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Sensors 2012, 12(1), 115-147; doi:10.3390/s120100115

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

Trusted Positioning Inc., Calgary, AB T2L 2K7, Canada
Electrical and Computer Engineering Department, Queen’s University, Kingston, ON K7L 3N6, Canada
Electrical and Computer Engineering Department, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada
Author to whom correspondence should be addressed.
Received: 17 November 2011 / Revised: 12 December 2011 / Accepted: 13 December 2011 / Published: 22 December 2011
(This article belongs to the Section Physical Sensors)


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. View Full-Text
Keywords: embedded systems; FPGA; soft-core; land vehicle navigation; Global Positioning System; inertial sensors; Kalman filter embedded systems; FPGA; soft-core; land vehicle navigation; Global Positioning System; inertial sensors; Kalman filter

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Abdelfatah, W.F.; Georgy, J.; Iqbal, U.; Noureldin, A. FPGA-Based Real-Time Embedded System for RISS/GPS Integrated Navigation. Sensors 2012, 12, 115-147.

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