Trilateration approaches for seamless out-/indoor GNSS and Wi-Fi smartphone positioning

2019 ◽  
Vol 13 (1) ◽  
pp. 47-61
Author(s):  
Guenther Retscher ◽  
Jonathan Kleine ◽  
Lisa Whitemore
Keyword(s):  
Inertial Sensors ◽  
Low Cost ◽  
Ground Truth ◽  
Mobile User ◽  
Location Based Services ◽  
Raspberry Pi ◽  
Indoor Environments ◽  
Point Location ◽  
Point Determination ◽  
The Relationship

Abstract More and more sensors and receivers are found nowadays in smartphones which can enable and improve positioning for Location-based Services and other navigation applications. Apart from inertial sensors, such as accelerometers, gyroscope and magnetometer, receivers for Wireless Fidelity (Wi-Fi) and GNSS signals can be employed for positioning of a mobile user. In this study, three trilateration methods for Wi-Fi positioning are investigated whereby the influence of the derivation of the relationship between the received signal strength (RSS) and the range to an Access Points (AP) are analyzed. The first approach is a straightforward resection for point determination and the second is based on the calculation of the center of gravity in a triangle of APs while weighting the received RSS. In the third method a differential approach is employed where as in Differential GNSS (DGNSS) corrections are derived and applied to the raw RSS measurements. In this Differential Wi-Fi (DWi-Fi) method, reference stations realized by low-cost Raspberry Pi units are used to model temporal RSS variations. In the experiments in this study two different indoor environments are used, one in a laboratory and the second in the entrance of an office building. The results of the second and third approach show position deviations from the ground truth of around 2 m in dependence of the geometrical point location. Furthermore, the transition between GNSS positioning outdoors and Wi-Fi localization indoors in the entrance area of the building is studied.

scholarly journals Trilateration Approaches for Indoor Wi-Fi Positioning

2019 ◽  
Vol 94 ◽  
pp. 02002
Author(s):  
Guenther Retscher ◽  
Jonathan Kleine ◽  
Lisa Whitemore
Keyword(s):  
Inertial Sensors ◽  
Low Cost ◽  
Ground Truth ◽  
Center Of Gravity ◽  
Location Based Services ◽  
Raspberry Pi ◽  
Point Location ◽  
Differential Approach ◽  
Time Modeling ◽  
Gnss Receivers

In smartphones several sensors and receivers are embedded which enable positioning in Location-based Services and other navigation applications. They include GNSS receivers and Wireless Fidelity (Wi-Fi) cards as well as inertial sensors, such as accelerometers, gyroscope and magnetometer. In this paper, indoor Wi-Fi positioning is studied based on trilateration. Three methods are investigated which are a resection, a calculation of the center of gravity point and a differential approach. The first approach is a commonly employed resection using the ranges to the Wi-Fi Access Points (APs) as radii and intersect the circles around the APs. In the second method, the center of gravity in a triangle of APs is calculated with weighting of the received signal strength (RSS) of the Wi-Fi signals. The third approach is developed by analogy to Differential GNSS (DGNSS) and therefore termed Differential Wi-Fi (DWi-Fi). Its advantage is that a real-time modeling of the temporal RSS variations and fluctuations is possible. For that purpose, reference stations realized by low-cost Raspberry Pi units are deployed which serve at the same time as APs. The experiments conducted in a laboratory and entrance of an office building showed that position deviations from the ground truth of around 2 m are achievable with the second and third method. Thereby the positioning accuracies depend mainly on the geometrical point location in the triangle of APs and reference stations and the RSS scan duration.

scholarly journals FUSION OF LOCATION FINGERPRINTING AND TRILATERATION BASED ON THE EXAMPLE OF DIFFERENTIAL WI-FI POSITIONING

2017 ◽  
Vol IV-2/W4 ◽  
pp. 377-384 ◽  
Author(s):  
G. Retscher
Keyword(s):  
Low Cost ◽  
Mobile User ◽  
Reference Station ◽  
Raspberry Pi ◽  
Indoor Environments ◽  
Differential Gps ◽  
Area Of Interest ◽  
Location Fingerprinting ◽  
Novel Approach ◽  
Interest Differential

