Fusion of Inertial Sensors and Orthogonal Frequency Division Multiplexed Signals of Opportunity for Unassisted Navigation
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The advent of the global positioning system (GPS) has provided worldwide high-accuracy position measurements. However, GPS may be rendered unavailable by jamming, disruption of satellites, or simply by signal shadowing in urban environments. Thus, this thesis considers fusion of Inertial Navigation Systems (INS) and Orthogonal Frequency Division Multiplexed (OFDM) signals of opportunity (SOOP) for navigation. Typical signal of opportunity navigation involves the use of a reference receiver and uses time difference of arrival (TDOA) measurements. However, by exploiting the block structure of OF...
The advent of the global positioning system (GPS) has provided worldwide high-accuracy position measurements. However, GPS may be rendered unavailable by jamming, disruption of satellites, or simply by signal shadowing in urban environments. Thus, this thesis considers fusion of Inertial Navigation Systems (INS) and Orthogonal Frequency Division Multiplexed (OFDM) signals of opportunity (SOOP) for navigation. Typical signal of opportunity navigation involves the use of a reference receiver and uses time difference of arrival (TDOA) measurements. However, by exploiting the block structure of OFDM communication signals, the need for the reference receiver is reduced or possibly removed entirely. This research uses a Kalman Filter (KF) to optimally combine INS measurements with the OFDM TDOA measurements. A proof of concept in two dimensions is shown, and effects of the number of transmitters, sampling rate, multipath, and clock errors are investigated.
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