ELEC-E8740 - Basics of sensor fusion D, Lecture, 14.9.2021-14.12.2021

Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

After successfully completing this course, the participants are able to

  • explain the principles and components of sensor fusion systems,
  • construct continuous and discrete time state space models based on ordinary differential equations, difference equations, and physical sensor models,
  • identify and explain the differences between linear and nonlinear models and their implications on sensor fusion
  • develop and compare state space models and Kalman as well as particle filtering algorithms for solving sensor fusion problems.

Credits: 5

Schedule: 14.09.2021 - 14.12.2021

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Simo Särkkä, Lauri Palva

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    The course content includes: Probabilistic modeling of dynamic systems, sensor models, batch estimation, Kalman and extended Kalman filtering, bootstrap particle filtering.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Project work, exercises, and final examination

Workload

  • valid for whole curriculum period:

    36 h contact teaching, 97 h independent studies

DETAILS

Study Material

  • valid for whole curriculum period:

    Roland Hostettler and Simo Särkkä: Lecture notes on Basics of Sensor Fusion; Gustafsson: Statistical Sensor Fusion (2012)

     

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    9 Industry, Innovation and Infrastructure

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Autumn I-II

    2021-2022 Autumn I-II

    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=ELEC-E8740

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

    Weboodi

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