Improving Indoor Localization System Using a Partitioning Technique Based on RSS and ToA

Designing a localization system for an indoor environment faces more challenges because of multipath and interference problems. In this field, the most important techniques used for such environment, are RSS and ToA which need to be improved especially from more interference because of the huge multipath problems. In this paper, a case study of a selected building is chosen in order to apply the proposed technique of this research. Such proposal is based on the PT ‎ of the area in the case study into MZ. Each zone is allocated special values for the parameters used to estimate the target positions. WI package is used to simulate the case study area and apply such proposal based on RSS and ToA. The results confirm that the estimated locations are close to the real locations by the average error of (2.8) meter and (0.192) meter for ToA corresponding one zone and four zones ‎respectively. ‎ In contrast, the results of our experiment show that the accuracy is improved from an average error of (2.4) meter and (0.217) meter for RSS corresponding one zone and four zones ‎respectively‎. Such results confirm that dividing the case study area into more zones leads to more accuracy.

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An Indoor Localization System Using Residual Learning with Channel State Information

Entropy ◽

10.3390/e23050574 ◽

2021 ◽

Vol 23 (5) ◽

pp. 574

Author(s):

Chendong Xu ◽

Weigang Wang ◽

Yunwei Zhang ◽

Jie Qin ◽

Shujuan Yu ◽

...

Keyword(s):

Channel State Information ◽

Indoor Environment ◽

Indoor Localization ◽

Location Based Services ◽

Channel State ◽

State Information ◽

Localization Accuracy ◽

Localization System ◽

Increasing Demand ◽

Degradation Problem

With the increasing demand of location-based services, neural network (NN)-based intelligent indoor localization has attracted great interest due to its high localization accuracy. However, deep NNs are usually affected by degradation and gradient vanishing. To fill this gap, we propose a novel indoor localization system, including denoising NN and residual network (ResNet), to predict the location of moving object by the channel state information (CSI). In the ResNet, to prevent overfitting, we replace all the residual blocks by the stochastic residual blocks. Specially, we explore the long-range stochastic shortcut connection (LRSSC) to solve the degradation problem and gradient vanishing. To obtain a large receptive field without losing information, we leverage the dilated convolution at the rear of the ResNet. Experimental results are presented to confirm that our system outperforms state-of-the-art methods in a representative indoor environment.

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INDOOR LOCALIZATION OF AN OMNI-DIRECTIONAL WHEELED MOBILE ROBOT

Transactions of the Canadian Society for Mechanical Engineering ◽

10.1139/tcsme-2013-0090 ◽

2013 ◽

Vol 37 (4) ◽

pp. 1043-1056 ◽

Cited By ~ 3

Author(s):

Sasha Ginzburg ◽

Scott Nokleby

Keyword(s):

Mobile Robot ◽

Indoor Environment ◽

Indoor Localization ◽

Wheeled Mobile Robot ◽

Fusion Algorithm ◽

Distance Measurements ◽

Localization System ◽

Relative Localization ◽

Position And Orientation ◽

Improved Performance

This paper presents a localization system developed for estimating the pose, i.e., position and orientation, of an omni-directional wheeled mobile robot operating in indoor structured environments. The developed system uses a combination of relative and absolute localization methods for pose estimation. Odometry serves as the relative localization method providing pose estimates through the integration of measurements obtained from shaft encoders on the robot’s drive motors. Absolute localization is achieved with a novel GPS-like system that performs localization of active beacons mounted on the mobile robot based on distance measurements to receivers fixed at known positions in the robot’s indoor workspace. A simple data fusion algorithm is used in the localization system to combine the pose estimates from the two localization methods and achieve improved performance. Experimental results demonstrating the performance of the developed system at localizing the omni-directional robot in an indoor environment are presented.

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Indoor Localization System Based on an Ultrasonic Sensor Network

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.383-390.3105 ◽

2011 ◽

Vol 383-390 ◽

pp. 3105-3109

Author(s):

Lei Zhang ◽

Shao Li Shi ◽

Ying Ying Sun ◽

Yang Tian

Keyword(s):

Sensor Network ◽

Indoor Environment ◽

Indoor Localization ◽

Response Speed ◽

Ultrasonic Sensors ◽

Control Center ◽

Localization System ◽

Localization Test ◽

Set Up ◽

Speed And Accuracy

This paper proposes an ultrasonic localization system, which adopts ultrasonic sensors to set up a network and realizes the information interactively with control center via 485 Bus. Using TDOA algorithm realizes the localization in indoor environment, and proposes a method to gain node information, on the basis, we can get a higher degree of response speed and accuracy of the system. Take an experiment by constructing an indoor localization test terrace, to prove feasibility of the theoretical.

