Empirical investigation of the effect of the door's state on received signal strength in indoor environments at 2.4 GHz

2014 ◽  
Author(s):  
Alaa Alhamoud ◽  
Michael Kreger ◽  
Haitham Afifi ◽  
Christian Gottron ◽  
Daniel Burgstahler ◽  
...  
Keyword(s):  
Empirical Investigation ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Indoor Environments

Robustness in Fingerprinting-Based Indoor Positioning Systems

2018 ◽  
pp. 88-141 ◽  
Author(s):  
Shih-Hau Fang
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Signal Strength ◽  
Histogram Equalization ◽  
Indoor Positioning ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Location Based Services ◽  
Indoor Environments ◽  
Positioning Systems

Indoor positioning systems have received increasing attention for supporting location-based services in indoor environments. Received signal strength (RSS), mostly utilized in Wi-Fi fingerprinting systems, is known to be unreliable due to two reasons: orientation mismatch and variations in hardware. This chapter introduces an approach based on histogram equalization to compensate for orientation mismatch in robust Wi-Fi localization. The proposed method involves converting the temporal-spatial radio signal strength into a reference function (i.e., equalizing the histogram). This chapter also introduces an enhanced positioning feature, which is called delta-fused principal strength, to enhance the robustness of Wi-Fi localization against the problem of heterogeneous hardware. This algorithm computes the pairwise delta RSS and then integrates with RSS using principal component analysis. The proposed methods effectively and efficiently improve the robustness of location estimation in the presence of mismatch orientation and hardware variations, respectively.

scholarly journals PEOPLE’S PPRESENCE EFFECT ON WLAN-BASED IPS’ ACCURACY

2015 ◽  
Vol 77 (9) ◽  
Author(s):  
Iyad H Alshami ◽  
Noor Azurati Ahmad ◽  
Shamsul Sahibuddin
Keyword(s):  
Low Cost ◽  
Signal Strength ◽  
Access Point ◽  
Received Signal Strength ◽  
Positioning System ◽  
Indoor Environments ◽  
Received Signal Strength Indicator ◽  
Indoor Positioning System ◽  
Closed Environment ◽  
Presence Of People

In order to enable Location Based Service (LBS) closed environment, many technologies have been investigated to replace the Global Positioning System (GPS) in the localization process in indoor environments. WLAN is considered as the most suitable and powerful technology for Indoor Positioning System (IPS) due to its widespread coverage and low cost. Although WLAN Received Signal Strength Indicator (RSS) fingerprinting can be considered as the most accurate IPS method, this accuracy can be weakened due to WLAN RSS fluctuation. WLAN RSS fluctuates due to the multipath being influenced by obstacles presence. People presence under WLAN coverage can be considered as one of the main obstacles which can affect the WLAN-IPS accuracy. This research presents experimental results demonstrating that people’s presence between access point (AP) and mobile device (MD) reduces the received signal strength by -2dBm to -5dBm. This reduction in RSS can lead to distance error greater than or equal to 2m. Hence, any accurate IPS must consider the presence of people in the indoor environment. 

Theory and Practice of Signal Strength-Based Localization in Indoor Environments

2009 ◽  
pp. 282-301
Author(s):  
Eiman Elnahrawy ◽  
Richard P. Martin
Keyword(s):  
Signal Strength ◽  
Received Signal Strength ◽  
Theory And Practice ◽  
Location Information ◽  
Positioning System ◽  
Indoor Environments ◽  
Sensor Applications ◽  
Strength Based

This chapter discusses radio-based positioning. It surveys and compares several received signal strength localization approaches from two broad categories: point-based and area-based. It also explores their performance and means to improve it. It describes GRAIL - a sample positioning system. It finally concludes with a brief discussion of sensor applications that utilize location information.

scholarly journals Dealing with Insufficient Location Fingerprints in Wi-Fi Based Indoor Location Fingerprinting

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Kai Dong ◽  
Zhen Ling ◽  
Xiangyu Xia ◽  
Haibo Ye ◽  
Wenjia Wu ◽  
...  
Keyword(s):  
Value Added ◽  
Likelihood Estimation ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Stochastic Gradient Descent ◽  
Indoor Environments ◽  
Localization Accuracy ◽  
Indoor Location ◽  
Location Fingerprinting ◽  
Gradient Descent Algorithm

The development of the Internet of Things has accelerated research in the indoor location fingerprinting technique, which provides value-added localization services for existing WLAN infrastructures without the need for any specialized hardware. The deployment of a fingerprinting based localization system requires an extremely large amount of measurements on received signal strength information to generate a location fingerprint database. Nonetheless, this requirement can rarely be satisfied in most indoor environments. In this paper, we target one but common situation when the collected measurements on received signal strength information are insufficient, and show limitations of existing location fingerprinting methods in dealing with inadequate location fingerprints. We also introduce a novel method to reduce noise in measuring the received signal strength based on the maximum likelihood estimation, and compute locations from inadequate location fingerprints by using the stochastic gradient descent algorithm. Our experiment results show that our proposed method can achieve better localization performance even when only a small quantity of RSS measurements is available. Especially when the number of observations at each location is small, our proposed method has evident superiority in localization accuracy.

