Multimodal Sensor Fusion and Navigation

Semester
First semester: PPCU, Budapest
Credit
5
Lecturer
Dr. András HORVÁTH, PhD, associate professor
Character
Elective
Objectives

The main goal of the course is to give an overivew about real time algorithms and architecutres used in multi-sensor data fusion and navigation.
The course introduces estimation theory, the necessary definitions in static, dynamics linear and non-linear cases and also in discrete and continous systems. Reveals and explaind such generally used algorithms like the Kalman- and the Bootstrap-filter. Also the limitations and applications of these algorithms in pracitcal problems.
The course gives 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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