- General Information -

sThe examination dates for the lecture are:

Wednesday 12th of February 2014 starting at 13:30h and

Friday 4th of April 2014 starting at 17:00h.

Please register now for a examination time slot if you are qualified by sending an email to lectureSDF@fkie.fraunhofer.de.

 

Lecture: Introduction to Sensor Data Fusion - Methods and Applications

Sensor data fusion is an omnipresent phenomenon that existed prior to its technological realization or the scientific reaction on it. In fact, all living creatures, including human beings, by nature or intuitively perform sensor data fusion. Each in their own way, they combine or fuse sensations provided by different and mutually complementary sense organs with knowledge learned from previous experiences and communications from other creatures. As a result, they produce a mental picture of their individual environment, the basis of behaving appropriately in their struggle to avoid harm or successfully reach a particular goal in a given situation. Sensor Data Fusion is the process of combining incomplete and imperfect pieces of mutually complementary sensor information in such a way that a better understanding of an underlying real-world phenomenon is achieved. Typically, this insight is either unobtainable otherwise or a fusion result exceeds what can be produced from a single sensor output in accuracy, relia- bility, or cost. Appropriate collection, registration and alignment, stochastic filtering, logical analysis, space-time integration, exploitation of redundancies, quantitative evaluation, and appropriate display are part of Sensor Data Fusion as well as the integration of related context information. Today, Sensor Data Fusion is evolving at a rapid pace and present in countless everyday systems and civilian products.

Course:

Exercises:

Other:

  • Term: Master, Diploma (Graduate)
  • Requirements:
  • Faculty: MA-INF 3310, (B,C)[B4]
  • Effort: 2L+2E
  • Exams: Information on the exams can be found in the Introduction Slides which are offered for download below. If you have further questions, please contact felix.govaers@fkie.fraunhofer.de.
  • Follow-up/Side-events: The lecture will be continued in SS 2014.

The slides and other downloads are available from within the university or via passwort. The password is announced will be announced at the next lecture or can be requested at lectureSDF@fkie.fraunhofer.de

Slides

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Exercises

DateFile
13.11.2013undefinedSlides
22.11.2013undefinedAssignment 1, kalman.zip, undefinedHelp-Document
17.12.2013undefinedAssignment 2undefinedimm.zip

 

 

Additional Information

Journal Tutorial published by P.D. Dr. W. KochIEEE_AESS_Tutorial_V__Koch.pdf
Monograph by P.D. Dr. W. KochTracking_and_Sensor_Data_Fusion__Koch.pdf
An introduction to the Kalman filterhttp://www.cs.unc.edu/~tracker/media/pdf/SIGGRAPH2001_CoursePack_08.pdf