scholarly journals Accurate Ultrasound Indoor Localization Using Spring-Relaxation Technique

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1290
Author(s):  
Moi Tin Chew ◽  
Fakhrul Alam ◽  
Mathew Legg ◽  
Gourab Sen Sen Gupta
Keyword(s):  
Visible Light ◽  
Indoor Localization ◽  
Least Square ◽  
Relaxation Technique ◽  
Positioning System ◽  
Ultrasonic Sensing ◽  
Chirp Signals ◽  
Flight Measurement ◽  
Active Localization ◽  
Linear Least Square

This paper reports on the development of an ultrasonic sensing-based active localization system. The system employs an ultrasonic array to transmit chirp signals and time-of-flight measurement for ranging. The position of the receiver is estimated iteratively using the spring-relaxation technique. A median and 90-percentile error of 12.4 and 21.7 mm, respectively, were obtained for measurements at 625 positions within a 1.2 × 1.2 m area testbed. The spring-relaxation technique outperforms the widely adopted linear least square-based lateration technique while using the same ranging data. The performance of the system is benchmarked against that of visible light positioning using the same platform setup. The reported results show the ultrasonic system to be more accurate when compared with the visible light positioning system, which achieved median and 90-percentile errors of 33.7 and 58.6 mm, respectively.

scholarly journals An Indoor Visible Light Positioning System Using Tilted LEDs with High Accuracy

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 920
Author(s):  
Neha Chaudhary ◽  
Othman Isam Younus ◽  
Luis Nero Alves ◽  
Zabih Ghassemlooy ◽  
Stanislav Zvanovec ◽  
...  
Keyword(s):  
Visible Light ◽  
Polynomial Regression ◽  
Power Level ◽  
Least Square ◽  
Line Of Sight ◽  
Received Power ◽  
Strength Based ◽  
Complex Linear ◽  
Linear Least Square ◽  
First Time

The accuracy of the received signal strength-based visible light positioning (VLP) system in indoor applications is constrained by the tilt angles of transmitters (Txs) and receivers as well as multipath reflections. In this paper, for the first time, we show that tilting the Tx can be beneficial in VLP systems considering both line of sight (LoS) and non-line of sight transmission paths. With the Txs oriented towards the center of the receiving plane (i.e., the pointing center F), the received power level is maximized due to the LoS components on F. We also show that the proposed scheme offers a significant accuracy improvement of up to ~66% compared with a typical non-tilted Tx VLP at a dedicated location within a room using a low complex linear least square algorithm with polynomial regression. The effect of tilting the Tx on the lighting uniformity is also investigated and results proved that the uniformity achieved complies with the European Standard EN 12464-1. Furthermore, we show that the accuracy of VLP can be further enhanced with a minimum positioning error of 8 mm by changing the height of F.

scholarly journals Indoor Localization System Based on Bluetooth Low Energy for Museum Applications

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1055 ◽  
Author(s):  
Romeo Giuliano ◽  
Gian Carlo Cardarilli ◽  
Carlo Cesarini ◽  
Luca Di Nunzio ◽  
Francesca Fallucchi ◽  
...  
Keyword(s):  
Indoor Localization ◽  
Position Estimation ◽  
Low Energy ◽  
Least Square ◽  
Feed Forward Neural Network ◽  
Position Information ◽  
Bluetooth Low Energy ◽  
Performance Results ◽  
Linear Least Square ◽  
Position Estimate

In the last few years, indoor localization has attracted researchers and commercial developers. Indeed, the availability of systems, techniques and algorithms for localization allows the improvement of existing communication applications and services by adding position information. Some examples can be found in the managing of people and/or robots for internal logistics in very large warehouses (e.g., Amazon warehouses, etc.). In this paper, we study and develop a system allowing the accurate indoor localization of people visiting a museum or any other cultural institution. We assume visitors are equipped with a Bluetooth Low Energy (BLE) device (commonly found in modern smartphones or in a small chipset), periodically transmitting packets, which are received by geolocalized BLE receivers inside the museum area. Collected packets are provided to the locator server to estimate the positions of the visitors inside the museum. The position estimation is based on a feed-forward neural network trained by a measurement campaign in the considered environment and on a non-linear least square algorithm. We also provide a strategy for deploying the BLE receivers in a given area. The performance results obtained from measurements show an achievable position estimate accuracy below 1 m.

scholarly journals High-Accuracy and Real-Time Indoor Positioning System Based on Visible Light Communication and Mobile Robot

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xianmin Li ◽  
Zihong Yan ◽  
Linyi Huang ◽  
Shihuan Chen ◽  
Manxi Liu
Keyword(s):  
Mobile Robot ◽  
Visible Light ◽  
Real Time ◽  
Indoor Localization ◽  
Visible Light Communication ◽  
High Accuracy ◽  
Market Potential ◽  
Location Based Services ◽  
Positioning System ◽  
Robot Positioning

For mobile robots and location-based services, precise and real-time positioning is one of the most basic capability, and low-cost positioning solutions are increasingly in demand and have broad market potential. In this paper, we innovatively design a high-accuracy and real-time indoor localization system based on visible light positioning (VLP) and mobile robot. First of all, we design smart LED lamps with VLC and Bluetooth control functions for positioning. The design of LED lamps includes hardware design and Bluetooth control. Furthermore, founded on the loose coupling characteristics of ROS (Robot Operator System), we design a VLP-based robot system with VLP information transmitted by designed LED, dynamic tracking algorithm of high robustness, LED-ID recognition algorithm, and triple-light positioning algorithm. We implemented the VLP-based robot positioning system on ROS in an office equipped with the designed LED lamps, which can realize cm-level positioning accuracy of 3.231 cm and support the moving speed up to 20 km/h approximately. This paper pushes forward the development of VLP application in indoor robots, showing the great potential of VLP for indoor robot positioning.

