The ML bearing estimation by using neural networks

This paper proposes a neural network to implement the maximum likelihood bearing estimation algorithm in real time. We show both analytically and by simulation that this neural network is guaranteed to be stable and to provide the maximum likelihood bearing estimation within an elapsed time of only a few characteristic time constants of the network. As a result, this proposed neural network is satisfactory for real-time bearing estimation.