An Efficient Position Estimation of Indoor Positioning System Based on Dynamic Time Warping

2020 ◽  
Vol 9 (1.2) ◽  
pp. 17-20
Author(s):  
Rhowel M. Dellosa
Keyword(s):  
Dynamic Time Warping ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Positioning System ◽  
Time Warping ◽  
Dynamic Time ◽  
Indoor Positioning System

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 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 Indoor Positioning System Based on Global Positioning System Signals with Down- and Up-Converters in 433 MHz ISM Band

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4338
Author(s):  
Abdulkadir Uzun ◽  
Firas Abdul Ghani ◽  
Amir Mohsen Ahmadi Najafabadi ◽  
Hüsnü Yenigün ◽  
İbrahim Tekin
Keyword(s):  
Global Positioning System ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Line Of Sight ◽  
Positioning System ◽  
Gps Receiver ◽  
Ism Band ◽  
Global Positioning ◽  
Indoor Positioning System ◽  
Non Line Of Sight

In this paper, an indoor positioning system using Global Positioning System (GPS) signals in the 433 MHz Industrial Scientific Medical (ISM) band is proposed, and an experimental demonstration of how the proposed system operates under both line-of-sight and non-line-of-sight conditions on a building floor is presented. The proposed method is based on down-converting (DC) repeaters and an up-converting (UC) receiver. The down-conversion is deployed to avoid the restrictions on the use of Global Navigation Satellite Systems (GNSS) repeaters, to achieve higher output power, and to expose the GPS signals to lower path loss. The repeaters receive outdoor GPS signals at 1575.42 MHz (L1 band), down-convert them to the 433 MHz ISM band, then amplify and retransmit them to the indoor environment. The front end up-converter is combined with an off-the-shelf GPS receiver. When GPS signals at 433 MHz are received by the up-converting receiver, it then amplifies and up-converts these signals back to the L1 frequency. Subsequently, the off-the-shelf GPS receiver calculates the pseudo-ranges. The raw data are then sent from the receiver over a 2.4 GHz Wi-Fi link to a remote computer for data processing and indoor position estimation. Each repeater also has an attenuator to adjust its amplification level so that each repeater transmits almost equal signal levels in order to prevent jamming of the off-the-shelf GPS receiver. Experimental results demonstrate that the indoor position of a receiver can be found with sub-meter accuracy under both line-of-sight and non-line-of-sight conditions. The estimated position was found to be 54 and 98 cm away from the real position, while the 50% circular error probable (CEP) of the collected samples showed a radius of 3.3 and 4 m, respectively, for line-of-sight and non-line-of-sight cases.

Speech Recognition for Endoscopic Automatic Positioning System

2012 ◽  
Vol 588-589 ◽  
pp. 1296-1299
Author(s):  
Ning Ma ◽  
Xiao Dong Chen ◽  
Ya Nan Li ◽  
Qing Yun Yin ◽  
Yi Wang ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Embedded System ◽  
Dynamic Time Warping ◽  
Recognition Rate ◽  
Positioning System ◽  
Time Warping ◽  
Embedded Platform ◽  
Speech Recognition Engine ◽  
Dynamic Time ◽  
Automatic Positioning

A novel system for minimally invasive surgery is presented in this paper. The system utilized an Endoscopic Automatic Positioner (EAP) controlled by Speech Recognition Engine to implement the clamping and dynamically positioning of the laparoscope. The motion instructions of the EAP are transformed from voice commands of specific doctor recognized by an improved algorithm named Normalized Average- Dynamic Time Warping (NA-DTW). An embedded platform based on ARM is designed to run the NA-DTW on Windows CE operating system. 1250 groups of experiments from 10 individual speakers demonstrate the performance of DTW. Compared with traditional algorithms, the enhanced algorithm improves the recognition rate from 96.6% to 99.76% and shortens the time of calculation by 51%. The results demonstrate the enhanced algorithm being effective and can satisfy the real time requirement in embedded system.

scholarly journals Monte Carlo-Based Indoor RFID Positioning with Dual-Antenna Joint Rectification

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1548
Author(s):  
Yonghui Tao ◽  
Lujie Wu ◽  
Johan Sidén ◽  
Gang Wang
Keyword(s):  
Monte Carlo ◽  
Radio Frequency Identification ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Rfid Tags ◽  
Positioning System ◽  
Time Step ◽  
Position Information ◽  
Reader Antenna ◽  
Indoor Positioning System

A novel Monte Carlo-based indoor radio-frequency identification (RFID) positioning scheme is proposed for dual-antenna RFID systems with the cooperation of dual-antenna joint rectification. By deploying reference passive RFID tags on the ground to establish an RFID tag-based map, indoor self-positioning of a moving platform carrying an RFID reader with two forward-looking antennas can be simply implemented by looking up the positions of responded RFID tags at each time step of movement, and estimating the platform position by using the proposed Monte Carlo-based algorithm. To improve the positioning accuracy of Monte Carlo-based positioning, each antenna channel, with its own footprint on the ground, may rectify its position estimation by using the tag position information interrogated by the other antenna channel. The algorithm for dual-antenna rectification is proposed. The performance of the proposed Monte Carlo-based self-positioning scheme is demonstrated by both simulation and experiment tests. Some factors in a practical indoor-positioning system, such as the reference tag distribution pattern, reader antenna footprint size, and footprint overlap, are discussed. Some guide rules for deploying the RFID indoor-positioning system are also reported.

