Radar tools for spectrum assessment and prediction

Anthony F. Martone, Kelly D. Sherbondy, Kyle A. Gallagher, Jake A. Kovarskiy, Ram M. Narayanan

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

4 Scopus citations


In this paper we introduce an assessment and prediction technique for radar spectrum access in a dynamic electromagnetic environment. The proposed technique expands upon the existing spectrum sensing, multi-objective optimization (SSMO) framework for the joint optimization of the radar's signal to interference plus noise ratio (SINR) and range resolution. The proposed framework gathers training information in one spatial sector while the radar operates in another sector. The training information is used to form statistical estimates of the SINR and radio-frequency (RF) emitter activity. The predictive SSMO (pSSMO) technique then uses the training information during radar operation to avoid collisions with other RF emitters. Synthetic and measured Global System for Mobile (GSM) communication waveform data are processed by the proposed technique and the results indicate similar performance between the simulated and measured dataset, thereby validating the results.

Original languageEnglish (US)
Title of host publication2018 IEEE Radar Conference, RadarConf 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538641675
StatePublished - Jun 8 2018
Event2018 IEEE Radar Conference, RadarConf 2018 - Oklahoma City, United States
Duration: Apr 23 2018Apr 27 2018

Publication series

Name2018 IEEE Radar Conference, RadarConf 2018


Other2018 IEEE Radar Conference, RadarConf 2018
Country/TerritoryUnited States
CityOklahoma City

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Instrumentation


Dive into the research topics of 'Radar tools for spectrum assessment and prediction'. Together they form a unique fingerprint.

Cite this