In these days, a technology that utilize of Bluetooth Low Energy (BLE) beacon, has been attracted attention to provide variety of convenience services. Especially, not limited to the service that can assist to people ...
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ISBN:
(纸本)9781467381161
In these days, a technology that utilize of Bluetooth Low Energy (BLE) beacon, has been attracted attention to provide variety of convenience services. Especially, not limited to the service that can assist to people directly such as public safety, healthcare, proximity-based service, mobile payment, etc., a technology that can provide convenience indirectly such as asset tracking has also been proposed. Most of all, the indoor location awareness using BLE beacon is the essential technique that can realize these services, it is expected to be more focused if the more BLE beacon is spread in the future. In this paper, we first analyse practical path loss model of BLE signals with compared to that of Wi-Fi signals in order to take advantage of the BLE beacon for indoor positioning. To estimate the practical path loss model, we employed four BLE beacons (each two beacon is the same manufacturer) and two of Wi-Fi AP. Each signal was measured during one minute at each reference distance from lm to 13m (with 2m interval) in a Line-of-Sight (LOS) environment. The calculated path loss model was used to generate a BLE signal virtually, we applied the model to configure the BLE radiomap and generate positioning measurement data in our simulation. Since BLE signal has relatively lower tx power compared to Wi-Fi APs, it requires much more beacons to achieve comparable positioning accuracy. We focused on the relationship between the number of installed beacon and its positioning accuracy in this paper.
Knowing the future position of a mobile user bring huge benefit to applications in the field of location-based services (LBSs). One of the major advantages is that helps LBSs provide targeted content or disseminate ad...
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In this paper, we proposed Advanced Heuristic Drift Elimination (AHDE) which can remove azimuth drift error in indoor environments. In Pedestrian Dead Reckoning (PDR) system, azimuth error is one of the main factors t...
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In this paper, we proposed Advanced Heuristic Drift Elimination (AHDE) which can remove azimuth drift error in indoor environments. In Pedestrian Dead Reckoning (PDR) system, azimuth error is one of the main factors that cause estimated position error. In order to reduce azimuth error, several methods are used. Heuristic Drift Elimination (HDE) algorithm proposed by Johann Borenstein shows great strength in indoor environments. HDE assumes that generally walls and corridors are straight and either parallel or orthogonal to each other in man-made building. They called the typical directions of walls and corridors as the dominant directions. HDE is corrected if the computed azimuth angle matches the closest dominant direction. HDE also has limitation when the pedestrian walks in various directions because HDE can cause a new azimuth error by matching the closed dominant direction. To overcome these limitations, we propose AHDE which is based on INS-EKF-ZUPT (IEZ) by using foot-mounted IMU. The algorithm consists with the following two steps. First, it determines whether a pedestrian is walking straight forward or not. If a pedestrian is not walking straight forward, the algorithm estimates the biases of accelerometers and gyroscopes by Zero velocity UPdaTe (ZUPT) method. However if the pedestrian is walking straight forward, the algorithm determines whether the pedestrian is walking along the dominant direction or not. When it is determined that pedestrian is walking along the dominant direction, the algorithm corrects the computed azimuth angle to the closest dominant direction. When it is determined that the pedestrian is not walking along the dominant direction but walking straight with no change in azimuth, AHDE applies a correction to the gyro output which contains the bias error. Experimental results show that the accuracy of AHDE is improved compared to HDE and the algorithm is a powerful method which can reduce the azimuth error in complex motion.
For commercial Wi-Fi localization, the construction of precise fingerprint DB or AP position DB is very important. While various wireless signal surveying methods such as war driving and user generated crowdsourcing c...
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