A class of predictive analog filters for sensor signal processing and control instrumentation

Abstract

A class of analog continuous-time filters is introduced, having predictive properties for specified narrow-band signal models, such as low-order polynomials or sinusoids. Such filters are designed by using model transfer functions designed in the discrete-time domain. Z-to-s-domain mapping is done using the inverse bilinear transformation. The analog filters are implemented with active-RC structures, using the state-variable structure for biquads and a single-op-amp structure for real poles and zeros. The application examples include a filter for zero-crossing detectors, polynomial predictors for sensor signal smoothing, and an optimized sixth-order ramp-tracking filter for anti-aliasing and anti-imaging in digital signal processor (DSP) systems where high selectivity is required.