Integration of Heading-Aided MEMS IMU with GPS for Pedestrian Navigation

James Pinchin, Chris Hide, Khari Abdulrahim, Terry Moore, and Chris Hill

Abstract:	This paper describes the loose integration of GPS positions with a foot-mounted inertial navigation system (INS). Pedestrian navigation using foot mounted inertial measurement units (IMUs) has been the subject of intensive research in recent years. By mounting the IMU on a person's foot the positioning algorithm can make use of frequent zero-velocity updates (ZUPTs). Such a technique makes it possible to use poor quality, mass market MEMs IMUs for accurate pedestrian navigation. Foot mounted INS still suffer from position drift over time and require the initialisation of position and heading from independent sensors. In previous papers the authors have described a method for reducing position drift through the use of ‘building heading aiding’ which makes simple assumptions about the restrictions on a pedestrians movement when inside a building. In this work we describe the use of two forms of GPS position estimates in the navigation algorithm. Use of these positions when they are available both reduces position drift and allows initialisation of the systems position. When the pedestrian is moving, position aiding will also aid the estimation of heading and z-axis gyro bias. For comparison two forms of GPS position are used. Real Time Kinematic (RTK) carrier phase position is used to provide highly precise position estimates at the expense of solution availability and affordability. It is anticipated that the integrated RTKGPS / INS approach will provide a high accuracy reference trajectory, against which other approaches may be compared. We describe the use of high precision position estimates in a pedestrian INS, accounting for the varying GPS antenna to IMU leverarm. Secondly we integrate position solutions from a high sensitivity GPS receiver (HSGPS). These receivers are mass market products already available in many mobile computing devices. They provide position solutions in most environments, even indoors and in urban canyons. However the positions provided are of low precision and suffer from biases caused by signal blockage, attenuation and reflection. Through a test walk encompassing many environments, from open sky to indoors, we show that the HSGPS based approach can give a trajectory which closely matches that obtained using the RTKGPS approach, despite a system cost difference greater than $US20k. Over a walk 25 minutes long the mean position difference between the two approaches was 4.14m, with a maximum of 12m during initialisation. We find that the high solution availability from the HSGPS receiver combined with an appropriate weighting model compensates for the lack of precision when compared to the RTKGPS method. Finally the paper discusses possible approaches for the integration of GPS with a pedestrian INS in the future.
Published in:	Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011) September 20 - 23, 2011 Oregon Convention Center, Portland, Oregon Portland, OR
Pages:	1346 - 1356
Cite this article:	Pinchin, James, Hide, Chris, Abdulrahim, Khari, Moore, Terry, Hill, Chris, "Integration of Heading-Aided MEMS IMU with GPS for Pedestrian Navigation," Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011), Portland, OR, September 2011, pp. 1346-1356.
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