Parameter Tuning in the Application of Stochastic Resonance to Redundant Sensor Systems

Abstract

Stochastic resonance (SR) is a phenomenon by which the addition of random noise improves the detection of weak signals. Thus far, this phenomenon has been extensively studied with the aim of improving sensor sensitivity in various fields of engineering research. However, the possibility of actual application of SR has not been explored because the target signal has to be known in order to confirm the occurrence of SR. In this paper, we propose an optimization method for making SR usable in engineering applications. The underlying mechanism of the proposed method is investigated using information theory and numerical simulation. We developed a tactile sensing system based on the simulation results. The proposed method is applied to this system in order to optimize its parameters for exploiting SR. Results of the experiment show that the developed tactile sensing system successfully achieved higher sensitivity than a conventional system.