Improving the Response of a Rollover Sensor Placed in a Car under Performance Tests by Using Optimal Signal Processing Techniques

In this paper, a sensor to measure the rollover angle of a car under performance tests is presented. Basically, the sensor consists of a dual-axis accelerometer, analog-electronic instrumentation stages, a data acquisition system and a square-root adaptive filtering algorithm for recursive least-squares estimation (QR-RLS). In short, the adaptive filter is used to improve the performance of the rollover sensor by carrying out an optimal prediction of the relevant signal coming from the sensor, which is buried in a broad-band noise background where we have little knowledge of the noise characteristics. The experimental results are satisfactory and show a significant improvement in the signal-to-noise ratio at the system output