Sparse source location for real aperture radar using generalized sparse covariance fitting

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding


Source location for real aperture radar (RAR) has raised many concerns in the fields of ground-based monitoring for aircrafts and vessels. Notably, the resolution of RAR in azimuth is constrained by the antenna beam width, which results in low degree of location accuracy. In this paper, we exploit the inherent sparseness of the target distributions to formulate a superresolution methodology to locate the observed sources. Making use of a recently developed generalized sparse covariance fitting technique, we show that the resulting estimator enjoys improved resolution and higher location accuracy as compared with the RAR system and other recent superresolution algorithms.


External organisations
  • University of Electronic Science and Technology of China
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Electrical Engineering, Electronic Engineering, Information Engineering
Original languageEnglish
Title of host publication2017 IEEE Radar Conference, RadarConf 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781467388238
Publication statusPublished - 2017 Jun 7
Publication categoryResearch
Event2017 IEEE Radar Conference, RadarConf 2017 - Seattle, United States
Duration: 2017 May 82017 May 12


Conference2017 IEEE Radar Conference, RadarConf 2017
CountryUnited States