scholarly journals Analysis and Improvement of Indoor Positioning Accuracy for UWB Sensors

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5731
Author(s):  
Leehter Yao ◽  
Lei Yao ◽  
Yeong-Wei Wu
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Indoor Positioning ◽  
Mobile Node ◽  
Ultra Wideband ◽  
Positioning Accuracy ◽  
3 Dimensional ◽  
Positioning Errors ◽  
3D Positioning ◽  
2D And 3D

Ultra-wideband (UWB) sensors have been widely applied to indoor positioning. The indoor positioning of UWB sensors usually refers to the positioning of the mobile node that interacts with the anchors through radio for calculating the distance between the mobile node and each of the surrounding anchors. The positioning accuracy of the mobile node is affected by the installation positions of surrounding anchors. A mathematical model was proposed in this paper to respectively analyze the mobile node’s 2-dimensional (2D) and 3-dimensional (3D) positioning errors. The factors influencing the mobile node’s positioning errors were explored through the mathematical models. The best installation positions of surrounding anchors were obtained based on the mathematical models. The mobile node’s 2D and 3D positioning errors were reduced based on the anchor positions derived from the mathematical model. Both computer simulations and practical experiments were implemented to justify the results obtained in the mathematical models.

scholarly journals Optical Boundaries for LED-Based Indoor Positioning System

Computation ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 7 ◽  
Author(s):  
Olaoluwa Popoola ◽  
Sinan Sinanović ◽  
Wasiu Popoola ◽  
Roberto Ramirez-Iniguez
Keyword(s):  
Mathematical Model ◽  
Indoor Positioning ◽  
Experimental Measurements ◽  
Positioning System ◽  
Positioning Error ◽  
Positioning Accuracy ◽  
Light Emitting ◽  
Positioning Systems ◽  
Indoor Positioning System ◽  
Positioning Time

Overlap of footprints of light emitting diodes (LEDs) increases the positioning accuracy of wearable LED indoor positioning systems (IPS) but such an approach assumes that the footprint boundaries are defined. In this work, we develop a mathematical model for defining the footprint boundaries of an LED in terms of a threshold angle instead of the conventional half or full angle. To show the effect of the threshold angle, we compare how overlaps and receiver tilts affect the performance of an LED-based IPS when the optical boundary is defined at the threshold angle and at the full angle. Using experimental measurements, simulations, and theoretical analysis, the effect of the defined threshold angle is estimated. The results show that the positional time when using the newly defined threshold angle is 12 times shorter than the time when the full angle is used. When the effect of tilt is considered, the threshold angle time is 22 times shorter than the full angle positioning time. Regarding accuracy, it is shown in this work that a positioning error as low as 230 mm can be obtained. Consequently, while the IPS gives a very low positioning error, a defined threshold angle reduces delays in an overlap-based LED IPS.

scholarly journals A Hybrid Dead Reckon System Based on 3-Dimensional Dynamic Time Warping

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 185 ◽  
Author(s):  
Jian Chen ◽  
Gang Ou ◽  
Ao Peng ◽  
Lingxiang Zheng ◽  
Jianghong Shi
Keyword(s):  
Magnetic Field ◽  
Dynamic Time Warping ◽  
Weighted Least Squares ◽  
Dead Reckoning ◽  
Step Length ◽  
Indoor Positioning ◽  
Time Warping ◽  
Positioning Accuracy ◽  
3 Dimensional ◽  
Dynamic Time

In recent years, using smartphones for indoor positioning has become increasingly popular with consumers. This paper presents an integrated localization technique for inertial and magnetic field sensors to challenge indoor positioning without Wi-Fi signals. For dead-reckoning (DR), attitude angle estimation, step length calculation, and step counting estimation are introduced. Dynamic time warping (DTW) usually calculates the distance between the measured magnetic field and magnetic fingerprint in the database. For DR/Magnetic matching (MM), we creatively propose 3-dimensional dynamic time warping (3DDTW) to calculate the distance. Unlike traditional DTW, 3DDTW extends the original one-dimensional signal to a two-dimensional signal. Finally, the weighted least squares further improves indoor positioning accuracy. In the three different experimental scenarios—teaching building, study room, office building—DR/MM hybrid positioning accuracy is about 3.34 m.

scholarly journals Application of LSTM Network to Improve Indoor Positioning Accuracy

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5824
Author(s):  
Dongqi Gao ◽  
Xiangye Zeng ◽  
Jingyi Wang ◽  
Yanmang Su
Keyword(s):  
Short Term Memory ◽  
Indoor Positioning ◽  
Base Stations ◽  
Ultra Wideband ◽  
Positioning Accuracy ◽  
Last Mile ◽  
Ranging Error ◽  
Positioning Method ◽  
Lstm Network ◽  
Positioning Algorithm

