scholarly journals Research on RSS Data Optimization and DFL Localization for Non-Empty Environments

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4419
Author(s):  
Wenyu Mao ◽  
Rongxuan Shen ◽  
Ke Wang ◽  
Guoliang Gong ◽  
Yi Xiao ◽  
...  
Keyword(s):  
Target Location ◽  
Learning Model ◽  
Random Disturbance ◽  
Wavelet Filtering ◽  
Localization Accuracy ◽  
Generalization Ability ◽  
Localization Model ◽  
Random Disturbances ◽  
Shadowing Effect ◽  
A New Technique

Device-free localization (DFL) is a new technique which can estimate the target location through analyzing the shadowing effect on surrounding radio frequency (RF) links. In a relatively complex environment, the influences of random disturbance and the multipath effect are more serious. There are kinds of noises and disturbances in the received signal strength (RSS) data of RF links and the data itself can even be distorted, which will seriously affect the DFL accuracy. Most of the common filtering methods adopted in DFL field are not targeted and the filtering effects are unstable. This paper researches the characteristics of RSS data with random disturbances and proposes two-dimensional double correlation (TDDC) distributed wavelet filtering. It can filter out the random disturbances and noise while preserving the RSS fluctuations which are helpful for the DFL, thus improving the quality of RSS data and localization accuracy. Furthermore, RSS variation rules for the links are different in complex environments and hence, it is difficult for the collected training samples to cover all possible patterns. Therefore, a single machine learning model with poor generalization ability finds it difficult to achieve ideal localization results. In this paper, the Adaboost.M2 ensemble learning model based on the Gini decision tree (GDTE) is proposed to improve the generalization ability for unknown patterns. Extensive experiments performed in two different drawing rooms demonstrate that the TDDC distributed wavelet filtering and the GDTE localization model have obvious advantages compared with other methods. The localization accuracy rates of 87% and 95% can be achieved respectively in the two environments.

Video Nodes Based Collaborative Object Localization Framework in Wireless Multimedia Sensor Networks

2011 ◽  
Vol 317-319 ◽  
pp. 1078-1083 ◽  
Author(s):  
Qing Tao Lin ◽  
Xiang Bing Zeng ◽  
Xiao Feng Jiang ◽  
Xin Yu Jin
Keyword(s):  
Cluster Head ◽  
Computation Time ◽  
Least Square Method ◽  
Least Square ◽  
Object Localization ◽  
Wireless Multimedia ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Multimedia Sensor Networks ◽  
Localization Model

This paper establishes a 3-D localization model and based on this model, it proposes a collaborative localization framework. In this framework, node that observes the object sends its attitude information and the relative position of the object's projection in its camera to the cluster head. The cluster head adopts an algorithm proposed in this paper to select some nodes to participate localization. The localization algorithm is based on least square method. Because the localization framework is based on a 3-D model, the size of the object or other prerequisites is not necessary. At the end of this paper, a simulation is taken on the numbers of nodes selected to locate and the localization accuracy. The result implies that selecting 3~4 nodes is proper. The theoretical analysis and the simulation result also imply that a const computation time cost is paid in this framework with a high localization accuracy (in our simulation environment, a 0.01 meter error).

Large Nonlinear Responses of Spatially Nonhomogeneous Stochastic Shell Structures Under Nonstationary Random Excitations

2009 ◽  
Vol 9 (4) ◽  
Author(s):  
C. W. S. To
Keyword(s):  
Finite Element ◽  
Shell Structures ◽  
Random Disturbance ◽  
Hybrid Strain ◽  
Central Difference ◽  
Spherical Cap ◽  
Approximation Techniques ◽  
Nonlinear Responses ◽  
Novel Approach ◽  
Random Disturbances

