FPGA-Based Real-Time Embedded System for RISS/GPS Integrated Navigation

Sensors

Walid Farid Abdelfatah¹  Jacques Georgy¹  Umar Iqbal² 

[1] Trusted Positioning Inc., Calgary, AB T2L 2K7, Canada; E-Mail:;Electrical and Computer Engineering Department, Queen’s University, Kingston, ON K7L 3N6, Canada; E-Mails:

关键词: embedded systems;    FPGA;    soft-core;    land vehicle navigation;    Global Positioning System;    inertial sensors;    Kalman filter;   

DOI  :  10.3390/s120100115

来源: mdpi

【 摘 要 】

Navigation algorithms integrating measurements from multi-sensor systems overcome the problems that arise from using GPS navigation systems in standalone mode. Algorithms which integrate the data from 2D low-cost reduced inertial sensor system (RISS), consisting of a gyroscope and an odometer or wheel encoders, along with a GPS receiver via a Kalman filter has proved to be worthy in providing a consistent and more reliable navigation solution compared to standalone GPS receivers. It has been also shown to be beneficial, especially in GPS-denied environments such as urban canyons and tunnels. The main objective of this paper is to narrow the idea-to-implementation gap that follows the algorithm development by realizing a low-cost real-time embedded navigation system capable of computing the data-fused positioning solution. The role of the developed system is to synchronize the measurements from the three sensors, relative to the pulse per second signal generated from the GPS, after which the navigation algorithm is applied to the synchronized measurements to compute the navigation solution in real-time. Employing a customizable soft-core processor on an FPGA in the kernel of the navigation system, provided the flexibility for communicating with the various sensors and the computation capability required by the Kalman filter integration algorithm.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland