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SSD A ROBUST RF LOCATION FINGERPRINT ADDRESSING
MOBILE DEVICES’ HETEROGENEITY
ABSTRACT:
Fingerprint-based methods are widely adopted for indoor localization purpose because of their
cost-effectiveness compared to other infrastructure-based positioning systems. However, the
popular location fingerprint, Received Signal Strength (RSS), is observed to differ significantly
across different devices' hardware even under the same wireless conditions. We derive
analytically a robust location fingerprint definition, the Signal Strength Difference (SSD), and
verify its performance experimentally using a number of different mobile devices with
heterogeneous hardware.
Our experiments have also considered both Wi-Fi and Bluetooth devices, as well as both Access-
Point (AP)-based localization and Mobile-Node (MN)-assisted localization. We present the
results of two well-known localization algorithms (K Nearest Neighbor and Bayesian Inference)
when our proposed fingerprint is used, and demonstrate its robustness when the testing device
differs from the training device. We also compare these SSD-based localization algorithms'
performance against that of two other approaches in the literature that are designed to mitigate
the effects of mobile node hardware variations, and show that SSD-based algorithms have better
accuracy.
ECWAY TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE
CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111
VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com
Robust SSD fingerprint for indoor localization

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Robust SSD fingerprint for indoor localization

  • 1. SSD A ROBUST RF LOCATION FINGERPRINT ADDRESSING MOBILE DEVICES’ HETEROGENEITY ABSTRACT: Fingerprint-based methods are widely adopted for indoor localization purpose because of their cost-effectiveness compared to other infrastructure-based positioning systems. However, the popular location fingerprint, Received Signal Strength (RSS), is observed to differ significantly across different devices' hardware even under the same wireless conditions. We derive analytically a robust location fingerprint definition, the Signal Strength Difference (SSD), and verify its performance experimentally using a number of different mobile devices with heterogeneous hardware. Our experiments have also considered both Wi-Fi and Bluetooth devices, as well as both Access- Point (AP)-based localization and Mobile-Node (MN)-assisted localization. We present the results of two well-known localization algorithms (K Nearest Neighbor and Bayesian Inference) when our proposed fingerprint is used, and demonstrate its robustness when the testing device differs from the training device. We also compare these SSD-based localization algorithms' performance against that of two other approaches in the literature that are designed to mitigate the effects of mobile node hardware variations, and show that SSD-based algorithms have better accuracy. ECWAY TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111 VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com