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

Multi - Sensor Data Fusion Using Bayesian Programming : anAutomotive

Using bayesian programming for multi-sensor multi-target tracking in automotive applications

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Designing a Home Security System using Sensor Data Fusion with DST and DSMT Methods

Today due to the importance and necessity of implementing security systems in homes and other buildings, systems with higher certainty, lower cost and with sensor fusion methods are more attractive, as an applicable and high performance methods for the researchers. In this paper, the application of Dempster-Shafer evidential theory and also the newer, more general one Dezert-Smarandache theory ...

A New Fault Tolerant Nonlinear Model Predictive Controller Incorporating an UKF-Based Centralized Measurement Fusion Scheme

A new Fault Tolerant Controller (FTC) has been presented in this research by integrating a Fault Detection and Diagnosis (FDD) mechanism in a nonlinear model predictive controller framework. The proposed FDD utilizes a Multi-Sensor Data Fusion (MSDF) methodology to enhance its reliability and estimation accuracy. An augmented state-vector model is developed to incorporate the occurred senso...

Information fusion for automotive applications - An overview

Please cite this article in press as: C. Stiller et a j.inffus.2011.03.005 This article focusses on the fusion of information from various automotive sensors like radar, video, and lidar for enhanced safety and traffic efficiency. Fusion is not restricted to data from sensors onboard the same vehicle but vehicular communication systems allow to propagate and fuse information with sensor data fr...