A novel approach for determining large nonlinear responses of spatially homogeneous and nonhomogeneous stochastic shell structures under intensive transient excitations is presented. The intensive transient excitations are modeled as combinations of deterministic and nonstationary random excitations. The emphases are on (i) spatially nonhomogeneous and homogeneous stochastic shell structures with large spatial variations, (ii) large nonlinear responses with finite strains and finite rotations, (iii) intensive deterministic and nonstationary random disturbances, and (iv) the large responses of a specific spherical cap under intensive apex nonstationary random disturbance. The shell structures are approximated by the lower order mixed or hybrid strain based triangular shell finite elements developed earlier by the author and his associate. The novel approach consists of the stochastic central difference method, time coordinate transformation, and modified adaptive time schemes. Computed results of a temporally and spatially stochastic shell structure are presented. Computationally, the procedure is very efficient compared with those entirely or partially based on the Monte Carlo simulation, and it is free from the limitations associated with those employing the perturbation approximation techniques, such as the so-called stochastic finite element or probabilistic finite element method. The computed results obtained and those presented demonstrate that the approach is simple and easy to apply.

scholarly journals Microwave Dielectric Property Retrieval from Open-Ended Coaxial Probe Response with Deep Learning

2021 ◽  
Author(s):  
Cemanur Aydinalp ◽  
Sulayman Joof ◽  
Mehmet Nuri Akinci ◽  
Ibrahim Akduman ◽  
Tuba Yilmaz
Keyword(s):  
Deep Learning ◽  
Dielectric Property ◽  
Large Scale ◽  
Real Data ◽  
Learning Model ◽  
Data Generation ◽  
Retrieval Technique ◽  
Design Flexibility ◽  
A New Technique ◽  
Deep Learning Model

In the manuscript, we propose a new technique for determination of Debye parameters, representing the dielectric properties of materials, from the reflection coefficient response of open-ended coaxial probes. The method retrieves the Debye parameters using a deep learning model designed through utilization of numerically generated data. Unlike real data, using synthetically generated input and output data for training purposes provides representation of a wide variety of materials with rapid data generation. Furthermore, the proposed method provides design flexibility and can be applied to any desired probe with intended dimensions and material. Next, we experimentally verified the designed deep learning model using measured reflection coefficients when the probe was terminated with five different standard liquids, four mixtures,and a gel-like material.and compared the results with the literature. Obtained mean percent relative error was ranging from 1.21±0.06 to 10.89±0.08. Our work also presents a large-scale statistical verification of the proposed dielectric property retrieval technique.

The response of simple nonlinear systems to a random disturbance of the earthquake type

1964 ◽  
Vol 54 (1) ◽  
pp. 263-276
Author(s):  
J. E. Goldberg ◽  
J. L. Bogdanoff ◽  
D. R. Sharpe
Keyword(s):  
Nonlinear Systems ◽  
First Passage Time ◽  
Equations Of Motion ◽  
Passage Time ◽  
Statistical Properties ◽  
Random Disturbance ◽  
Random Disturbances ◽  
Engineering Significance ◽  
Complex Linear ◽  
Velocity Spectra

abstract Stationary properties of the response of simple nonlinear systems to earthquake type (nonstationary) random disturbances are determined. The method used consists in generating member functions of the input processes, integrating the equations of motion using these as inputs to obtain output member functions, and then, from this ensemble of outputs, determining the statistical properties of interest. The method is flexible in that it is easy to apply to simple as well as complex linear and nonlinear systems; it yields a variety of statistical properties of engineering significance; it provides a method for approaching the design of aseismic structures; and more generally, shock resistant structures on a practical basis. In addition to determining and displaying input and corresponding output member functions, we determine individual as well as average velocity spectra, first passage time probabilities, and extreme value distributions of relative displacements. Comments are also offered on the utility of these results in design.

scholarly journals Device-Free Localization and Identification Using Sub-GHz Passive Radio Mapping

2020 ◽  
Vol 10 (18) ◽  
pp. 6183
Author(s):  
Stijn Denis ◽  
Abdil Kaya ◽  
Rafael Berkvens ◽  
Maarten Weyn
Keyword(s):  
Target Location ◽  
The Other ◽  
Identification Accuracy ◽  
Body Type ◽  
Localization Accuracy ◽  
Rf Communication ◽  
Distance Minimization ◽  
Rudimentary Form ◽  
Device Free ◽  
The Impact

