A single-chip FPGA design for real-time ICA-based blind source separation algorithm

Blind source separation (BSS) of independent sources from their mixtures is a common problem in real world multi-sensor applications. In this paper, we propose an efficient hardware architecture for the implementation of real-time BSS that can be implemented using a low-cost FPGA. The architecture offers a good balance between hardware requirement (gate count and minimal clock speed) and separation performance. The FPGA design implements the modified Torkkola BSS algorithm for audio signals based on the ICA (independent component analysis) technique. The separation is performed by implementing noncausal filters, instead of the typical causal filters, within the feedback network. The architecture of the hardware is described. Results of various FPGA simulations and real-time testing of the final hardware design in a real environment are given.