Distortion Analysis of Memory-Less Nonlinear Sensors

Distortion associated with memory-less nonlinear sensors is analyzed and several distortion compensation techniques are presented. Sensor nonlinearity is considered a defect in sensory systems because it introduces distortion into the system. Due to the fact that no efficient technique is available to deal with the issues related sensor nonlinearity, nonlinear primary sensors tend to be ignored. In this paper, we point out that there are certain advantages of using nonlinear sensor and nonlinear distortion caused by sensor nonlinearity may be completely compensated. A robust and efficient signal recovery procedure is derived to facilitate the design of nonlinear sensors. Not having an accurate sensor will result in errors and it is shown that the error can be minimized with a proper choice of a convergence parameter whereby stability of the developed algorithm is established. Simulation results are presented to validate the algorithms developed.