Fiches de cours 2017-2018


Localization and Navigation Methods


Lecturer(s) :

Botteron Cyril
Martinoli Alcherio
Merminod Bertrand
Skaloud Jan




Every 2 years


Next time: Fall 2018


Transmitting to the student state-of-the art methods and research topics in localization and navigation algorithms and systems. Students will be able to put in practice their knowledge in a course project and by three labs involved in the course. Lectures are concentrated in the first 5 weeks.


Week 1: Satellite positioning (Prof. Bertrand Merminod)

' Satellite orbit motion, Kepler's laws, broadcast and precise ephemeris

' Description of GPS signal structure and derivation of observables

' Inventory of error sources, random and non-random effects

' Derivation of mathematical models for absolute and differential positioning.

' Estimation of the position and its precision based on least-square principle analysis

' Overview of GNSS

' Lab assignments: Absolute GPS positioning with and without approximation

Week 2: Wireless location and state-space estimation (Dr. Cyril Botteron)

' Fundamentals of radio-frequency propagation and positioning

' Time and angle observables and associated error sources

' Kalman filtering applied to kinematic positioning

' Location with wireless computer network

' Ultra-wide band positioning principles

' Outdoor and indoor personal location, asset tracking

' Lab assignment: Kalman Filtering in kinematic positioning

Week 3: Trajectory and attitude determination with INS/GNSS (Dr. Jan Skaloud)

' Inertial sensors, inertial systems

' Linear dynamical systems, stochastic differential equations

' Inertial strapdown mechanization equations in (i,e,n) frames

' INS strapdown error equations and calibration states

' Alignment models

' Redundant IMU configurations

' Prediction, filtering, smoothing and calibration

' No lab assignments

Week 4: Trajectory and attitude determination via optical positioning and dynamic networks, integrated sensor orientation (Dr. Jan Skaloud)

' Colineraity condition for 0-D, 1-D and 2-D optical sensors

' Sensor models and observations, feature matching

' Principle of integrated sensor orientation. Orientation vs calibration

' Formulation of INS/GNSS/optical-sensor case in dynamic networks, numerical issues

' Lab assignment to select among visionary sensors; 1. oscillating cams & ALS; 2.
1-line-camera and ALS; etc.

Week 5: Localization and Navigation in Mobile Robotics (Prof. Alcherio Martinoli)

' Overview of localization techniques in mobile robotics (off-board/on-board;

' Basic kinematic models (differential drive, Ackerman steering vehicles)

' Odometry

' Feature-based localization

' Kalman filtering and particle filtering techniques applied to mobile robots

' Multi-robot localization

' Fundamental of navigation (path planning, landmark-based navigation)

' No lab assignments


Navigation, Localization, Kalman Filtering, Estimation Methods

Learning Prerequisites

Required courses

Least-square adjustment.

Recommended courses

Recommended Bachelor courses:
Advanced Satellite Positioning and/or Sensor Orientation.

Learning Outcomes

By the end of the course, the student must be able to:


Moodle Link

In the programs

  • Civil and Environmental Engineering (edoc), 2017-2018
    • Semester
    • Exam form
    • Credits
    • Subject examined
      Localization and Navigation Methods
    • Lecture
      30 Hour(s)
    • Exercises
      6 Hour(s)
    • Practical work
      20 Hour(s)

Reference week

Exercise, TP
Project, other


  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German