Positioning of mobile users in indoor environments with Wireless Fidelity (Wi-Fi) has become very popular whereby location fingerprinting and trilateration are the most commonly employed methods. In both the received signal strength (RSS) of the surrounding access points (APs) are scanned and used to estimate the user’s position. Within the scope of this study the advantageous qualities of both methods are identified and selected to benefit their combination. By a fusion of these technologies a higher performance for Wi-Fi positioning is achievable. For that purpose, a novel approach based on the well-known Differential GPS (DGPS) principle of operation is developed and applied. This approach for user localization and tracking is termed Differential Wi-Fi (DWi-Fi) by analogy with DGPS. From reference stations deployed in the area of interest differential measurement corrections are derived and applied at the mobile user side. Hence, range or coordinate corrections can be estimated from a network of reference station observations as it is done in common CORS GNSS networks. A low-cost realization with Raspberry Pi units is employed for these reference stations. These units serve at the same time as APs broadcasting Wi-Fi signals as well as reference stations scanning the receivable Wi-Fi signals of the surrounding APs. As the RSS measurements are carried out continuously at the reference stations dynamically changing maps of RSS distributions, so-called radio maps, are derived. Similar as in location fingerprinting this radio maps represent the RSS fingerprints at certain locations. From the areal modelling of the correction parameters in combination with the dynamically updated radio maps the location of the user can be estimated in real-time. The novel approach is presented and its performance demonstrated in this paper.

scholarly journals INDOOR POSITIONING BY VISUAL-INERTIAL ODOMETRY

2017 ◽  
Vol IV-2/W4 ◽  
pp. 371-376 ◽  
Author(s):  
M. Ramezani ◽  
D. Acharya ◽  
F. Gu ◽  
K. Khoshelham
Keyword(s):  
Inertial Sensors ◽  
Low Cost ◽  
Measurement Model ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Indoor Environments ◽  
Positioning Accuracy ◽  
Indoor Location ◽  
Trajectory Length ◽  
Fundamental Requirement

Indoor positioning is a fundamental requirement of many indoor location-based services and applications. In this paper, we explore the potential of low-cost and widely available visual and inertial sensors for indoor positioning. We describe the Visual-Inertial Odometry (VIO) approach and propose a measurement model for omnidirectional visual-inertial odometry (OVIO). The results of experiments in two simulated indoor environments show that the OVIO approach outperforms VIO and achieves a positioning accuracy of 1.1 % of the trajectory length.

Constructing Floor Plan through Smoke Using Ultra Wideband Radar

2021 ◽  
Vol 5 (4) ◽  
pp. 1-29
Author(s):  
Weiyan Chen ◽  
Fusang Zhang ◽  
Tao Gu ◽  
Kexing Zhou ◽  
Zixuan Huo ◽  
...  
Keyword(s):  
Spatial Information ◽  
Low Cost ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Ultra Wideband ◽  
Indoor Environments ◽  
Floor Plan ◽  
Construction Methods ◽  
Median Error ◽  
Indoor Scenarios

Floor plan construction has been one of the key techniques in many important applications such as indoor navigation, location-based services, and emergency rescue. Existing floor plan construction methods require expensive dedicated hardware (e.g., Lidar or depth camera), and may not work in low-visibility environments (e.g., smoke, fog or dust). In this paper, we develop a low-cost Ultra Wideband (UWB)-based system (named UWBMap) that is mounted on a mobile robot platform to construct floor plan through smoke. UWBMap leverages on low-cost and off-the-shelf UWB radar, and it is able to construct an indoor map with an accuracy comparable to Lidar (i.e., the state-of-the-art). The underpinning technique is to take advantage of the mobility of radar to form virtual antennas and gather spatial information of a target. UWBMap also eliminates both robot motion noise and environmental noise to enhance weak reflection from small objects for the robust construction process. In addition, we overcome the limited view of single radar by combining multi-view from multiple radars. Extensive experiments in different indoor environments show that UWBMap achieves a map construction with a median error of 11 cm and a 90-percentile error of 26 cm, and it operates effectively in indoor scenarios with glass wall and dense smoke.

