Title :
A multilayered ANN architecture for underwater target tracking
Author :
Jing, Yuyang ; El-Hawary, Ferial
Author_Institution :
Tech. Univ. Nova Scotia, Halifax, NS, Canada
Abstract :
A multilayered artificial neural network (ANN) is proposed for tracking underwater targets. A method using a feedforward network is presented to obtain state estimates from the time series of measurements. We shifted the time series observations before presentation to the ANN input and the simulation results show that the ANN tracker achieved a satisfactory degree of accuracy and robustness in dealing with noise in the measurements
Keywords :
backpropagation; feedforward neural nets; multilayer perceptrons; neural net architecture; noise; parameter estimation; sonar tracking; state estimation; time series; underwater sound; ANN input; ANN tracker; accuracy; backpropagation; feedforward network; measurements; multilayered ANN architecture; noise; passive sonar; robustness; simulation results; state estimates; time series observations; underwater target tracking; Backpropagation; Computer architecture; Feedforward neural networks; Multilayer perceptrons; Neural network applications; Noise; Parameter estimation; Sonar measurements; Sonar tracking; State estimation; Time series; Underwater acoustic measurements;
Conference_Titel :
Electrical and Computer Engineering, 1994. Conference Proceedings. 1994 Canadian Conference on
Conference_Location :
Halifax, NS
Print_ISBN :
0-7803-2416-1
DOI :
10.1109/CCECE.1994.405869
