Comparison of Indoor localization techniques by using reference nodes and weighted k-NN algorithms
نویسندگان
چکیده
Positioning accuracy with Landmarc localization systems in the literature is around 2 meters. In this study, a reference node topology is introduced and 3-NN weighted algorithm is utilized to determine the unknown target locations. Firstly, target localization is carried out by using simple Landmarc system. Secondly, two stage 3-NN algorithm is deployed to estimate the target location. Finally, 3-NN algorithm is utilized with a new weight mechanism related to both physical and Euclidean distances. Overall comparative results reveal that classical Landmarc technique introduces 1.2 meter error distance while two stage 3-NN algorithms introduces 0.7 meter and new weighted system introduces 0.4 meter error.
منابع مشابه
Improvement of the Effective Components in the PDR Positioning Method Based on Detecting the User’s Movement Mode Using Smartphone Sensors
The purpose of this paper is to evaluate and improve the accuracy of indoor positioning using smartphone sensors based on Pedestrian Dead Reckoning (PDR) method. In some specific situations, such as fires or power outages that disable infrastructure-based positioning techniques, using PDR method based on smartphone sensors that perform positioning continuously is a good solution.This paper focu...
متن کاملAn experimental study of indoor RSS-based RF fingerprinting localization using GSM and Wi-Fi signals
Localization of mobile users in indoor environments has many practical applications in daily life. In this paper, we study the performance of the received signal strength (RSS)-based radio frequency (RF) fingerprinting localization method in a shopping mall environment considering both calibration and practical measurement cases. In the calibration case, the test data for the RSS fingerprinting...
متن کاملReference node placement and selection algorithm based on trilateration for indoor sensor networks
The key problem of location service in indoor sensor networks is to quickly and precisely acquire the position information of mobile nodes. Due to resource limitation of the sensor nodes, some of the traditional positioning algorithms, such as two-phase positioning (TPP) algorithm, are too complicated to be implemented and they cannot provide the real-time localization of the mobile node. We an...
متن کاملComparison of Two Quantitative Susceptibility Mapping Measurement Methods Used For Anatomical Localization of the Iron-Incorporated Deep Brain Nuclei
Introduction Quantitative susceptibility mapping (QSM) is a new contrast mechanism in magnetic resonance imaging (MRI). The images produced by the QSM enable researchers and clinicians to easily localize specific structures of the brain, such as deep brain nuclei. These nuclei are targets in many clinical applications and therefore their easy localization is a must. In this study, we aimed to i...
متن کاملA Rssi Based Localization Algorithm for WSN Using a Mobile Anchor Node
Wireless sensor networks attracting a great deal of research interest. Accurate localization of sensor nodes is a strong requirement in a wide area of applications. In recent years, several techniques have been proposed for localization in wireless sensor networks. In this paper we present a localization scheme with using only one mobile anchor station and received signal strength indicator tec...
متن کامل