An Intelligent Navigation Solution for Land Mobile Location-Based Services

2002 ◽  
Vol 55 (2) ◽  
pp. 225-240 ◽  
Author(s):  
Stephen Scott-Young ◽  
Allison Kealy
Keyword(s):  
Firm Growth ◽  
Spatial Information ◽  
Inertial Sensors ◽  
Low Cost ◽  
Dead Reckoning ◽  
Location Based Services ◽  
Geographical Information ◽  
Navigation Systems ◽  
Navigation Solution ◽  
Lower Accuracy

The increasing availability of small, low-cost GPS receivers has established a firm growth in the production of Location-Based Services (LBS). LBS, such as in-car navigation systems, are not necessarily reliant on high accuracy but a continuous positioning service. When available, the accuracy provided by the standard positioning service (SPS) of 30 metres, 95% of the time is often acceptable. The reality is, however, that GPS does not work in all situations, and it is therefore common to integrate GPS with additional sensors. The use of low-cost inertial sensors alone during GPS signal outage is severely restricted due to the accumulation of errors that is inherent with such dead reckoning (DR) systems. Through the integration of spatial information with real-time positioning sensors, intelligence can be added to the land mobile navigation solution. The information contained within a Geographical Information System (GIS) provides additional observations that can be used to improve the navigation result. With this approach, the solution is not dependent on the performance capabilities of the navigation sensors alone. This enables the use of lower accuracy navigation devices, allowing low-cost systems to provide a sustained, viable navigation solution despite long-term GPS outages. Practical results are presented comparing solutions obtained from a hand-held GPS receiver to a gyroscope and odometer.

Positioning and Privacy in Location-Based Services

2010 ◽  
pp. 279-299
Author(s):  
Haibo Hu ◽  
Junyang Zhou ◽  
Jianliang Xu ◽  
Joseph Kee-Yin Ng
Keyword(s):  
Wireless Lan ◽  
Nearest Neighbor ◽  
Mobile User ◽  
Nearest Neighbor Search ◽  
Location Based Services ◽  
Indoor Environments ◽  
Related Information ◽  
Mobile Cellular ◽  
Neighbor Search ◽  
Traditional Approaches

Location positioning by GPS has become a standard function in modern handheld device specifications. Even in indoor environments, positioning by utilizing signals from the mobile cellular network and the wireless LAN has been intensively studied. This chapter starts with some review of the state-of-the-art technologies. Positioning technologies propel the market of location-based services (LBS). They are mobile content services that provide location-related information to users. However, to enjoy these LBS services, the mobile user must explicitly expose his/her accurate location to the service provider, who might abuse such location information or even trade it to unauthorized parties. To protect privacy, traditional approaches require a trusted middleware on which user locations are anonanonymous ymized. This chapter presents two new privacy-preserving approaches without such a middleware. The first is a non-exposure location cloaking protocol where only relative distances are exchanged. The second is a protocol for nearest neighbor search with controlled location exposure.

scholarly journals Validation of a Low-Cost Pavement Monitoring Inertial-Based System for Urban Road Networks

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3127
Author(s):  
Giuseppe Loprencipe ◽  
Flavio Guilherme Vaz de Almeida Filho ◽  
Rafael Henrique de Oliveira ◽  
Salvatore Bruno
Keyword(s):  
High Performance ◽  
Ride Comfort ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Road Networks ◽  
Measurement Unit ◽  
Raspberry Pi ◽  
Urban Road ◽  
Comfort Index

Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, a novel inertial sensor-based system is proposed using a low-cost inertial measurement unit (IMU) and a global positioning system (GPS) module, which are connected to a Raspberry Pi Zero W board and embedded inside a vehicle to indirectly monitor the road condition. To assess the level of pavement decay, the comfort index awz defined by the ISO 2631 standard was used. Considering 21 km of roads with different levels of pavement decay, validation measurements were performed using the novel sensor, a high performance inertial based navigation sensor, and a road surface profiler. Therefore, comparisons between awz determined with accelerations measured on the two different inertial sensors are made; in addition, also correlations between awz, and typical pavement indicators such as international roughness index, and ride number were also performed. The results showed very good correlations between the awz values calculated with the two inertial devices (R2 = 0.98). In addition, the correlations between awz values and the typical pavement indices showed promising results (R2 = 0.83–0.90). The proposed sensor may be assumed as a reliable and easy-to-install method to assess the pavement conditions in urban road networks, since the use of traditional systems is difficult and/or expensive.

scholarly journals Cost-Effective Proximity Detection and Filtering of Unreliable Results Based on BLE RSSI and IMU Readings Using Smartphones for Indoor Environments

