Mohamed M. Atia

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Context-awareness and Location-Based-Services are of great importance in mobile computing environments. Although fingerprinting provides accurate indoor positioning in Wireless Local Area Networks (WLAN), difficulty of offline site surveys and the dynamic environment changes prevent it from being practically implemented and commercially adopted. This paper(More)
This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated(More)
Global Positioning System (GPS) accuracy deteriorates significantly in dense urban areas and it is almost unavailable inside buildings. Thus, an alternative accurate navigation system for such GPS-denied systems is of great importance. In this paper, the popular IEEE 802.11 WLAN (WiFi) is utilized along with a MEMS-based reduced inertial sensors system(More)
Royal Military College of Canada. He received a Ph.D. degree (Computer and Electrical Engineering) from Queen's University in 2013. He has several years of industry experience in software systems design and development. He has 40+ international publications, one book chapter, and several patent applications in the in the area of multi-sensor integrated(More)
A Kalman filter (KF) enhanced by the Gaussian process regression (GPR) technique is suggested to bridge GPS-outages in navigation solutions where inertial navigation systems (INS) and GPS are integrated. A KF utilises linearised dynamic models. If a low-cost MEMS-based INS with complex stochastic nonlinearity is considered, performance degrades(More)
In fingerprint-based wireless positioning, a high number of wireless access points solicits feature reduction to obtain a compact radio map for accurate real-time positioning. Although principal component analysis (PCA) can be used to reduce dimensionality, PCA is compu-tationally expensive. Additionally, PCA maps the data to a new space where physical(More)
The accurate estimation of measurements covariance is a fundamental problem in sensors fusion algorithms and is crucial for the proper operation of filtering algorithms. This paper provides an innovative solution for this problem and realizes the proposed solution on a 2D indoor navigation system for unmanned ground vehicles (UGVs) that fuses measurements(More)