A sequential approach for fault detection and identification of vehicles' ultrasonic parking sensors

This paper presents a sequential fault detection and identification algorithm to be applied for vehicle's ultrasonic parking sensors. The algorithm detects a bias fault in any of the ultrasonic sensors by computing the probability of having that bias fault given a constructed measurement residual that is only a function of the measurement noise and measurement fault. A set of bias hypotheses are assumed and initially given equal alarm probability. It is assumed that only one sensor will acquire a bias at any given time. Once the probability of a hypothesis approaches 1, that hypothesis is declared as the correct hypothesis and the bias associated with the hypothesis is removed from the sensors' reading. This study is essential to ensure accurate operation of vehicle's ultrasonic parking sensors.