2021 ◽  
Author(s):  
Katarzyna Filus ◽  
Sławomir Nowak ◽  
Joanna Domańska ◽  
Jakub Duda
Keyword(s):  
Low Cost ◽  
Real Life ◽  
Great Majority ◽  
Cost Effective ◽  
Location Based Services ◽  
Measurement Unit ◽  
Learning Activity ◽  
External Information ◽  
Indoor Environments ◽  
Boosted Decision Trees

Abstract Indoor environments are a major challenge in the domain of location-based services due to the inability to use GPS. Currently, Bluetooth Low Energy has been the most commonly used technology for such services due to its low cost, low power consumption, ubiquitous availability in smartphones and the dependence of the signal strength on the distance between devices. The article proposes a system that detects the proximity of a moving object with respect to static points (anchors), evaluates the quality of this prediction and filters out the unreliable results based on custom metrics. We define three metrics: two matrics based on RSSI and Intertial Measurement Unit (IMU) readings and one joint metric. This way the filtering is based on both, the external information (RSSI) and the internal information (IMU). To process the IMU data, we use machine learning activity recognition models (we apply feature selection and compare three models and choose the best one-Gradient Boosted Decision Trees). The proposed system is flexible and can be easily customized. The great majority of operations can be conducted directly on smartphones. The solution is easy to implement, cost-efficient and can be deployed in real-life applications (MICE industry, museums, industry).

scholarly journals A Tilt Visible Light Positioning System Based on Double LEDs and Angle Sensors

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1923
Author(s):  
Futong An ◽  
Haixin Xu ◽  
Shangsheng Wen ◽  
Hongzhan Song ◽  
Zhijian Chen ◽  
...  
Keyword(s):  
Visible Light ◽  
Low Cost ◽  
Location Based Services ◽  
Vertical Position ◽  
Positioning System ◽  
Geometric Information ◽  
Imaging Characteristics ◽  
Mobile Receiver ◽  
Relationship Of ◽  
The Relationship

Visible light positioning (VLP) has been studied widely due to its high accuracy and low cost in the field of location-based services (LBS). However, many existing VLP systems have the requirements that the receiver should be placed horizontally and more than three LED lamps should be used, which are difficult to meet in practical scenarios. Therefore, it is necessary to develop a novel VLP algorithm for tilted conditions. An effective and simple VLP system while the receiver is tilted based on double-LED lamps is proposed in this paper. The vertical position can be determined by combining the information from angle sensors with geometric information. Through analyzing the imaging characteristics of the tilted state, we can utilize the relationship of similarity to calculate the location of the mobile receiver. Experimental results show that the positioning accuracy of our proposed algorithm can reach 5.48 cm.

scholarly journals Low-cost methodology for skin strain measurement of a flexed biological limb

2016 ◽  
Author(s):  
Bevin Lin ◽  
Kevin Mattheus Moerman ◽  
Connor McMahan ◽  
Kenneth Pasch ◽  
Hugh Herr
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Ground Truth ◽  
Proximal Region ◽  
Posterior Surface ◽  
Point Location ◽  
Maximum Shear Strain ◽  
Prosthetic Socket ◽  
Socket Interface ◽  
3D Digital Models

*Objective:* The purpose of this manuscript is to compute skin strain datafrom a flexed biological limb, using portable, inexpensive, andeasily-available resources. *Methods:* We apply and evaluate this approachon a person with bi-lateral transtibial amputations, imaging left and rightresidual limbs in extended and flexed knee postures. We map 3D deformationsto a flexed biological limb using freeware and a simple point-and-shootcamera. Mean principal strain, maximum shear strain, as well as lines ofmaximum, minimum, and non-extension are computed from 3D digital models toinform directional mappings of the strain field for an unloaded residuallimb.*Results:* Peak tensile strains are ~ 0.3 on the anterior surface of theknee in the proximal region of the patella, whereas peak compressivestrains are ~ -0.5 on the posterior surface of the knee. Peak maximum shearstrains are ~ 0.3 on the posterior surface of the knee. The accuracy andprecision of this methodology are assessed for a ground truth model. Themean point location distance is found to be 0.08 cm, and the overallstandard deviation for point location difference vectors is 0.05 cm.*Conclusion:* This low-cost and mobile methodology may prove critical forapplications such as the prosthetic socket interface where whole-limb skinstrain data are required from patients in the field outside of traditional,large-scale clinical centers.*Significance:* Such data may inform the design of wearable technologiesthat directly interface with human skin.

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