The research domain of device-free localization (DFL) is centered on the study of localization techniques which do not require targets to wear any kind of device. Passive radio mapping or passive fingerprinting is an example of a training-based DFL technique which uses the impact of a human target on radio frequency (RF) communication between stationary nodes to perform localization. We describe a set of experiments performed in a 42 m2 empty office environment in which we installed a RF network with nodes communicating on the 433 MHz and 868 MHz bands. We attempted to locate a single stationary human target based solely on signal strength measurements and did so for six different participants using two different fingerprinting methods. One method was based on Euclidean distance minimization while the other made use of a naive Bayesian classifier. We investigated the impact of frequency band, number of nodes and target body type on localization accuracy. Results indicated that a root mean square error of 48 cm could be obtained with only four nodes, provided that the data from both frequency bands was combined. Additionally, we investigated the potential of these fingerprinting approaches to distinguish between targets based on body type and perform a rudimentary form of passive identification. Accuracy rates for identification could vary significantly depending on target location, with results ranging from 0.07 to 0.75 in the exact same environment. However, the experiment participant with the lowest height and weight could be distinguished from the other participants in over 90% of cases.

Improved Modeling of Electromagnetic Localization for Implantable Wireless Capsules

2010 ◽  
Vol 44 (4) ◽  
pp. 354-359 ◽  
Author(s):  
Xudong Guo ◽  
Guozheng Yan ◽  
Wenhui He ◽  
Pingping Jiang
Keyword(s):  
Series Expansion ◽  
Magnetic Sensor ◽  
Dipole Model ◽  
Localization Error ◽  
Localization Accuracy ◽  
Localization Method ◽  
Localization Model ◽  
Elementary Math ◽  
Electromagnetic Localization ◽  
Improved Model

Abstract An electromagnetic localization method for implantable wireless capsules has been developed that employs a three-axial magnetic sensor embedded in the capsules and three energized coils attached on the abdomen. In order to further improve the localization accuracy, a novel localization model has been derived based on the Biot-Savart Law. For simplicity of the calculation without increasing the position error, the method of truncated series expansion has been used in modeling. The experiment showed that the improved model had higher precision than the original dipole model. Using the improved model, the localization error can be greatly reduced. The improved model is an elementary math function and suitable for resolving some inverse magnetic problems in engineering.

A genetic path planning algorithm for redundant articulated robots

Robotica ◽  
1997 ◽  
Vol 15 (2) ◽  
pp. 213-224 ◽  
Author(s):  
Andreas C. Nearchou ◽  
Nikos A. Aspragathos
Keyword(s):  
Path Planning ◽  
Degrees Of Freedom ◽  
Target Location ◽  
Planning Problem ◽  
Worst Case ◽  
Pick And Place ◽  
Planning Algorithm ◽  
A New Technique ◽  
Articulated Robots ◽  
Path Planning Algorithm

In some daily tasks, such as pick and place, the robot is requested to reach with its hand tip a desired target location while it is operating in its environment. Such tasks become more complex in environments cluttered with obstacles, since the constraint for collision-free movement must be also taken into account. This paper presents a new technique based on genetic algorithms (GAs) to solve the path planning problem of articulated redundant robot manipulators. The efficiency of the proposed GA is demonstrated through multiple experiments carried out on several robots with redundant degrees-of-freedom. Finally, the computational complexity of the proposed solution is estimated, in the worst case.

