Empirical Mode Decomposition and Blind Source Separation Methods for Antijamming with GPS Signals

Vinayak Kamath, Ying-Cheng Lai, Liqiang Zhu and Suprada Urval

Abstract:	The spread-spectrum structure of GPS signals provides inherent jamming tolerance for GPS receivers. In a hostile environment where jamming sites may be close to GPS users, a larger JSR is possible. How to achieve the desired accuracy for GPS-based systems in the presence of strong jamming is an important but outstanding problem. Here we propose to use the empirical-mode decomposition (EMD) method, originally developed for analyzing nonlinear and nonstationary signals, for antijamming. Given a jammed, noisy GPS signal, the EMD method identifies the innate undulations belonging to different time scales and sifts them out to yield a small number of intrinsic modes. We find that the EMD method typically works well when the jamming is stationary in that the GPS signal and jamming components are typically contained in different intrinsic modes. However, when the jamming is nonstationary, the GPS signal and jamming are spread over all the intrinsic modes. Our solution is to use the blind-source separation (BSS) method operating on the set of intrinsic modes from EMD. Simulations indicated that this combined EMD/BSS methodology works reasonably well for extracting the GPS signal in the presence of nonstationary jamming for JSR up 45dB.
Published in:	Proceedings of IEEE/ION PLANS 2006 April 25 - 27, 2006 Loews Coronado Resort Hotel San Diego, CA
Pages:	335 - 341
Cite this article:	Kamath, Vinayak, Lai, Ying-Cheng, Zhu, Liqiang, Urval, Suprada, "Empirical Mode Decomposition and Blind Source Separation Methods for Antijamming with GPS Signals," Proceedings of IEEE/ION PLANS 2006, San Diego, CA, April 2006, pp. 335-341. https://doi.org/10.1109/PLANS.2006.1650620
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