@inproceedings{pierce_centralized_2015,
	title = {A {Centralized} {Approach} to {Pedestrian} {Localization} {Using} {Multiple} {Odometry} {Sources}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=12607},
	abstract = {A method is presented for pedestrian localization by use of stereo visual odometry and a foot-mounted inertial navigation system (INS). As opposed to prior approaches for fusing such systems, a centralized model combines the state vector for both visual odometry and INS mechanization using an Extended Kalman Filter (EKF) framework. Correlations are maintained in the centralized filter by pseudo-measurements relating the position and heading of the two systems. Gait monitoring is performed in order to detect vertical leg conditions in which the two systems can be related by a baseline separation. In addition, zero velocity updates are applied to foot velocity states to estimate INS errors. External measurements are applied through a standard EKF update, and their effect on filter performance is shown. Results are presented using both simulated and real data.},
	language = {en},
	urldate = {2024-06-20},
	author = {Pierce, J. Daniel and Bevly, David M.},
	month = jan,
	year = {2015},
	pages = {123--128},
}

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