Hybrid navigation

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Hybrid navigation is the simultaneous use of more than one navigation system for location data determination, needed for navigation. By using multiple systems at once, the accuracy as a whole is improved. It also allows for a more reliable navigation system, as if one system fails, the other can kick in and provide accurate navigation for the user. [1] Especially for self-driving cars, the exact and continuous knowledge of the navigating object's location is essential. [2]

Contents

Function

GPS and other satellite based systems (GLONASS, GALILEO, BEIDOU, QZSS) provide a way to learn one's location, but these methods require free field conditions in order to receive the radio signal. Various satellite systems are subject to switching-off or reduction of data precision by the company or government that runs them. [3] They are also prone to intentional or unintentional disturbances. Even passing through a tunnel or a garage interrupts the data flow. In situations where the signal cannot be received reliably, alternate sources of location data are needed. Combining GPS with other methods can avoid these limitations, but each method has its own specific limitations. A hybrid system provides fault tolerance for each underlying method and improves the overall precision of the result. [4]

The hybrid system needs to decide how to choose among the different methods at any given time. One solution is a triple configuration, allowing 'result voting' for data collecting systems. [3] [5]

Alternate systems that supply navigational data include:

See also

Related Research Articles

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<span class="mw-page-title-main">Inertial navigation system</span> Continuously computed dead reckoning

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<span class="mw-page-title-main">Inertial measurement unit</span> Accelerometer-based navigational device

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<span class="mw-page-title-main">Pose tracking</span>

In virtual reality (VR) and augmented reality (AR), a pose tracking system detects the precise pose of head-mounted displays, controllers, other objects or body parts within Euclidean space. Pose tracking is often referred to as 6DOF tracking, for the six degrees of freedom in which the pose is often tracked.

References

  1. ↑ Rizos, C, Grejner-Brzezinska, DA, Toth, CK, Dempster, AG, Li, Y, Politi, N, Barnes, J, Sun, H (2008). A hybrid system for navigation in GPS-challenged environments: case study. Institute of Navigation (ION). OCLC   1056492868.{{cite book}}: CS1 maint: multiple names: authors list (link)
  2. ↑ Friedhelm Greis (2015-09-02). golem (ed.). "AUTONOMES FAHREN: Wer hat die besten Karten?" (in German). Retrieved 2016-07-17.
  3. 1 2 Bestmann, vonWulfen, Hecker, Kneissl, Kropp (August 2010). "Aviation Applications: Hybrid Navigation Techniques and Safety-of-Life Requirements". Archived from the original on 2016-07-17. Retrieved 2016-07-17.{{cite web}}: CS1 maint: multiple names: authors list (link)
  4. ↑ "HIGHLY AUTOMATED DRIVING (HAD) MAPS FOR AUTONOMOUS VEHICLES" . Retrieved 2016-07-18.
  5. ↑ Johannes Jahn (1997). "Optimality Conditions in Set Valued Vector Optimation". In Günter Fandel; Tomas Gal, Thomas Hanne (eds.). Multiple criteria decision making : proceedings of the Twelfth International Conference. New York: Springer-Verlag. p. 22.
  6. ↑ Leendert Dorst (2011-01-27). Hydro International (ed.). "How Does Inertial Navigation Work?" . Retrieved 2016-07-16.
  7. ↑ Stanley K. Honey (1985-04-02). "NAV85 Papers" (PDF). Archived from the original (PDF) on 2016-03-04. Retrieved 2016-07-17.
  8. ↑ Brooks Goodhue (2011-05-09). "What is DGPS or Differential GPS?" . Retrieved 2016-07-16.
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