scholarly journals A Frequency Domain Direct Localization Method Based on Distributed Antenna Sensing

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Gaofeng Zhao ◽  
Hao Zheng ◽  
Yingying Li ◽  
Kehui Zhu ◽  
Jianfeng Li
Keyword(s):  
Frequency Domain ◽  
Original Data ◽  
Time Of Arrival ◽  
Positioning Accuracy ◽  
Localization Accuracy ◽  
Error Accumulation ◽  
Direct Localization ◽  
The Cost ◽  
Passive Localization ◽  
Monitoring Area

Traditional two-step passive localization methods need to extract the parameters like the direction of arrival (DOA), time of arrival (TOA), and time difference of arrival (TDOA) from the original data to determine the source position, which causes the poor positioning accuracy due to error accumulation. In this paper, a direct position determination (DPD) method is proposed to improve the positioning accuracy and robustness, which is based on a correlation algorithm. Firstly, the cost function directly related to the location of the source can be established by synthesizing the data received by multiantenna in the frequency domain. Then, the position of the source is estimated by the correlation DPD method to search the monitoring area. Compared to the improved TDOA algorithm and Least Squares DPD algorithm, the proposed method shows better localization accuracy of different SNRs. Finally, based on real measured data, it can be seen that the results of the proposed algorithm are better than the improved TDOA algorithm.

scholarly journals Embedding Undersampling Rotation Forest for Imbalanced Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Huaping Guo ◽  
Xiaoyu Diao ◽  
Hongbing Liu
Keyword(s):  
Imbalanced Data ◽  
Feature Space ◽  
Original Data ◽  
Training Set ◽  
Data Set ◽  
Minority Class ◽  
Rotation Forest ◽  
Novel Method ◽  
Individual Classifier ◽  
The Cost

Rotation Forest is an ensemble learning approach achieving better performance comparing to Bagging and Boosting through building accurate and diverse classifiers using rotated feature space. However, like other conventional classifiers, Rotation Forest does not work well on the imbalanced data which are characterized as having much less examples of one class (minority class) than the other (majority class), and the cost of misclassifying minority class examples is often much more expensive than the contrary cases. This paper proposes a novel method called Embedding Undersampling Rotation Forest (EURF) to handle this problem (1) sampling subsets from the majority class and learning a projection matrix from each subset and (2) obtaining training sets by projecting re-undersampling subsets of the original data set to new spaces defined by the matrices and constructing an individual classifier from each training set. For the first method, undersampling is to force the rotation matrix to better capture the features of the minority class without harming the diversity between individual classifiers. With respect to the second method, the undersampling technique aims to improve the performance of individual classifiers on the minority class. The experimental results show that EURF achieves significantly better performance comparing to other state-of-the-art methods.

Teaching the Hardy-Weinberg Equilibrium: A 5E Lesson Plan

2017 ◽  
Vol 79 (4) ◽  
pp. 288-293
Author(s):  
Mike U. Smith
Keyword(s):  
Young People ◽  
Lesson Plan ◽  
Original Data ◽  
Good Teaching ◽  
Weinberg Equilibrium ◽  
Hardy Weinberg Equilibrium ◽  
Basic Concepts ◽  
The Cost

In an earlier paper (Smith & Baldwin, 2015), we explained the basic concepts of the Hardy-Weinberg equilibrium (HWeq) principle needed for meaningful understanding and for good teaching, emphasizing distinctions that are sometimes ignored at the cost of coherent understanding, and identifying nine shortcomings of most available Hardy-Weinberg activities and problem sets. In the present paper, we provide a 5E lesson plan based on that analysis and designed to avoid the shortcomings identified, including providing original data and focusing on understanding and topics that are interesting and meaningful to young people.

scholarly journals Research on Indoor Positioning Algorithm of Single Reader Based on Gated Recurrent Unit

