The diagnosis of faults in instrumentation equipments can often be confused with faults in the system. The correct diagnosis of instrument faults is of importance.Here it is described how to detect instrument faults in non-linearity. Time-varying processes that include uncertainties such as modelling error, parameter ambiguity, and input and output noise. The design of state estimation filters with zero sensitivity to the uncertainties and maximum sensitivity to the instrument faults is described together with the conditions for the existence of such filters.The idea was applied to the fault diagnosis of a heat exchanger. The heat exchanger can be described by a bilinear model with modelling uncertainties. The cause of the fault is estimated from a fault dictionary which was compiled.

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This paper describes a new type of radio wave spatial filtering to measure the absolute speed of vehicles. The electric field intensity of radio waves generated and propagated from a broadcasting station demonstrate stochastically periodic and non-Gaussian spatial patterns due to the multi-pass fading phenomenon. We detect the patterns and apply the spatial filtering technique to the patterns to measure the absolute speed. Here we investigated the optimal conditions of the filtering via the study on the stochastic property of the patterns. We developed the optimal filtering system. Experiment carried out by the filter on real roads by real automobile demonstrated the validity of the proposed radio wave spatial filtering.