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Caglar Yardim

  • Research Scientist, Electroscience Lab
  • Room #173
    1330 Kinnear Rd
    Columbus, OH 43212
  • 614-292-4913


Caglar Yardim received his PhD in Electrical Engineering from University of California, San Diego (UCSD) in 2007. He worked as a Postdoctoral Scholar and Project Scientist at the Marine Physical Laboratory of Scripps Institution of Oceanography from 2007-2014. He has been with ESL as a Research Scientist since June 2014.


Research Interests:

Dr. Yardim has two main areas of specialization: Remote sensing and applied signal processing. 

His main interest is atmospheric propagation of electromagnetic signals under non-standard atmospheric conditions and remote sensing of atmospheric refractivity. His efforts in this field are threefold: First, developing better propagation codes (parabolic equation) and accurate clutter modeling. Second is developing inversion techniques that infer the time and space-varying anomalous atmospheric conditions from radar clutter measurements, a technique known as refractivity from clutter (RFC) and from sources-of-opportunity using passive remote-sensing measurements. Third is the assimilation of the environmental information obtained from electromagnetic data with climatology databases, and numerical weather prediction codes to simultaneously improve radar/communication system performance and numerical weather prediction codes by assimilating new types of data. 

He works on microwave radiometry, remote sensing of ice-sheets in Greenland and Antarctica, and bistatic radar cross section calculations at low grazing angles.

Another area he focuses on is applied signal processing, particularly Bayesian sequential methods such as Kalman and particle filters, Monte Carlo samplers, optimization, statistical parameter estimation, adaptive beamforming, passive interferometry, data assimilation, and compressive sensing. 

He also works with acoustic signals for underwater acoustic remote sensing of oceans and sub-bottom/sediment layers and seismic signals for tracking non-volcanic tremors source locations.