A Novel Angle-of-Arrival Based Position Estimation Scheme Using Visible Light in Indoor Positioning Systems

2014 ◽  
Author(s):  
Yinan Hou ◽  
Shilin Xiao ◽  
Meihua Bi ◽  
Zexi Yu ◽  
Yuankai Xue
Keyword(s):  
Visible Light ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Angle Of Arrival ◽  
Positioning Systems ◽  
Estimation Scheme

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.

scholarly journals Two-Phase Framework for Indoor Positioning Systems Using Visible Light

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1917 ◽  
Author(s):  
Gregary Prince ◽  
Thomas Little
Keyword(s):  
Visible Light ◽  
Indoor Positioning ◽  
Two Phase ◽  
Positioning Systems

scholarly journals Lora RTT Ranging Characterization and Indoor Positioning System

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Qiang Liu ◽  
XiuJun Bai ◽  
Xingli Gan ◽  
Shan Yang
Keyword(s):  
Estimation Method ◽  
Ground Truth ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Cumulative Distribution ◽  
Positioning System ◽  
Positioning Error ◽  
Positioning Systems ◽  
Ground Truth Location ◽  
Indoor Positioning System

In recent years, indoor positioning systems (IPS) are increasingly very important for a smart factory, and the Lora positioning system based on round-trip time (RTT) has been developed. This paper introduces the ranging characterization, RTT measurement, and position estimation method. In particular, a particle filter localization method-aided Lora pseudorange fitting correction is designed to solve the problem of indoor positioning; the cumulative distribution function (CDF) criteria are used to measure the quality of the estimated location in comparison to the ground truth location; when the positioning error on the x -axis threshold is 0.2 m and 0.6 m, the CDF with pseudorange correction is 61% and 99%, which are higher than the 32% and 85% without pseudorange correction. When the positioning error on the y -axis threshold is 0.2 m and 0.6 m, the CDF with pseudorange correction is 71% and 99.9%, which are higher than the 52% and 94.8% without pseudorange correction.

scholarly journals Multilateration Approach for Wide Range Visible Light Indoor Positioning System Using Mobile CMOS Image Sensor

2021 ◽  
Vol 11 (16) ◽  
pp. 7308
Author(s):  
Md Habibur Rahman ◽  
Mohammad Abrar Shakil Sejan ◽  
Wan-Young Chung
Keyword(s):  
Visible Light ◽  
Real Time ◽  
Indoor Positioning ◽  
Image Sensor ◽  
Computational Time ◽  
Positioning System ◽  
Horizontal Distance ◽  
Large Area ◽  
Positioning Systems ◽  
Wide Range

Visible light positioning (VLP) is a cost-effective solution to the increasing demand for real-time indoor positioning. However, owing to high computational costs and complicated image processing procedures, most of the existing VLP systems fail to deliver real-time positioning ability and better accuracy for image sensor-based large-area indoor environments. In this study, an effective method is proposed to receive coordinate information from multiple light-emitting diode (LED) lights simultaneously. It provides better accuracy in large experimental areas with many LEDs by using a smartphone-embedded image sensor as a terminal device and the existing LED lighting infrastructure. A flicker-free frequency shift on–off keying line coding modulation scheme was designed for the positioning system to ensure a constant modulated frequency. We tested the performance of the decoding accuracy with respect to vertical and horizontal distance, which utilizes a rolling shutter mechanism of a complementary metal-oxide-semiconductor image sensor. The experimental results of the proposed positioning system can provide centimeter-level accuracy with low computational time, rendering it a promising solution for the future direction of large-area indoor positioning systems.

scholarly journals Error Analysis on Indoor Localization with Visible Light Communication

2019 ◽  
Vol 11 (4) ◽  
pp. 427
Author(s):  
Jun Yan ◽  
Bingcheng Zhu ◽  
Liang Chen ◽  
Jin Wang ◽  
Jingbin Liu
Keyword(s):  
Visible Light ◽  
Indoor Localization ◽  
Smart Phone ◽  
Visible Light Communication ◽  
Indoor Positioning ◽  
Light Signal ◽  
Indoor Navigation ◽  
Angle Of Arrival ◽  
Light Emitting ◽  
Indoor Scenarios

Affected by the complexity of the indoor environment, accurate indoor positioning is challenging in many localization based services (LBS). Recently, it has been recognized that, visible light communication (VLC) is promising for indoor navigation and positioning, due to the low implementation cost with marginal modification to the existing infrastructure and the possibility to achieve high accurate positioning results. Provided that the positions of the light emitting diodes (LEDs) are known to the receiver, the angle of arrival (AOA) of the light signal is able to be estimated by a camera embedded in a smart phone, and thus the position of the smart phone can be derived based on the triangulation. In this paper, the performance of the positioning accuracy is analyzed based on indoor positioning with VLC, and the analytical upper bound of location error is derived. Extensive simulation results have verified the theoretical analysis on the VLC-based localization approach in different indoor scenarios. In order to obtain better location performance, the principles of choosing reference LED and localization LED are also given.

