Author
Ahmed M. Hassan
Bio: Ahmed M. Hassan is an academic researcher. The author has contributed to research in topics: Inertial navigation system & GPS/INS. The author has an hindex of 1, co-authored 1 publications receiving 2 citations.
Papers
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Proceedings Article•
01 Jan 2006
TL;DR: A new method for error estimation in a GPS/INS augmented system based on Artificial Neural Network (ANN) and Wavelet Transform (WT) was offered and it was found that the proposed technique reduces the standard deviation error in the position by about 91% and in velocity it was reduced by about 94%.
Abstract: Global Positioning System (GPS) and Strapdown Inertial Navigation System (SDINS) can be integrated together to provide a reliable navigation system. This paper offers a new method for error estimation in a GPS/INS augmented system based on Artificial Neural Network (ANN) and Wavelet Transform (WT). An ANN was adopted in this paper to model the GPS/INS position and velocity errors in real time to predict the error in the integrated system and provide accurate navigation information for a moving vehicle. It was found that the proposed technique reduces the standard deviation error in the position by about 91% for X, Y, and Z axes, while in velocity it was reduced by about 94% for North, East, and Down directions.
2 citations
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31 Oct 2016
TL;DR: The Global Positioning System (GPS) aided low cost Dead Reckoning (DR) system can provide without interruption the vehicle position for efficient fleet management solutions in smart cities.
Abstract: The Global Positioning System (GPS) aided low cost Dead Reckoning (DR) system can provide without interruption the vehicle position for efficient fleet management solutions in smart cities. The Extended Kalman Filter (EKF) is generally applied for data fusion using the sensor’s measures and the GPS position as a helper.
5 citations
23 Mar 2009
TL;DR: The results show that the intelligent navigator based on ANFIS more powerful compared with other (traditional and intelligent navigators based on ANN).
Abstract: In this work an intelligent navigator developed to overcome the limitations of existing Strapdown Inertial Navigation Systems (SINS) algorithm. This system is based on Adaptive Neuro-Fuzzy Inference System (ANFIS). As in previous work, which is based on Artificial Neural Network, the window based weight updating strategy was used, and the intelligent navigator evaluated using several SINS hypothetical field tests data. And the results show that the intelligent navigator based on ANFIS more powerful compared with other (traditional and intelligent navigator based on ANN).
5 citations