Simulation of digital filter banks and signal classification in wideband monitoring tasks

Abstract

The paper is devoted to handling radio monitoring tasks (wideband monitoring tasks) in real time. We suggest a new multichannel modification of the weighted overlap-add algorithm (WOLA-algorithm) for processing vector (multichannel) signals and performing multichannel signal classification. Filter bank implementation is considered using computers based on the CUDA (Compute Unified Device Architecture) technology. We show that CUDA is efficient for large signal sets due to its low temporal costs. We study signal classification in filter bank channels for different signal-tonoise ratios using binary decision trees, the iterative procedure Adaboost, and neural networks. Our experiments provided a total classification error less than 10%.