scholarly journals Accuracy Bounds for Array-Based Positioning in Dense Multipath Channels

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4249 ◽  
Author(s):  
Thomas Wilding ◽  
Stefan Grebien ◽  
Ulrich Mühlmann ◽  
Klaus Witrisal
Keyword(s):  
Error Bound ◽  
Antenna Arrays ◽  
Estimation Error ◽  
Position Estimation ◽  
Position Error ◽  
Time Of Arrival ◽  
Angle Of Arrival ◽  
Multipath Interference ◽  
Positioning Systems ◽  
Performance Loss

The accuracy of radio-based positioning systems will be limited by multipath interference in realistic application scenarios. This paper derives closed-form expressions for the Cramér–Rao lower bound (CRLB) on the achievable time-of-arrival (ToA) and angle-of-arrival (AoA) estimation-error variances, considering the presence of multipath radio channels, and extends these results to position estimation. The derivations are based on channel models comprising deterministic, specular multipath components as well as stochastic, diffuse/dense multipath. The derived CRLBs thus allow an evaluation of the influence of channel parameters, the geometric configuration of the environment, and system parameters such as signal bandwidth and array geometry. Our results quantify how the ToA and AoA accuracies decrease when the signal bandwidth is reduced, because more multipath will then interfere with the useful LoS component. Antenna arrays can (partly) compensate this performance loss, exploiting diversity among the multipath interference. For example, the AoA accuracy with a 16-element linear array at 1 MHz bandwidth is similar to a two-element array at 1 GHz , in the magnitude order of one degree. The ToA accuracy, on the other hand, still scales by a factor of 100 from the cm-regime to the m-regime because of the dominating influence of the signal bandwidth. The position error bound shows the relationship between the range and angle information under realistic indoor channel conditions and their different scaling behaviors as a function of the anchor–agent placement. Specular multipath components have a maximum detrimental influence near the walls. It is shown for an L-shaped room that a fairly even distribution of the position error bound can be achieved throughout the environment, using two anchors equipped with 2 × 2 -array antennas. The accuracy limit due to multipath increases from the 1–10-cm-range at 1 GHz bandwidth to the 0.5–1-m-range at 100 MHz .

scholarly journals In-Depth Analysis of Unmodulated Visible Light Positioning Using the Iterated Extended Kalman Filter

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5198 ◽  
Author(s):  
Robin Amsters ◽  
Eric Demeester ◽  
Nobby Stevens ◽  
Peter Slaets
Keyword(s):  
Kalman Filter ◽  
Visible Light ◽  
Autonomous Robots ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Light Sources ◽  
High Speeds ◽  
Depth Analysis ◽  
Update Rate ◽  
Temporary Occlusion

Indoor positioning with visible light has become increasingly important in recent years. Usually, light sources are modulated at high speeds in order to wirelessly transmit data from the fixtures to a receiver. The accuracy of such systems can range from a few decimeters to a few centimeters. However, additional modulation hardware is required for every light source, thereby increasing cost and system complexity. This paper investigates the use of unmodulated light for indoor positioning. Contrary to previous work, a Kalman filter is used instead of a particle filter to decrease the computational load. As a result, the update rate of position estimation can be higher. Additionally, more resources could be made available for other tasks (e.g., path planning for autonomous robots). We evaluated the performance of our proposed approach through simulations and experiments. The accuracy depends on a number of parameters, but is generally lower than 0.5 m. Moreover, temporary occlusion of the receiver can be compensated in most cases.

scholarly journals Algorithm for Dynamic Fingerprinting Radio Map Creation Using IMU Measurements

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2283
Author(s):  
Peter Brida ◽  
Juraj Machaj ◽  
Jan Racko ◽  
Ondrej Krejcar
Keyword(s):  
Dead Reckoning ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Reference Points ◽  
Location Based Services ◽  
Position Information ◽  
Vast Number ◽  
Positioning Systems ◽  
Time Required ◽  
Radio Map

While a vast number of location-based services appeared lately, indoor positioning solutions are developed to provide reliable position information in environments where traditionally used satellite-based positioning systems cannot provide access to accurate position estimates. Indoor positioning systems can be based on many technologies; however, radio networks and more precisely Wi-Fi networks seem to attract the attention of a majority of the research teams. The most widely used localization approach used in Wi-Fi-based systems is based on fingerprinting framework. Fingerprinting algorithms, however, require a radio map for position estimation. This paper will describe a solution for dynamic radio map creation, which is aimed to reduce the time required to build a radio map. The proposed solution is using measurements from IMUs (Inertial Measurement Units), which are processed with a particle filter dead reckoning algorithm. Reference points (RPs) generated by the implemented dead reckoning algorithm are then processed by the proposed reference point merging algorithm, in order to optimize the radio map size and merge similar RPs. The proposed solution was tested in a real-world environment and evaluated by the implementation of deterministic fingerprinting positioning algorithms, and the achieved results were compared with results achieved with a static radio map. The achieved results presented in the paper show that positioning algorithms achieved similar accuracy even with a dynamic map with a low density of reference points.

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