Radar Localization with multiple Unmanned Aerial Vehicles using Support Vector Regression

  • Authors:

  • B. Sundaram;M. Palaniswami;S. Reddy;M. Sinickas

  • Affiliations:

  • Dept. of EEE, The University of Melbourne. bhar@ee.mu.oz.au;-;-;-

  • Venue:
  • ICISIP '05 Proceedings of the 2005 3rd International Conference on Intelligent Sensing and Information Processing
  • Year:
  • 2005

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Abstract

This paper presents a first attempt to solve the Geolocation problem using Support Vector Regression (SVR). This paper proposes a method to pinpoint the location of stationary, hostile radar using the Time Difference of Arrival (TDoA) of the same characteristic pulse emitted by the radar at 3 different Unmanned Aerial Vehicles (UAVs) flying in a fixed triangular formation. The performance of the proposed SVR method is compared with a variation of the Taylor Series Method (TSM) used for solving the same problem and currently deployed by the DSTO, Australia on the Aerosonde Mark III UAVs. The robustness to error of the SVR method is explored and compared with the TSM. Extended applications of the SVR approach to more general localization scenarios in Wireless Sensor Networks are proposed for further work.