Application of neural networks to bearing estimation

Abstract

This study presents an application of a feedforward neural network (NN) structure to the bearing estimation problem. Using N snapshots from M sensors, the NN estimates the sensor-to-sensor propagation delays, which yield the far-field source location. The proposed network has only one output, which is the direction-of-arrival (DOA) angle. Thus, the network does not require any: preprocessing. ?he NN buffers the sensor data, treats them as multidimensional delayed patterns and gives the location of a sinusoidal signal source in a noisy environment as output.