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This paper focuses on WiFi indoor positioning based on received signal strength, a common local positioning approach with a number of prominent advantages such as low cost and ease of deployment. Weighted k nearest neighbor (WKNN) approach and Naive Bayes Classifier (NBC) method are two classic position estimation strategies for location determination using WiFi fingerprinting. Both of them need to...
Methods to cluster fingerprints based on Smallest-Enclosing-Circle (SEC) and to modify Weighted-K-Nearest-Neighbor (WKNN) matching algorithm for indoor fingerprint positioning system are proposed. Based on the approach to computing the smallest k-enclosing circle, the method proposed clusters fingerprints in database by introducing reference points' coordinates, instead of their received signal strength...
The concept of indoor location positioning has been around for decades now. Despite the existence of many algorithms that can achieve location positioning with remarkable performance in terms of accuracy, implementation of such algorithms has not been done on a large scale. There is a trade-off between the positioning accuracy and the complexity of the algorithm. This paper introduces and explains...
This paper investigates the role of quantization in the Received Signal Strength Indicator (RSSI) information used for fingerprinting (FP) applications. One of the common drawbacks of FP is the large data size and consequently the large search space and computational load as a result of either vastness of the positioning area or the finer resolution in the FP grid map: this limits the application...
The aim of this paper is to model the radio channel behavior in indoor environment for a transport application, and evaluate its impact on a ranging system by means of error estimation. The simulations were then performed in a tunnel scenario at 10 GHz, and the ray tracing model was adopted to obtain the channel response. In the positioning systems based on Time Of Arrival technique, the accuracy...
We demonstrate the effectiveness of a cooperative scheme to improve the positioning accuracy of four users moving in a building, by using the received signal strength (RSS) measurements from a number of known location RFID tags (anchors) and combining it with RSS measurements of mobile tags carried by themselves. The method is based on a centralized particle filter approach over the joint state of...
In foot-mounted positioning systems, it is hard to align multi-agent trajectories. In addition, the positioning accuracy is hard to maintain due to inertial drifts. An approach for trajectory initialization and calibration using iBeacons is proposed in this paper. This approach is under the framework of a particle filter. In the observation model of the particle filter, a nonparametric Gaussian Process...
This paper presents a systematic study of the scan skewing problem. Scan skewing is the non-rigid deformation of point clouds acquired by LiDAR's and is the result of their sequential scanning nature. We theoretically analyze the impact of skewing on scan matching and subsequently quantify the impact using synthetic LiDAR data with controlled skew distortions. We also show how the Geometric-Algebra...
This paper gives an overview on several current indoor georeferencing methods for kinematic multi sensor systems (MSS) and compares them to each other. Key issue is the application of these methods in complex indoor environments like office spaces with many separate rooms and contorted structures. Furthermore, a new universal knowledge-based approach for accurate indoor georeferencing will be introduced...
The Global Navigation Satellite Systems (GNSS) suffer from accuracy deterioration and outages in dense urban canyons and are almost unavailable for indoor environments. Nowadays, developing indoor positioning systems has become an attractive research topic due to the increasing demands on ubiquitous positioning. WiFi technology has been studied for many years to provide indoor positioning services...
The rapid growth of ubiquitous applications and location-based services has made indoor navigation an interesting topic. Some indoor localization solutions exploit radio information and Inertial Measurement Units (IMUs), which are embedded in most of the modern smartphones. In this paper, we present a real-time indoor localization approach that fuses WiFi Receiving Signal Strength Indicator (RSSI)...
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