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Smartphone based indoor localization and tracking model using bat algorithm and Kalman filter

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Abstract

In recent days, accurate localization becomes essential for enabling smartphone-based navigation to attain maximum accuracy in the construction of the real world.Fingerprint-based localization is the widespread solution to achieve and assure effective performance. In this study, a new fingerprint-based localization model using a bat algorithm (BA) is presented stimulated by the echolocation nature of microbats. The presented model adapts BA for estimating the location information. Initially, the presented model applies a Bayesian-rule based objective function. Then, the BA is used for improving the accuracy and analyzing the effects of the initial position of the bats on the localization outcome. For mitigating the estimation error, the Kalman filter is employed for updating the initially determined position using the BA for tracking purposes. The experimental analysis indicated an improvement in real-time performance and decrease in computation complexity. The presented model also obtained maximum localization accuracy with minimum localization error over the compared methods.

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  1. Christ University, Bangalore, India

    R. Gobi

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  1. R. Gobi
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Gobi, R. Smartphone based indoor localization and tracking model using bat algorithm and Kalman filter. Multimed Tools Appl 80, 15377–15390 (2021). https://doi.org/10.1007/s11042-020-10438-y

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  • DOI: https://doi.org/10.1007/s11042-020-10438-y

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