Statistical sensor fusion of ECG data using automotive-grade sensors

Multi-sensor data fusion using Bayesian programming : an automotive application

Sensor Data Fusion in Automotive Applications

Sensor data fusion plays an important role in current and future vehicular active safety systems. The development of new advanced sensors is not sufficient enough without the utilisation of enhanced signal processing techniques such as the data fusion methods. A stand alone sensor cannot overcome certain physical limitations as for example the limited range and the field of view. Therefore comb...

Road Grade Estimation Results Using Sensor and Data Fusion

Advanced driver assistance systems for heavy duty vehicles, such as lookahead cruise and gearshift controllers, rely on high quality map data. Current digital maps do not offer the required level of road grade information. This contribution presents an algorithm for on-board road grade estimation based on fusion of GPS and vehicle sensor data with measurements from previous runs over the same r...

Improved road grade estimation using sensor fusion

A method for estimation of the road grade based on standard mounted sensors in a heavy duty vehicle is presented. The method combines information from a barometer and a GPS with velocity and torque measurements of conventional type. The sensor information is adaptively integrated using extended Kalman filtering. This provides a systematic method for dealing with varying uncertainty in the senso...

Sensor Fusion for Automotive Applications

Mapping stationary objects and tracking moving targets are essential for many autonomous functions in vehicles. In order to compute the map and track estimates, sensor measurements from radar, laser and camera are used together with the standard proprioceptive sensors present in a car. By fusing information from different types of sensors, the accuracy and robustness of the estimates can be inc...