Abstract
AbstractIndoor tracking has evolved with various methods. The most popular method is using signal strength measuring techniques like triangulation, trilateration and fingerprinting, etc. Generally, these methods use the internal sensors of the smartphone. All these techniques require an adequate number of access point signals. The estimated positioning accuracy depends on the number of signals received at any point and precision of its signal (Wi-Fi radio waves) strength. In a practical environment, the received signal strength indicator (RSSI) of the access point is hindered by obstacles or blocks in the direct path or Line of sight. Such access points become an anomaly in the calculation of position. By detecting the anomaly access points and neglecting it during the computation of an indoor position will improve the accuracy of the positioning system. The proposed method, Practical Hindrance Avoidance in an Indoor Positioning System (PHA-IPS), eliminate the anomaly nodes while estimating the position, so then enhances the accuracy.
Highlights
IntroductionWith the evolution of the smartphone-based indoor positioning techniques [1] and advancement, numerous applications have been developed based on it, including mapsbased navigation, location-based control, personalized ad-
With the evolution of the smartphone-based indoor positioning techniques [1] and advancement, numerous applications have been developed based on it, including mapsbased navigation, location-based control, personalized ad-The accuracy of current Wi-Fi signal strength-based positioning techniques deteriorates in the practical environment due to the non-line of sight of the signal [2], new constructions, furniture, moving blocks, and even human presence in the line of the received signal strength indicator (RSSI) signal [3]
The received signal strength indicator (RSSI) of the access point is hindered by obstacles or blocks in the direct path or Line of sight
Summary
With the evolution of the smartphone-based indoor positioning techniques [1] and advancement, numerous applications have been developed based on it, including mapsbased navigation, location-based control, personalized ad-. The accuracy of current Wi-Fi signal strength-based positioning techniques deteriorates in the practical environment due to the non-line of sight of the signal [2], new constructions, furniture, moving blocks, and even human presence in the line of the RSSI signal [3]. The position estimated error increases if the RSSI strength is affected by the non-line of sight or any block in the direct path of the signal [5]. When the Line of sight is affected by moving a block or new construction in the fingerprinted environment a re-training phase would be called for, which is tedious [7]. The PHA-IPS method efficiently identifies the access point hindered by any obstacles and eliminates it completely during the position estimate
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