Method of signal processing in weigh-in-motion of vehicles

Based on the concept of inverse model, an adaptive inverse filter (AIF) was employed which could suppress noise within the bandwidth of the desired signal. Within the framework of the finite impulse response (FIR) filter, the inverse system of weigh-in-motion (WIM) system was constructed by using least mean square (LMS) adaptive algorithm as an innovative filter. Moreover, for the sake of best improving measurement accuracy, as a noise filter, a low-pass (LP) filter dedicated to restrain noise out of the bandwidth of useful signal was adopted. After processed by cascaded filter combination, namely, AIF filter and LP filter, obtained results, compared with those processed by the approach of parameter estimation, show a significant improvement in estimation of static weight of moving vehicles.