Comparison of Nine Methods of Indicating the Direction to Objects: Data from Blind Adults

Perception ◽  
1993 ◽  
Vol 22 (1) ◽  
pp. 35-47 ◽  
Author(s):  
Lyn Haber ◽  
Ralph Norman Haber ◽  
Suzanna Penningroth ◽  
Kevin Novak ◽  
Hilary Radgowski
Keyword(s):  
Individual Differences ◽  
Target Location ◽  
Body Part ◽  
The Body ◽  
Verbal Description ◽  
Body Parts ◽  
Localization Accuracy ◽  
Object Locations ◽  
The Subject ◽  
Diagnostic Measurement

Nine methods of indicating the direction to object locations were tested on twenty blind adult subjects. The task was to indicate the location of active auditory targets distributed in a semicircle with a 1.7 m radius around the subject. Target location, practice, and feedback were systematically varied for each method. The greatest accuracy and lowest variability were found for pointing methods that used body parts (directing the nose at the target, facing it with the chest, and pointing with the index finger) and extensions of body parts (pointing with a hand-held cane or with a short stick). Two less accurate methods involved rotating a dial. The least accurate methods involved drawing and a verbal description in terms of clockface labels. Method interacted significantly with target location, and with individual differences. In general, the body-part and extension method were affected less than other methods by target location and individual differences. The findings suggest that a pointing response that uses a body part or an extension of a body part is the best choice for experimental or diagnostic measurement of object location by blind subjects. Differences between the results of this study of blind subjects and auditory localization accuracy in sighted subjects are discussed, and the implications for spatial processing in the blind are considered.

scholarly journals Multipath Exploitation-Based Indoor Target Localization Model Using Single Marginal Antenna

2020 ◽  
Vol 39 (1) ◽  
pp. 13-20
Author(s):  
Joseph Sisala ◽  
Abdi T. Abdalla
Keyword(s):  
Target Location ◽  
Wide Band ◽  
Target Localization ◽  
Localization Error ◽  
Area Of Interest ◽  
Trip Time ◽  
Localization Model ◽  
Wide Range ◽  
Localization Errors ◽  
Target Locations

Recently, indoor target localization became an area of interest due to its diverse applications. In indoor target localization, surrounding environment creates multipath components, which can be exploited to aid in localization process. A number of studies have been proposed to employ multipath exploitation in localizing indoor targets. However, their localization errors can still be improved. This study proposed a new localization model based on multipath exploitation techniques by using triangulation method. Ultra-wide band signals were resolved and associated using marginal antenna-based scheme. The estimate of the target location was then obtained using measured round-trip time delays. The location was determined by applying the simple trigonometry on the triangle in which real radar, virtual radars, and the target location are the vertices of the triangle in question. Simulation results show that the proposed method has improved the localization error over a wide range of timing errors, target locations and room sizes with the overall maximum localization error of 1.4 m equivalent to 22.2% improvement as compared to 1.8 m localization error obtained using the method developed by the Muqaibel et al. (2017).

Effect of Facility Geometry on RFID Localization Accuracy

2009 ◽  
Author(s):  
Junyi Zhou ◽  
Jing Shi
Keyword(s):  
Radio Frequency Identification ◽  
Target Location ◽  
Industrial Applications ◽  
Width Ratio ◽  
Regular Polygons ◽  
Entire Region ◽  
Localization Accuracy ◽  
Multiple Factors ◽  
Frequency Identification ◽  
Localization Performance

Radio frequency identification (RFID) is a promising technology for localization in various industrial applications. In RFID localization, accuracy is the top performance concern, and it is affected by multiple factors. In this paper, we investigate how the facility geometry impacts the expected localization accuracy in the entire region where the target is uniformly distributed. Three groups of geometries, namely, rectangles with various length-to-width ratios, circle, and regular polygons with 3–10 edges, are chosen for this study. A hybrid multilateration approach, which combines linearization and nonlinear optimization, is used to estimate the target location. Since the layout of landmarks significantly affects localization performance, we evaluate the expected accuracy in a facility obtained under the optimal landmark layout for the facility. The optimal landmark layout for each type of facility geometry is obtained, and then the effect of geometry is studied by comparing the expected accuracies of these layouts. It is discovered that (1) the optimal layouts follow several simple empirical deployment principles, (2) for all geometries, the expected accuracy improves and tends to reach the expected Cramer-Rao lower bound as more landmarks are used, and (3) if the same numbers of landmarks are used, the expected accuracies for circular and regular polygonal geometries are close. However, the expected accuracy for a rectangular geometry decreases as the length-to-width ratio increases.

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