Autor/Autorin: Zaied Salah
Was born in Wanzerik, LY, on March 1975. Received the M.S. degree in communications and signal processing from Technical University of Ilmenau, DE in 2013. Received the B.S degree from Al-Jabal Al-Gharbi university, LY, in 1998. From 1999 to 2009, worked at GMMR project, LY, handling all telecommunications activities in southern part of GMMR phase II.
The Time Of Arrival (TOA) localization technique in Ultra-Wideband (UWB) wireless sensor networks (WSN) is one of the most promising position location techniques that can be used to estimate the position of passive target objects like people. TOA technique determine the time that the signal takes from the transmitting antenna, the passive target object and the receiving antenna. TOA is then transformed into range distance. TOA algorithm involves solving a non linear equations resulting from estimated TOA ranges measured from multiple receiving antennas. The performance of four different passive TOA algorithms in wireless sensor networks is analyzed. The assessment and comparison of these algorithms has been made for two different simulation scenarios in Additive White Gaussian Noise (AWGN), where a passive target object needs to be localized. The simulation also considers a measure of accuracy and precision for TOA algorithms by applying the principal component analysis (PCA) to the covariance matrix of position estimates.
Über den Autor
Was born in Wanzerik, LY, on March 1975. Received the M.S. degree in communications and signal processing from Technical University of Ilmenau, DE in 2013. Received the B.S degree from Al-Jabal Al-Gharbi university, LY, in 1998. From 1999 to 2009, worked at GMMR project, LY, handling all telecommunications activities in southern part of GMMR phase II.
Klappentext
The Time Of Arrival (TOA) localization technique in Ultra-Wideband (UWB) wireless sensor networks (WSN) is one of the most promising position location techniques that can be used to estimate the position of passive target objects like people. TOA technique determine the time that the signal takes from the transmitting antenna, the passive target object and the receiving antenna. TOA is then transformed into range distance. TOA algorithm involves solving a non linear equations resulting from estimated TOA ranges measured from multiple receiving antennas. The performance of four different passive TOA algorithms in wireless sensor networks is analyzed. The assessment and comparison of these algorithms has been made for two different simulation scenarios in Additive White Gaussian Noise (AWGN), where a passive target object needs to be localized. The simulation also considers a measure of accuracy and precision for TOA algorithms by applying the principal component analysis (PCA) to the covariance matrix of position estimates.
