PC104 Based Low-cost Inertial/GPS Integrated Navigation Platform: Design and Experiments

Di Li, René Jr. Landry, Philippe Lavoie

LACIME, Department of Electrical Engineering, école de Technologie Supérieure (éTS), University of Quebec, Montreal, Quebec, Canada, H3C 1K3.

DOI:                 

Abstract

The integration of Global Positioning System (GPS)/Inertial Navigation System (INS) has become very important in various navigation applications. In the last decade, with the rapid development of Micro Electro Mechanical Sensors (MEMS), great interest has been generated in low cost integrated GPS/INS applications. This paper presents a PC104 based low cost GPS/INS integrated navigation platform. The platform hardware consists of low cost inertial sensors and an assembly of various PC104 compatible peripherals, such as data acquisition card, GPS receiver, Ethernet card, mother board, graphic card, etc. The platform software including inertial/GPS data acquisition, inertial navigation calculation and integrated GPS/INS Kalman filter is implemented with Simulink, which can be directly loaded and processed in the PC104 mother board with the aid of Matlab Real-Time Workshop (RTW) utility. This platform is totally self-embedded and can be applied independently or as part of a system. Simulation and real data experiments have been performed to validate and evaluate the proposed design. A very low cost MEMS inertial sensor was utilized in the experiments. The reference is the navigation solution derived from a tactic grade Inertial Measurement Unit (IMU). Test results show that PC104 navigation platform delivers the integrated navigation solutions comparable to the reference solutions, which were calculated with a conventional laptop computer, however with less power consumptions, less system volume/complexity and much lower over-all costs. Moreover the platform hardware is compatible to various inertial sensors of different grades by configuring the related parameters in the system software.

Keywords

PC104, GPS, MEMS, Kalman filter, Realtime Workshop, xPC Target

Conflicts of Interest

The authors declare no conflicts of interest.

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