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TDOA estimation using a pair of synchronized anchor nodes

International Journal of Microwave and Wireless Technologies ◽

10.1017/s1759078719000345 ◽

2019 ◽

Vol 11 (7) ◽

pp. 593-601 ◽

Cited By ~ 1

Author(s):

Vitomir Djaja-Josko ◽

Jerzy Kolakowski ◽

Jozef Modelski

Keyword(s):

Indoor Environment ◽

Indoor Localization ◽

Time Difference ◽

Time Difference Of Arrival ◽

System Architectures ◽

Localization System ◽

Position Determination ◽

Positioning Errors ◽

Anchor Nodes ◽

Novel Method

AbstractNowadays, as indoor localization is getting more popular, there is a growing need for reliable and accurate techniques of position determination. Recently, ultrawideband (UWB)-based systems are gaining popularity, since they make achieving positioning errors in the range of dozens of centimeters or even single centimeters, possible. The Time Difference of Arrival (TDOA)-based systems are especially attractive because they allow to simplify tags, in which functionality can be limited to transmission of packets. However, one of TDOA-based solution drawbacks is a need for strict synchronization between anchor nodes, which may be hard to provide in indoor environment. In the paper, a novel method for simplifying synchronization in TDOA-based UWB localization system is described. The paper presents two system architectures based on pairs of synchronized nodes. Results of simulations and experiments included in the article allow for evaluation of both solutions.

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An Introduction to Indoor Localization Techniques. Case of Study: A Multi-Trilateration-Based Localization System with User–Environment Interaction Feature

Applied Sciences ◽

10.3390/app11167392 ◽

2021 ◽

Vol 11 (16) ◽

pp. 7392

Author(s):

Bruno Andò ◽

Salvatore Baglio ◽

Ruben Crispino ◽

Vincenzo Marletta

Keyword(s):

System Architecture ◽

Indoor Localization ◽

State Of The Art ◽

Operating Conditions ◽

Environment Interaction ◽

End User ◽

Localization System ◽

Wide Range ◽

Continuous Estimation

The problem of estimating the indoor position of a person or an object, also known as indoor localization, has gained a lot of interest in the last decades. Actually, this feature would be valuable in many application contexts, from logistics to robotic and Assistive Technology. Different solutions have been proposed in the literature, exploiting a wide range of approaches. This paper aims to provide a brief review of the state-of-the-art approaches in the field, as well as to present the RESIMA case study. The latter exploits an ultrasound-based indoor localization system and a User–Environment Interaction functionality, which allows for performing the continuous estimation of the distance between the end-user and objects in the environment. The latter is valuable to provide the end-user with efficient assistance during the environment exploitation. The main focus of this work is related to the overall description of the system architecture, the trilateration algorithm adopted for the sake of user localization and the estimation of the delay time produced by user-distance computation under different operating conditions.

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A Fusion Approach of RSSI and LQI for Indoor Localization System Using Adaptive Smoothers

Journal of Computer Networks and Communications ◽

10.1155/2012/790374 ◽

2012 ◽

Vol 2012 ◽

pp. 1-10 ◽

Cited By ~ 9

Author(s):

Sharly Joana Halder ◽

Wooju Kim

Keyword(s):

Indoor Localization ◽

Distance Estimation ◽

Link Quality ◽

Average Error ◽

Indoor Environments ◽

Interference Avoidance ◽

Localization System ◽

Context Aware Computing ◽

Link Quality Indicator ◽

Unknown Node

Due to the ease of development and inexpensiveness, indoor localization systems are getting a significant attention but, with recent advancement in context and location aware technologies, the solutions for indoor tracking and localization had become more critical. Ranging methods play a basic role in the localization system, in which received signal strength indicator- (RSSI-) based ranging technique gets the most attraction. To predict the position of an unknown node, RSSI measurement is an easy and reliable method for distance estimation. In indoor environments, the accuracy of the RSSI-based localization method is affected by strong variation, specially often containing substantial amounts of metal and other such reflective materials that affect the propagation of radio-frequency signals in nontrivial ways, causing multipath effects, dead spots, noise, and interference. This paper proposes an adaptive smoother based location and tracking algorithm for indoor positioning by making fusion of RSSI and link quality indicator (LQI), which is particularly well suited to support context aware computing. The experimental results showed that the proposed mathematical method can reduce the average error around 25%, and it is always better than the other existing interference avoidance algorithms.

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Outlier-Detection-Based Indoor Localization System for Wireless Sensor Networks

International Journal of Navigation and Observation ◽

10.1155/2012/961785 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 16

Author(s):

Yu-Chi Chen ◽

Jyh-Ching Juang

Keyword(s):

Outlier Detection ◽

Indoor Environment ◽

Indoor Localization ◽

Signal Strength ◽

Sensor Data ◽

Wireless Sensor ◽

Localization Problem ◽

Detection Scheme ◽

Localization System ◽

Detection Techniques

The paper exploits the outlier detection techniques for wireless-sensor-network- (WSN-) based localization problem and proposes an outlier detection scheme to cope with noisy sensor data. The cheap and widely available measurement technique—received signal strength (RSS)—is usually taken into account in the indoor localization system, but the RSS measurements are known to be sensitive to the change of the environment. The paper develops an outlier detection scheme to deal with abnormal RSS data so as to obtain more reliable measurements for localization. The effectiveness of the proposed approach is verified experimentally in an indoor environment.

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