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    Introduction and Implementations of the Kalman Filter

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    https://www.intechopen.com/books/introduction-and-implementations-of-the-kalman-filter
    Author(s)
    Felix Govaers
    Language
    English
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    Abstract
    Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some ""awareness"" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.
    URI
    https://directory.doabooks.org/handle/20.500.12854/50595
    Keywords
    Physical Sciences; Engineering and Technology; Computer and Information Science; Numerical Analysis and Scientific Computing; Signal Processing
    DOI
    10.5772/intechopen.75731
    ISBN
    9781838805364, 9781838807399, 9781838805371
    Publisher
    IntechOpen
    Publisher website
    https://www.intechopen.com/
    Publication date and place
    2019
    Pages
    128
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    • logo EUEuropean Union
      This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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