An application of the radial-basis function neural network (RBF NN) on the angle-of-arrival (AOA) estimation of a desired source in multipath environments is investigated. In conjunction with a set of judiciously constructed beamformers, the RBF NN are used to estimate the desired AOA within an angular sector of interest (ASOI). With a pilot signal emitted from each of the training AOA's within the ASOI, the RBF NN is trained with the higher-order statistics (HOS) estimated from the received array data. In principle, the RBF NN AOA estimator maps the complex HOS into the desired angle response as an function approximator. By matching the HOS to the center vectors associated with the hidden nodes and linearly combining the node values, an AOA estimate results. The efficacy of the proposed AOA estimator is confirmed by computer simulations.
|Number of pages||4|
|Journal||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|
|State||Published - 1 Jan 1995|
|Event||Proceedings of the 1995 20th International Conference on Acoustics, Speech, and Signal Processing. Part 2 (of 5) - Detroit, MI, USA|
Duration: 9 May 1995 → 12 May 1995