimized to match a target energy distribution removes the ground bounce to better image a buried scatterer.

Original languageEnglish (US)
Title of host publicationRadarConf23 - 2023 IEEE Radar Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665436694
StatePublished - 2023
Event2023 IEEE Radar Conference, RadarConf23 - San Antonia, United States
Duration: May 1 2023May 5 2023

Publication series

NameProceedings of the IEEE Radar Conference
ISSN (Print)1097-5764
ISSN (Electronic)2375-5318


Conference2023 IEEE Radar Conference, RadarConf23
Country/TerritoryUnited States
CitySan Antonia

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Instrumentation

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