scholarly journals EVALUATION OF DYNAMIC AD-HOC UWB INDOOR POSITIONING SYSTEM

2018 ◽  
Vol XLII-1 ◽  
pp. 379-385 ◽  
Author(s):  
M. Sakr ◽  
A. Masiero ◽  
N. El-Sheimy
Keyword(s):  
Ad Hoc ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Ultra Wideband ◽  
Positioning System ◽  
Range Measurements ◽  
Precision Time ◽  
Anchor Points ◽  
Positioning Algorithm ◽  
Indoor Positioning System

<p><strong>Abstract.</strong> Ultra-wideband (UWB) technology has witnessed tremendous development and advancement in the past few years. Currently available UWB transceivers can provide high-precision time-of-flight measurements which corresponds to range measurements with theoretical accuracy of few centimetres. Position estimation using range measurement is determined by measuring the ranges from a rover or a dynamic node, to a set of anchor points with known positions. However, building a flexible and accurate indoor positioning system requires more than just accurate range measurements. The performance of indoor positioning system is affected by the number and the configuration of the anchor points used, along with the accuracy of the anchor positions.</p><p>This paper introduces LocSpeck, a dynamic ad-hoc positioning system based on the DW1000 UWB transceiver from Decawave. LocSpeck is composed of a set of identical nodes communicating on a common RF channel, forming a fully or partially connected network where the positioning algorithm run on each node. Each LocSpeck node could act as an anchor or a rover, and the role could change dynamically during the same session. The number of nodes in the network could change dynamically, since the firmware of LocSpeck supports adding and removing nodes on-the-fly. The paper compares the performance of the LocSpeck system with commercially available off-the-shelf UWB positioning system. Different operating scenarios are considered when evaluating the performance of the system, including cases where collaboration between the two systems is considered.</p>

scholarly journals Modified fingerprinting localization technique of indoor positioning system based on coordinates

2019 ◽  
Vol 15 (3) ◽  
pp. 1345
Author(s):  
Rhowel M. Dellosa ◽  
Arnel C. Fajardo ◽  
Ruji P. Medina
Keyword(s):  
Radio Frequency ◽  
Long Range ◽  
Indoor Environment ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Location Estimation ◽  
Positioning System ◽  
Negative Effects ◽  
Localization Technique ◽  
Indoor Positioning System

<span>The fingerprinting localization technique is the most commonly used localization technique of the indoor positioning system. It is used by several technologies for short and long range position estimation like wireless fidelity and radio frequency. There are several schemes used to estimate a location for the indoor environment but the drawbacks resulted in complexity issues. These drawbacks have negative effects on location estimation. In order to address these drawbacks, this work attempted to explore the fingerprinting localization technique for location estimation of the indoor environment that focuses on position estimation. Results showed that the simplicity of the design of position estimation without compromising the functionality of the operations was observed with 100% accuracy on position estimation.</span>

scholarly journals Eksperimen Pengenalan Wajah dengan fitur Indoor Positioning System menggunakan Algoritma CNN

2020 ◽  
Vol 22 (2) ◽  
pp. 109-116
Author(s):  
Yessi Hartiwi ◽  
Errissya Rasywir ◽  
Yovi Pratama ◽  
Pareza Alam Jusia
Keyword(s):  
Deep Learning ◽  
Learning Algorithm ◽  
Facial Recognition ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Positioning System ◽  
Deep Learning Algorithm ◽  
Position Detection ◽  
The Face ◽  
Indoor Positioning System

Facial recognition work combined with the facial owner's position estimation feature can be utilized in various everyday applications such as face attendance with position detection. Based on this, this study offers a system testing experiment that can be run with facial recognition features and an Indoor Positioning System (IPS) to automatically check the location of the owner of the face. Recently, deep learning algorithms are the most popular method in the world of artificial intelligence. Currently, the Deep Learning algorithm toolbox has provided various programming language platforms. Departing from research findings related to deep learning, this study utilizes this method to perform facial recognition. The system we offer is also capable of checking the position or whereabouts of objects using Indoor Positioning System (IPS) technology. Facial recognition evaluation using CNN obtained a maximum value = 92.89% and an accuracy error value of 7.11%. Meanwhile, the average accuracy obtained is 91.86%. In the evaluation of the estimated position tested using DNN, the highest value of r2 score is 0.934, the lowest is 0.930 and an average is 0.932 and the highest value is MSE is 4.578, the lowest is 4.366 and the average is 4.475. This shows that the facial recognition process that is tested is able to produce good values but not the position estimation process. Keywords: Face Recognition, IPS, CNN, MSE, Accuraccy.

Sign in / Sign up

Export Citation Format

Share Document