The development of automotive remote surface identification system is an important step in ensuring road safety. In this paper we shall discuss a novel approach which addresses the road surface classification process. This method is based on polarimetric radar and sonar data fusion and surface identification using artificial neural network. A modular artificial neural network, which is considered in the paper, allows an overall increase in classification accuracy in the presence of a large number of surface types and a large number of signal features. We shall discuss the techniques involved and present classification results that have been achieved using modular neural network.
|Title of host publication||Radar Symposium (IRS), 2017 18th International|
|Place of Publication||Prague, Czech Republic|
|Number of pages||8|
|Publication status||E-pub ahead of print - 15 Aug 2017|
|Name||Radar Symposium (IRS)|