Multimodal Sensor Fusion and Navigation

First semester: PPKE, Budapest
Dr. András HORVÁTH, PhD, associate professor

The main goal of the course is to give an overview about real-time algorithms and architectures used in multi-sensor data fusion and navigation.
The course introduces estimation theory, the necessary definitions in static, dynamic, linear and non-linear cases and also in discrete and continuous systems. It reveals and explains such generally used algorithms like the Kalman- and the Bootstrap-filter, as well as the limitations and applications of these algorithms in practical problems.
The course gives a comprehensive knowledge about system-level computations in both top-down and bottom-up design of adaptive algorithmic solutions. Examines the topographic and non-topographic partitioning of data-flows regarding the modern multi-parallel architectures.

For more information, please download the teaching guide HERE.

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