Test results for indoor positioning solution using MEMS sensor enabled GPS receiver

Abstract

There are a variety of mobile phone applications which require location with a high degree of availability and reliability. Location information derived from high-sensitivity GPS technology can fulfill this need for a substantially large percentage of time. There are several instances, such as indoor environments where GPS signals are degraded or not available. In such environments, MEMS inertial sensors can be used for location computation. Recent advancements in MEMS technology have enabled several manufacturers to bring to market low-cost, reliable MEMS accelerometers, gyroscopes, magnetic sensors and pressure sensors which can be used to produce a cost-effective GPS and MEMS integrated solution for the high volume consumer devices such as mobile handsets. The sensor noise characteristics such as bias stability, scale factor stability, and noise density for these sensors are now within a range where an effective integration with GPS is possible to generate position information with improved availability and with a significantly large reliability. We have developed a Pedestrian Dead Reckoning (PDR) based algorithms which uses MEMS inertial sensors to compute location in GPS denied environments. The information about the dynamic state of device (or user), also known as context (or situational) detection is utilized for selecting appropriate indoor position determination algorithms and associated motion parameters used by these algorithms. The state of the user can be one of the following modes: stationary, walking, jogging, fast walking, climbing up/down stairs, in elevator, on escalator, biking, or driving.