2021 ◽  
pp. 1-10
Author(s):  
Jintao Tang ◽  
Lvqing Yang ◽  
Jiangsheng Zhao ◽  
Yishu Qiu ◽  
Yihui Deng
Keyword(s):  
Internet Of Things ◽  
Radio Frequency Identification ◽  
Indoor Positioning ◽  
The Internet ◽  
Positioning Accuracy ◽  
Frequency Identification ◽  
The Cost ◽  
Positioning Algorithm ◽  
Gated Recurrent Unit ◽  
The Internet Of Things

With the development of the Internet of Things and Radio Frequency Identification (RFID), indoor positioning technology as an important part of positioning technology, has been attracting much attention in recent years. In order to solve the problems of low precision, high cost and signal collision between readers, a new indoor positioning algorithm based on a single RFID reader combined with a Double-order Gated Recurrent Unit (GRU) are proposed in this paper. Firstly, the reader is moved along the specified direction to collect the sequential tag data. Then, the tag’s coordinate is taken as the target value to train models and compare them with existing algorithms. Finally, the best Gated Recurrent Unit positioning model is used to estimate the position of the tags. Experiment results show that the proposed algorithm can effectively improve positioning accuracy, reduce the number of readers, cut down the cost and eliminate the collisions of reader signals.

Reducing Tracking Error in RFID Real-Time Localization Systems Using Kalman Filters

2014 ◽  
Vol 5 (3) ◽  
pp. 1-24
Author(s):  
Benjamin Sanda ◽  
Ikhlas Abdel-Qader ◽  
Abiola Akanmu
Keyword(s):  
Real Time ◽  
Radio Frequency Identification ◽  
Kalman Filters ◽  
Tracking Error ◽  
Time Of Arrival ◽  
Indoor Environments ◽  
Real World Data ◽  
Localization Accuracy ◽  
Accurate Localization ◽  
Localization Systems

The use of Radio Frequency Identification (RFID) has become widespread in industry as a means to quickly and wirelessly identify and track packages and equipment. Now there is a commercial interest in using RFID to provide real-time localization. Efforts to use RFID technology in this way experience localization errors due to noise and multipath effects inherent to these environments. This paper presents the use of both linear Kalman filters and non-linear Unscented Kalman filters to reduce the error rate inherent to real-time RFID localization systems and provide more accurate localization results in indoor environments. A commercial RFID localization system designed for use by the construction industry is used in this work, and a filtering model based on 3rd order motion is developed. The filtering model is tested with real-world data and shown to provide an increase in localization accuracy when applied to both raw time of arrival measurements as well as final localization results.

scholarly journals A Loose-Coupled Fusion of Inertial and UWB Assisted by a Decision-Making Algorithm for Localization of Emergency Responders

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1463 ◽  
Author(s):  
André G. Ferreira ◽  
Duarte Fernandes ◽  
André P. Catarino ◽  
Ana M. Rocha ◽  
João L. Monteiro
Keyword(s):  
Decision Making ◽  
Indoor Localization ◽  
Dead Reckoning ◽  
Time Of Arrival ◽  
Robust Solution ◽  
Localization Accuracy ◽  
Positioning Systems ◽  
Emergency Responders ◽  
Pedestrian Dead Reckoning ◽  
Non Line Of Sight

Combining different technologies is gaining significant popularity among researchers and industry for the development of indoor positioning systems (IPSs). These hybrid IPSs emerge as a robust solution for indoor localization as the drawbacks of each technology can be mitigated or even eliminated by using complementary technologies. However, fusing position estimates from different technologies is still very challenging and, therefore, a hot research topic. In this work, we pose fusing the ultrawideband (UWB) position estimates with the estimates provided by a pedestrian dead reckoning (PDR) by using a Kalman filter. To improve the IPS accuracy, a decision-making algorithm was developed that aims to assess the usability of UWB measurements based on the identification of non-line-of-sight (NLOS) conditions. Three different data fusion algorithms are tested, based on three different time-of-arrival positioning algorithms, and experimental results show a localization accuracy of below 1.5 m for a 99th percentile.

scholarly journals Improving Accuracy and Reliability of Bluetooth Low-Energy-Based Localization Systems Using Proximity Sensors

