What signal processing techniques are used in advanced sensor systems?

Advanced sensor signal processing includes: digital filtering (FIR/IIR for noise reduction, notch filters for specific frequency rejection), linearization algorithms (polynomial, lookup table for non-linear sensors), sensor fusion (Kalman filtering for combining multiple sensor inputs), adaptive filtering (for time-varying noise characteristics), signal validation (range checking, rate-of-change limits, stuck value detection), FFT analysis (for vibration and pattern recognition), and machine learning algorithms (anomaly detection, predictive maintenance). Implementation on microcontrollers or DSPs in smart sensors enables sophisticated measurement and diagnostics at the device level.