scholarly journals Indoor radio channel modeling and mitigation of fading effects using linear and circular polarized antennas in combination for smart home system at 868 MHz

2014 ◽  
Vol 12 ◽  
pp. 53-59 ◽  
Author(s):  
S. Wunderlich ◽  
M. Welpot ◽  
I. Gaspard
Keyword(s):  
Smart Home ◽  
Radio Channel ◽  
Path Loss ◽  
Signal Strength ◽  
Channel Modeling ◽  
Received Signal Strength ◽  
Communication Link ◽  
Indoor Environments ◽  
Environmental Controls ◽  
Indoor Radio

Abstract. The markets for smart home products and services are expected to grow over the next years, driven by the increasing demands of homeowners considering energy monitoring, management, environmental controls and security. Many of these new systems will be installed in existing homes and offices and therefore using radio based systems for cost reduction. A drawback of radio based systems in indoor environments are fading effects which lead to a high variance of the received signal strength and thereby to a difficult predictability of the encountered path loss of the various communication links. For that reason it is necessary to derive a statistical path loss model which can be used to plan a reliable and cost effective radio network. This paper presents the results of a measurement campaign, which was performed in six buildings to deduce realistic radio channel models for a high variety of indoor radio propagation scenarios in the short range devices (SRD) band at 868 MHz. Furthermore, a potential concept to reduce the variance of the received signal strength using a circular polarized (CP) patch antenna in combination with a linear polarized antenna in an one-to-one communication link is presented.

scholarly journals Indoor localization system based on virtual access points with filtering schemes

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986613 ◽  
Author(s):  
Dong Myung Lee ◽  
Boney Labinghisa
Keyword(s):  
Kalman Filter ◽  
Indoor Environment ◽  
Performance Testing ◽  
Signal Strength ◽  
Access Point ◽  
Received Signal Strength ◽  
Indoor Environments ◽  
Received Signal Strength Indicator ◽  
Access Points ◽  
Error Distance

In indoor positioning techniques, Wi-Fi is one of the most used technology because of its availability and cost-effectiveness. Access points are usually the main source of Wi-Fi signals in an indoor environment. If access points are optimized to cover the indoor area, this could improve Wi-Fi signal distribution. This article proposed an alternative to optimizing access point placement and distribution by introducing virtual access points that can be virtually placed in any part of the indoor environment without installation of actual access points. Virtual access points will be created heuristically by correlating received signal strength indicator of already existing access points and through linear regression. After introducing virtual access points in the indoor environment, next will be the addition of filters to improve signal fluctuation and reduce noise interference. Kalman filter has been previously used together with virtual access point and showed improvement by decreasing error distance of Wi-Fi fingerprinting results. This article also aims to include particle filter in the system to further improve localization and test its effectiveness when paired with Kalman filter. The performance testing of the algorithm in different indoor environments resulted in 3.18 and 3.59 m error distances. An improvement was added on the system by using relative distances instead of received signal strength indicator values in distance estimation and gave an error distance average of 1.85 m.

scholarly journals A three-dimensional pattern recognition localization system based on a Bayesian graphical model

2020 ◽  
Vol 16 (9) ◽  
pp. 155014771988489 ◽  
Author(s):  
Abdulraqeb Alhammadi ◽  
Fazirulhisyam Hashim ◽  
Mohd. Fadlee A Rasid ◽  
Saddam Alraih
Keyword(s):  
Graphical Model ◽  
Indoor Localization ◽  
Three Dimensional ◽  
Signal Strength ◽  
Local Area ◽  
Received Signal Strength ◽  
Reference Points ◽  
Indoor Environments ◽  
Localization System ◽  
Proposed Model

Access points in wireless local area networks are deployed in many indoor environments. Device-free wireless localization systems based on available received signal strength indicators have gained considerable attention recently because they can localize the people using commercial off-the-shelf equipment. Majority of localization algorithms consider two-dimensional models that cause low positioning accuracy. Although three-dimensional localization models are available, they possess high computational and localization errors, given their use of numerous reference points. In this work, we propose a three-dimensional indoor localization system based on a Bayesian graphical model. The proposed model has been tested through experiments based on fingerprinting technique which collects received signal strength indicators from each access point in an offline training phase and then estimates the user location in an online localization phase. Results indicate that the proposed model achieves a high localization accuracy of more than 25% using reference points fewer than that of benchmarked algorithms.

A Received Signal Strength Indication Adaptive Algorithm for Wireless Sensor Network

2013 ◽  
Vol 273 ◽  
pp. 505-509 ◽  
Author(s):  
He Huang ◽  
Bin Luo
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Environmental Parameters ◽  
Signal Strength ◽  
Estimation Algorithm ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Estimation Methods ◽  
Indoor Environments ◽  
Received Signal Strength Indication

Indoor environments are complicated and changeable, and RSSI (Received Signal Strength Indication) observations have great randomness, so the classic RSSI estimation algorithm has poor results in indoor environments. To solve this problem, a RSSI adaptive estimation algorithm (RAE-IW) based on Kalman filtering algorithm is presented in this paper, which achieves exact RSSI estimation, and fast adapts to the change of environmental parameters. Simulation results show that RAE-IW has low complexity, performs better than classic estimation methods in indoor environments, and applies to indoor wireless sensor network.

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