2019 ◽  
Vol 9 (19) ◽  
pp. 4081 ◽  
Author(s):  
Marcin Kolakowski
Keyword(s):  
Assisted Living ◽  
Experimental Studies ◽  
Low Energy ◽  
Elderly Persons ◽  
Bluetooth Low Energy ◽  
Localization Accuracy ◽  
Hybrid Positioning ◽  
Improving Accuracy ◽  
The Cost ◽  
Localization Systems

One of the functionalities which are desired in Ambient and Assisted Living systems is accurate user localization at their living place. One of the best-suited solutions for this purpose from the cost and energy efficiency points of view are Bluetooth Low Energy (BLE)-based localization systems. Unfortunately, their localization accuracy is typically around several meters and might not be sufficient for detection of abnormal situations in elderly persons behavior. In this paper, a concept of a hybrid positioning system combining typical BLE-based infrastructure and proximity sensors is presented. The proximity sensors act a supporting role by additionally covering vital places, where higher localization accuracy is needed. The results from both parts are fused using two types of hybrid algorithms. The paper contains results of simulation and experimental studies. During the experiment, an exemplary proximity sensor VL53L1X has been tested and its basic properties modeled for use in the proposed algorithms. The results of the study have shown that employing proximity sensors can significantly improve localization accuracy in places of interest.

scholarly journals Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Boming Song ◽  
Shen Zhang ◽  
Jia Long ◽  
Qingsong Hu
Keyword(s):  
Particle Filtering ◽  
Production Efficiency ◽  
Access Point ◽  
Mine Safety ◽  
Manhattan Distance ◽  
Time Of Arrival ◽  
Localization Accuracy ◽  
Safety Production ◽  
Localization Signal ◽  
Localization Performance

Accurate target localization technology plays a very important role in ensuring mine safety production and higher production efficiency. The localization accuracy of a mine localization system is influenced by many factors. The most significant factor is the non-line of sight (NLOS) propagation error of the localization signal between the access point (AP) and the target node (Tag). In order to improve positioning accuracy, the NLOS error must be suppressed by an optimization algorithm. However, the traditional optimization algorithms are complex and exhibit poor optimization performance. To solve this problem, this paper proposes a new method for mine time of arrival (TOA) localization based on the idea of comprehensive optimization. The proposed method utilizes particle filtering to reduce the TOA data error, and the positioning results are further optimized with fingerprinting based on the Manhattan distance. This proposed method combines the advantages of particle filtering and fingerprinting localization. It reduces algorithm complexity and has better error suppression performance. The experimental results demonstrate that, as compared to the symmetric double-sided two-way ranging (SDS-TWR) method or received signal strength indication (RSSI) based fingerprinting method, the proposed method has a significantly improved localization performance, and the environment adaptability is enhanced.

scholarly journals Multitarget Direct Localization Using Block Sparse Bayesian Learning in Distributed MIMO Radar

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Bin Sun ◽  
Haowen Chen ◽  
Xizhang Wei ◽  
Xiang Li
Keyword(s):  
Sparse Representation ◽  
Bayesian Learning ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Sparse Bayesian Learning ◽  
Localization Accuracy ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Direct Localization ◽  
Correct Target

The target localization in distributed multiple-input multiple-output (MIMO) radar is a problem of great interest. This problem becomes more complicated for the case of multitarget where the measurement should be associated with the correct target. Sparse representation has been demonstrated to be a powerful framework for direct position determination (DPD) algorithms which avoid the association process. In this paper, we explore a novel sparsity-based DPD method to locate multiple targets using distributed MIMO radar. Since the sparse representation coefficients exhibit block sparsity, we use a block sparse Bayesian learning (BSBL) method to estimate the locations of multitarget, which has many advantages over existing block sparse model based algorithms. Experimental results illustrate that DPD using BSBL can achieve better localization accuracy and higher robustness against block coherence and compressed sensing (CS) than popular algorithms in most cases especially for dense targets case.

scholarly journals A collection of magnetic structures with cif-like files as a database seed

