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Orientation estimation is very important for development of unmanned aerial systems (UAS). Kalman filtersare widely used; however they assume linearity and Gaussianstatistics. While these assumptions work well for high-quality,high-cost sensors, they do not work as well for low-cost, low quality sensors. In these cases, complementary filters are usedsince no assumptions are made with regards to linearity andstatistics. This paper gives a review of the different typesof complementary filters bein

Author

caue

Language

EN