Various indoor positioning methods have been developed to solve the “last mile on Earth”. Ultra-wideband positioning technology stands out among all indoor positioning methods due to its unique communication mechanism and has a broad application prospect. Under non-line-of-sight (NLOS) conditions, the accuracy of this positioning method is greatly affected. Unlike traditional inspection and rejection of NLOS signals, all base stations are involved in positioning to improve positioning accuracy. In this paper, a Long Short-Term Memory (LSTM) network is used while maximizing the use of positioning equipment. The LSTM network is applied to process the raw Channel Impulse Response (CIR) to calculate the ranging error, and combined with the improved positioning algorithm to improve the positioning accuracy. It has been verified that the accuracy of the predicted ranging error is up to centimeter level. Using this prediction for the positioning algorithm, the average positioning accuracy improved by about 62%.

scholarly journals A high-accuracy indoor positioning system based on UWB

2018 ◽  
Vol 173 ◽  
pp. 01021
Author(s):  
Hanyu Liu ◽  
Yanhan Zeng ◽  
Ruguo Li ◽  
Huajie Huang
Keyword(s):  
Indoor Positioning ◽  
Mobile Node ◽  
High Accuracy ◽  
Base Stations ◽  
Ultra Wideband ◽  
Time Of Arrival ◽  
Positioning System ◽  
Wide Range ◽  
Fixed Base ◽  
Indoor Positioning System

In this paper, a high-accuracy indoor positioning system based on the ultra-wideband (UWB) technique is proposed. The proposed system uses a simple ranging process to obtain the distance between the mobile node and the fixed base stations. Besides, an improved time of arrival (ToA) algorithm with Kalman filtering is proposed to improve the positioning accuracy. Measurements have been performed in the real indoor 13m*7.6m environment with many obstacles and the root-mean-square error (RMSE) is less than 0.3m. The proposed system offers a wide range of application in robotics, industrial automation, post-sorting system and so on.

scholarly journals Improving the Accuracy of Estimates of Indoor Distance Moved Using Deep Learning-Based Movement Status Recognition

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 346
Author(s):  
Zhenjie Ma ◽  
Wenjun Zhang ◽  
Ke Shi
Keyword(s):  
Deep Learning ◽  
Indoor Positioning ◽  
Ultra Wideband ◽  
Indoor Environments ◽  
Job Allocation ◽  
The Real ◽  
Positioning Errors ◽  
Wireless Signal ◽  
Movement Distance ◽  
Status Recognition

As a result of the development of wireless indoor positioning techniques such as WiFi, Bluetooth, and Ultra-wideband (UWB), the positioning traces of moving people or objects in indoor environments can be tracked and recorded, and the distances moved can be estimated from these data traces. These estimates are very useful in many applications such as workload statistics and optimized job allocation in the field of logistics. However, due to the uncertainties of the wireless signal and corresponding positioning errors, accurately estimating movement distance still faces challenges. To address this issue, this paper proposes a movement status recognition-based distance estimating method to improve the accuracy. We divide the positioning traces into segments and use an encoder–decoder deep learning-based model to determine the motion status of each segment. Then, the distances of these segments are calculated by different distance estimating methods based on their movement statuses. The experiments on the real positioning traces demonstrate the proposed method can precisely identify the movement status and significantly improve the distance estimating accuracy.

scholarly journals A Method for Improving UWB Indoor Positioning

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Zhanjun Hao ◽  
Beibei Li ◽  
Xiaochao Dang
Keyword(s):  
Estimation Method ◽  
Pulse Amplitude ◽  
Relative Displacement ◽  
Indoor Positioning ◽  
Base Stations ◽  
Ultra Wideband ◽  
Signal Interference ◽  
Positioning Errors ◽  
Wireless Environment ◽  
The Time Domain

The existing positioning methods that use received signal strength indication (RSSI) and channel state information (CSI) may suffer from multipath and shadowing in a complex wireless environment, which can result in more positioning errors. This paper proposes a method for accurate multilabel positioning in the non-line-of-sight (NLOS) environment. First, the position is roughly estimated using the orthogonal variable spreading factor (OVSF-TH) algorithm, which can automatically match the signal interference. The ultra-wideband (UWB) spectral density and pulse amplitude in the time domain are used to determine the direction of the label and enhance estimation of the mobile label direction. Then, the location of the tag is obtained by triangulation, and a coordinate-based coordinate estimation method is proposed to calculate the relative displacement of multiple tags to determine the label position. Finally, by setting up a real experimental environment, the influence of the number of base stations on the accuracy and the performance of the localization method under different circumstances are analyzed. The theoretical analysis and experimental results show that the method is simple to deploy, inexpensive, and very accurate in terms of positioning, having a clearly effective indoor positioning accuracy. Compared with other existing positioning methods, this method can achieve more accurate positioning. Moreover, it has important theoretical and practical applicability because of the reliability and accuracy of indoor positioning in an NLOS environment.

scholarly journals Comparison of 2D and 3D Models of Salinity Numerical Simulation

2015 ◽  
Vol 22 (s1) ◽  
pp. 26-29
Author(s):  
Li Chunhui ◽  
Pan Xishan ◽  
Ke Jie ◽  
Dong Xiaotian
Keyword(s):  
Numerical Simulation ◽  
Mathematical Model ◽  
Mathematical Models ◽  
3D Models ◽  
Seawater Desalination ◽  
Salinity Distribution ◽  
Before And After ◽  
Hydrodynamic Environment ◽  
2D And 3D ◽  
Important Significance

