TY - GEN
T1 - Empirical mode decomposition and blind source separation methods for antijamming with GPS signals
AU - Kamath, Vinayak
AU - Lai, Ying-Cheng
AU - Zhu, Liqiang
AU - Urval, Suprada
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
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U2 - 10.1109/PLANS.2006.1650620
DO - 10.1109/PLANS.2006.1650620
M3 - Conference contribution
SN - 0780394542
SN - 9780780394544
T3 - Record - IEEE PLANS, Position Location and Navigation Symposium
SP - 335
EP - 341
BT - 2006 IEEE/ION Position, Location, and Navigation Symposium
T2 - 2006 IEEE/ION Position, Location, and Navigation Symposium
Y2 - 25 April 2006 through 27 April 2006
ER -