2014 ◽  
Vol 70 (a1) ◽  
pp. C1369-C1369
Author(s):  
Samuel Gallego ◽  
J. Manuel Perez-Mato ◽  
Emre Tasci ◽  
Luis Elcoro ◽  
Mois Aroyo ◽  
...  
Keyword(s):  
Magnetic Moments ◽  
Parent Phase ◽  
Point Group ◽  
Original Data ◽  
Quantitative Information ◽  
Isotropy Subgroup ◽  
Magnetic Structures ◽  
Structure Description ◽  
Magnetic Symmetry ◽  
The Cost

We report the release within the Bilbao Crystallographic server [1] of a webpage providing detailed quantitative information on a representative set of published magnetic structures. Under the name of MAGNDATA (www.cryst.ehu.es/magndata) more than 140 entries are available. Each magnetic structure has been saved making use of magnetic symmetry, i.e. Shubnikov magnetic groups for commensurate structures, and magnetic superspace groups for incommensurate ones. This ensures a unified communication method and a robust and unambiguous description of both atomic positions and magnetic moments. The origin and main crystallographic axes of the parent phase are usually kept, with the cost of often using a non-standard setting for the magnetic symmetry. The magnetic point group is also given, so that the allowed macroscopic tensor properties can be derived. The fact that magnetic structures are being described according to various methods, often with ambiguous information, has forced an elaborate interpretation and transformation of the original data. For this purpose the freely available internet tools MAXMAGN [1] and ISODISTORT [2] have been our essential tools. Most of the analyzed structures happen to possess maximal magnetic symmetries within the constraints imposed by the magnetic propagation vector, and the relevant model could be derived in a straightforward manner using MAXMAGN [1]. In a few cases a lower symmetry is realized, but then it corresponded to one isotropy subgroup of one or several irreducible representations (irreps) of the paramagnetic grey space group, and ISODISTORT [2] could be applied to model the structure. Although the structure description is done using magnetic groups, the active irrep(s) are also given in most cases. The entries of the collection can be retrieved in a cif-like format, which is supported by internet tools as STRCONVERT [1] and ISOCIF [2], the visualization program VESTA [3], and some refinement programs (JANA2006, FULLPROF). Each entry also includes Vesta files that allow the visualization of a single magnetic unit cell.

scholarly journals THE GLOBAL OPTIMAL PLACEMENT OF BLE BEACON FOR LOCALIZATION BASED ON INDOOR MAP

2018 ◽  
Vol XLII-4 ◽  
pp. 529-534
Author(s):  
L. Ruan ◽  
L. Zhang ◽  
F. Cheng ◽  
Y. Long
Keyword(s):  
Indoor Positioning ◽  
Optimal Placement ◽  
Prototype System ◽  
Localization Accuracy ◽  
Space Objects ◽  
Positioning Method ◽  
Anchor Nodes ◽  
Global Optimal ◽  
The Cost ◽  
Indoor Positioning System

<p><strong>Abstract.</strong> Anchor Nodes in a localization system obviously play a crucial role in determining the system’s quality. Their placement directly affects the localization accuracy and their number directly impacts the total cost of the system. Nowadays, the deployment of Bluetooth nodes in industry generally relies on the experience knowledge of engineers and the cost of positioning beacon does not considered the global level. In this paper, we put forward a method to extract the number and location of BLE beacon automatically and ensure a high positioning accuracy of the indoor positioning system based the rules of indoor positioning, which use all kinds of space objects and structure characteristics of indoor map. The triangulation method was selected to study the global optimal placement of BLE beacon for localization based on indoor map. The impacts and requirements of BLE beacon placement were systematic analysed from the triangulation positioning method, indoor positioning environment and indoor user distribution characteristics. According to the characteristics of indoor environment structure and user distribution, we built an optimization model of BLE beacon placement method based on genetic algorithm which can generate the number and the location of BLE beacon. At last, the Bluetooth indoor positioning prototype system is developed to compare the experience method deployment scheme and the global optimization deployment scheme in the real indoor positioning environment.</p>

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