Abstract For the study of the effect of 2D and 3D mathematical model in salinity simulation, with Liuheng island strong brine discharge of seawater desalination project as an example, using 2D and 3D salinity mathematical models of Liuheng island to simulate coastal hydrodynamic environment and salinity distribution before and after the concentrated brine discharge, and analyzed the results. Finally got the applicable scope of the two models, it has an important significance in the study of similar problems.

scholarly journals Integrated IMU with Faster R-CNN Aided Visual Measurements from IP Cameras for Indoor Positioning

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3134 ◽  
Author(s):  
Lin Zhang ◽  
Taoyun Zhou ◽  
Baowang Lian
Keyword(s):  
Indoor Positioning ◽  
Ultra Wideband ◽  
Measurement Unit ◽  
Indoor Environments ◽  
Inertial Measurement ◽  
Positioning Errors ◽  
Measurement Units ◽  
Stationary Obstacles ◽  
Indoor Scenarios ◽  
Visual Measurements

Considering the radio-based indoor positioning system pertaining to signal degradation due to the environmental factors, and rising popularity of IP (Internet Protocol) cameras in cities, a novel fusion of inertial measurement units (IMUs) with external IP cameras to determine the positions of moving users in indoor environments is presented. This approach uses a fine-tuned Faster R-CNN (Region Convolutional Neural Network) to detect users in images captured by cameras, and acquires visual measurements including ranges and angles of users with respect to the cameras based on the proposed monocular vision relatively measuring (MVRM) method. The results are determined by integrating the positions predicted by each user’s inertial measurement unit (IMU) and visual measurements using an EKF (Extended Kalman Filter). The results experimentally show that the ranging accuracy is affected by both the detected bounding box’s by Faster R-CNN height errors and diverse measuring distances, however, the heading accuracy is solely interfered with bounding box’s horizontal biases. The indoor obstacles including stationary obstacles and a pedestrian in our tests more significantly decrease the accuracy of ranging than that of heading, and the effect of a pedestrian on the heading errors is greater than stationary obstacles on that. We implemented a positioning test for a single user and an external camera in five indoor scenarios to evaluate the performance. The robust fused IMU/MVRM solution significantly decreases the positioning errors and shows better performance in dense multipath scenarios compared with the pure MVRM solution and ultra-wideband (UWB) solution.

A mathematical model and an algorithm for sampling sets of components on the Assembly enterprises of space technology

2018 ◽  
Vol 15 (1) ◽  
pp. 39-55
Author(s):  
V. B. Rudakov ◽  
V. M. Makarov ◽  
M. I. Makarov
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Space Technology ◽  
Economic Costs ◽  
Problem Statement ◽  
Optimal Plan ◽  
Product Mix ◽  
Technical Parameters ◽  
Complex Products ◽  
Assembly Plants

The article considers the problem of determining the rational plans of the input sampling reliability and technical parameters of components of space technology, the totality of which is supplied to the Assembly plants for the manufacture of complex products of space technology. Problem statement and mathematical model based on the minimization of the economic costs of control and losses related to the risks of taking wrong decisions, are given in the article. The properties of the mathematical models are investigated, the algorithm for its optimization is developed. The result is an optimal plan for the sampling of sets of components, which includes: an optimal product mix subject to mandatory control of the aggregate and optimum risks of first and second kind, when acceptance number of statistical plan is zero. The latter circumstance is due to the high requirements of reliability and technical parameters of products of space technology.

scholarly journals High-Precision RTT-Based Indoor Positioning System Using RCDN and RPN

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3701
Author(s):  
Ju-Hyeon Seong ◽  
Soo-Hwan Lee ◽  
Won-Yeol Kim ◽  
Dong-Hoan Seo
Keyword(s):  
High Precision ◽  
Distance Estimation ◽  
Sampling Period ◽  
Multipath Fading ◽  
Indoor Positioning ◽  
Positioning System ◽  
Positioning Systems ◽  
Positioning Errors ◽  
Location Determination ◽  
Indoor Positioning System

Wi-Fi round-trip timing (RTT) was applied to indoor positioning systems based on distance estimation. RTT has a higher reception instability than the received signal strength indicator (RSSI)-based fingerprint in non-line-of-sight (NLOS) environments with many obstacles, resulting in large positioning errors due to multipath fading. To solve these problems, in this paper, we propose high-precision RTT-based indoor positioning system using an RTT compensation distance network (RCDN) and a region proposal network (RPN). The proposed method consists of a CNN-based RCDN for improving the prediction accuracy and learning rate of the received distances and a recurrent neural network-based RPN for real-time positioning, implemented in an end-to-end manner. The proposed RCDN collects and corrects a stable and reliable distance prediction value from each RTT transmitter by applying a scanning step to increase the reception rate of the TOF-based RTT with unstable reception. In addition, the user location is derived using the fingerprint-based location determination method through the RPN in which division processing is applied to the distances of the RTT corrected in the RCDN using the characteristics of the fast-sampling period.

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