Drift-free integrators

Bias errors introduced by systems designed to measure low-frequency transients negate zero-mean assumptions on the measurement noise. On-line signal processing methods that require accurate low-frequency information can be adversely affected by bias errors. On-line integration of dynamic signals is a classical example of a process that is unstable in the presence of bias errors. Accurately integrated quantities (like velocity and displacement), from easily measured quantities (like acceleration), can inform control systems and reduce on-line computational burdens. This article introduces a feedback stabilization method for a hybrid digital-analog integrator. The analytical performance of this integrator is compared to a filtered analog integrator in the time and frequency domains. For wide-band random signals, the analog circuit performs well with respect to linearity and hysteresis, but does less well for long-period signals. A stabilized hybrid analog-digital integrator has exceptional accuracy when int...