scholarly journals Improvement of Ultrasound-based System Using Sine Wave Detector and CAN Network

2017 ◽  
Author(s):  
Sy Nguyen Tan
Keyword(s):  
Time Delay ◽  
Indoor Localization ◽  
Sine Wave ◽  
Field Application ◽  
Ultrasonic Signal ◽  
Least Square ◽  
Range Measurement ◽  
Mean Error ◽  
Wave Detector ◽  
Linear Least Square

This paper presents an improved indoor localization system based on RF and ultrasonic signal which we named SNSH system. This system composes of a transmitter mounted in a mobile target, and a series of receiver nodes which are managed by a coordinator. By measuring Time Delay of Arrival (TDoA) of RF and ultrasonic signal from the transmitter, distance from target to receiver node is calculated and sent to the coordinator through CAN network, and all the information are gathered in PC to estimate 3D position of the target. Sine wave detector and dynamic threshold filter are applied to provide excellent accuracy of range measurement from TDoA result, and multilateration algorithms is realized to optimize coordinate determination accuracy. Specifically, Linear Least Square and Non-linear Least Square techniques are implemented to contrast their performances in target coordinate estimation. RF signal encoding/decoding time, time delay in CAN network and math calculating are carefully considered to ensure optimal system performance and get ready for field application. Experiments show that sine wave detector algorithm has greatly improved range measurement accuracy, with mean error at 2.2mm and maximum error at 6.7 mm, for distance below 5m. In addition, 3D position accuracy is greatly enhanced by multilateration methods, with mean error in position stay under 15mm, and 90% confident error values at 23mm for LLS, 20mm for NLS. Overall system update period has been verified in real system operation, with maximum rate at 25ms, and compared with other existing researches.

GPS-DERIVED SECULAR VELOCITY FIELD AROUND SANGIHE ISLAND AND ITS IMPLICATION TO THE MOLUCCA SEA SEISMICITY

GEOMATIKA ◽  
2020 ◽  
Vol 26 (2) ◽  
pp. 107
Author(s):  
Leni Sophia Heliani ◽  
Cecep Pratama ◽  
Parseno Parseno ◽  
Nurrohmat Widjajanti ◽  
Dwi Lestari
Keyword(s):  
Surface Displacement ◽  
Active Regions ◽  
Least Square ◽  
The Other ◽  
Gps Data ◽  
West Side ◽  
Active Deformation ◽  
Secular Motion ◽  
Small Change ◽  
Linear Least Square

<p><em>Sangihe-Moluccas region is the most active seismicity in Indonesia. Between 2015 to 2018 there is four M6 class earthquake occurred close to the Sangihe-Moluccas region. These seismic active regions representing active deformation which is recorded on installed GPS for both campaign and continuous station. However, the origin of those frequent earthquakes has not been well understood especially related to GPS-derived secular motion. Therefore, we intend to estimate the secular motion inside and around Sangihe island. On the other hand, we also evaluate the effect of seismicity on GPS sites. Since our GPS data were conducted on yearly basis, we used an empirical global model of surface displacement due to coseismic activity. We calculate the offset that may be contained in the GPS site during its period</em><em>. </em><em>We remove the offset and estimate again the secular motion using linear least square. Hence, in comparison with the secular motion without considering the seismicity, we observe small change but systematically shifting the motion. We concluded the seismicity in the Molucca sea from 2015 to 2018 systematically change the secular motion around Sangihe Island at the sub-mm level. Finally, we obtained the secular motion toward each other between the east and west side within 1 to 5.5 cm/year displacement. </em></p>

scholarly journals Improved Visible Light-Based Indoor Positioning System Using Machine Learning Classification and Regression

2019 ◽  
Vol 9 (6) ◽  
pp. 1048 ◽  
Author(s):  
Huy Tran ◽  
Cheolkeun Ha
Keyword(s):  
Machine Learning ◽  
Visible Light ◽  
Noise Reduction ◽  
Indoor Positioning ◽  
Computational Time ◽  
Dual Function ◽  
Positioning System ◽  
Positioning Accuracy ◽  
Positioning Systems ◽  
Machine Learning Classification

Recently, indoor positioning systems have attracted a great deal of research attention, as they have a variety of applications in the fields of science and industry. In this study, we propose an innovative and easily implemented solution for indoor positioning. The solution is based on an indoor visible light positioning system and dual-function machine learning (ML) algorithms. Our solution increases positioning accuracy under the negative effect of multipath reflections and decreases the computational time for ML algorithms. Initially, we perform a noise reduction process to eliminate low-intensity reflective signals and minimize noise. Then, we divide the floor of the room into two separate areas using the ML classification function. This significantly reduces the computational time and partially improves the positioning accuracy of our system. Finally, the regression function of those ML algorithms is applied to predict the location of the optical receiver. By using extensive computer simulations, we have demonstrated that the execution time required by certain dual-function algorithms to determine indoor positioning is decreased after area division and noise reduction have been applied. In the best case, the proposed solution took 78.26% less time and provided a 52.55% improvement in positioning accuracy.

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