Jammer Location-Oriented Noise Node Elimination Method for MHWN

2014 ◽  
Vol 6 (4) ◽  
pp. 1-19 ◽  
Author(s):  
Jianhua Fan ◽  
Qiping Wang ◽  
Xianglin Wei ◽  
Tongxiang Wang
Keyword(s):  
Environmental Factors ◽  
Mutual Interference ◽  
Algorithm Analysis ◽  
Localization Algorithm ◽  
Elimination Method ◽  
Localization Algorithms ◽  
The Mean ◽  
Simulation Results ◽  
Noise Nodes

It is crucial to find the location of the radio jammer for implementing anti-jamming methods and thus resuming the communication and management of MHWN. Nevertheless, due to the influence of environmental factors and the mutual interference of normal nodes, several unaffected nodes are unable to accurately identify whether they are affected by jammer and thus become noise nodes in the jammer location-oriented process, thereby influencing the precision of jamming localization algorithm and causing remarkable error. In this paper, an algorithm is put forward to eliminate noise nodes based on the Mean of Squared Distance among the nodes. Through calculating the Mean of Squared Distance of each node, the authors can find out the noise nodes and remove them. Simulation results in different jamming localization algorithms verify the correctness and effectiveness of the proposed algorithm. Analysis results reveal that the performance of the proposed algorithm is more prominent when the incidence of noise node is small.

Correlation between Estimation Error and Possible Region in Localization Algorithms

2012 ◽  
Vol 457-458 ◽  
pp. 1514-1520
Author(s):  
Shi Hao Yan ◽  
Jian Ping Xing ◽  
De Qiang Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Estimation Error ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Estimation Errors ◽  
Localization Algorithms ◽  
Localization Precision ◽  
Simulation Results ◽  
Definite Correlation

Many localization algorithms in wireless sensor networks mention possible regions to increase the degree of localization precision. In this paper, we present the definite correlation between the estimation error and the possible region. The estimation error, which is the most important indictor to judge the performance of a localization algorithm, is proportional to the square root of the area of the possible region and the factor of proportionality relates to the shape of the possible region. We also propose two applications of the definite correlation, including estimation errors detection and energy conservation. The simulation results show that the definite correlation is suitable for all kinds of possible regions and it is feasible to detect estimation errors and conserve energy when we fix reasonable areas of possible regions in wireless sensor networks.

Accuracy analysis of BLE beacon-based localization in smart buildings

2021 ◽  
pp. 1-20
Author(s):  
Rosen Ivanov
Keyword(s):  
Use Case ◽  
Accuracy Analysis ◽  
Localization Algorithm ◽  
Computing Power ◽  
Smart Buildings ◽  
Localization Accuracy ◽  
Positioning Systems ◽  
Deployment Strategy ◽  
Accurate Localization ◽  
Localization Algorithms

The majority of services that deliver personalized content in smart buildings require accurate localization of their clients. This article presents an analysis of the localization accuracy using Bluetooth Low Energy (BLE) beacons. The aim is to present an approach to create accurate Indoor Positioning Systems (IPS) using algorithms that can be implemented in real time on platforms with low computing power. Parameters on which the localization accuracy mostly depends are analyzed: localization algorithm, beacons’ density, deployment strategy, and noise in the BLE channels. An adaptive algorithm for pre-processing the signals from the beacons is proposed, which aims to reduce noise in beacon’s data and to capture visitor’s dynamics. The accuracy of five range-based localization algorithms in different use case scenarios is analyzed. Three of these algorithms are specially designed to be less sensitive to noise in radio channels and require little computing power. Experiments conducted in a simulated and real environment show that using proposed algorithms the localization accuracy less than 1 m can be obtained.

scholarly journals Multi-UAV Area Coverage Based on Relative Localization: Algorithms and Optimal UAV Placement

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2400
Author(s):  
Ziyong Zhang ◽  
Xiaoling Xu ◽  
Jinqiang Cui ◽  
Wei Meng
Keyword(s):  
Quadratic Programming ◽  
Wide Band ◽  
Area Coverage ◽  
Localization Algorithm ◽  
Placement Problem ◽  
Position Information ◽  
Relative Localization ◽  
Coverage Control ◽  
Localization Algorithms ◽  
Multi Uav

This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.

scholarly journals Characterization of Deleterious Mutations in Outcrossing Populations

Genetics ◽  
1998 ◽  
Vol 150 (2) ◽  
pp. 945-956 ◽  
Author(s):  
Hong-Wen Deng
Keyword(s):  
Genetic Variation ◽  
Genetic Variance ◽  
Estimation Bias ◽  
Deleterious Mutations ◽  
Environmental Variance ◽  
Higher Power ◽  
Sib Mating ◽  
The Mean ◽  
Simulation Results

Abstract Deng and Lynch recently proposed estimating the rate and effects of deleterious genomic mutations from changes in the mean and genetic variance of fitness upon selfing/outcrossing in outcrossing/highly selfing populations. The utility of our original estimation approach is limited in outcrossing populations, since selfing may not always be feasible. Here we extend the approach to any form of inbreeding in outcrossing populations. By simulations, the statistical properties of the estimation under a common form of inbreeding (sib mating) are investigated under a range of biologically plausible situations. The efficiencies of different degrees of inbreeding and two different experimental designs of estimation are also investigated. We found that estimation using the total genetic variation in the inbred generation is generally more efficient than employing the genetic variation among the mean of inbred families, and that higher degree of inbreeding employed in experiments yields higher power for estimation. The simulation results of the magnitude and direction of estimation bias under variable or epistatic mutation effects may provide a basis for accurate inferences of deleterious mutations. Simulations accounting for environmental variance of fitness suggest that, under full-sib mating, our extension can achieve reasonably well an estimation with sample sizes of only ∼2000-3000.

Based on RSSI Ranging Technology for DV-Hop Localization Algorithm of Wireless Sensor Network

2012 ◽  
Vol 442 ◽  
pp. 360-365 ◽  
Author(s):  
Yang Jun Zhong
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Approximate Calculation ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Original Algorithm ◽  
Approximate Distance ◽  
Anchor Nodes ◽  
Simulation Results

For the DV-Hop algorithm of wireless sensor networks,there is an error arising problem that anchor nodes and location node hop distance is only an approximate calculation. A method based on the original Algorithm introducing RSSI ranging technique is proposed.Using RSSI ranging technology,we accord that if the anchor nodes is only a hop away from the location node,then decide whether using the DV-Hop algorithm to approach to the approximate distance between them. Simulation results show that the algorithm can effectively improve the error problems of calculating the hop distance between the anchor nodes and the location nodes, meanwhile improve the positioning accuracy of the node.

The Influence of Indoor Environmental Factors on the Prevalence of House Dust Mites as Aeroallergens in Bandar Abbas Student Dormitories, South of Iran, 2019

2021 ◽  
Author(s):  
Mehdi Zare ◽  
Mehdi Hassani-Azad ◽  
Moussa Soleimani-Ahmadi ◽  
Raziea Majnoon
Keyword(s):  
Environmental Factors ◽  
House Dust ◽  
Dermatophagoides Pteronyssinus ◽  
House Dust Mites ◽  
Dust Mites ◽  
Dermatophagoides Farinae ◽  
Floor Covering ◽  
The Mean ◽  
Bandar Abbas ◽  
Cheyletus Malaccensis

Abstract This study was conducted to determine the influence of environmental factors on the prevalence of house dust mites in student dormitories of Bandar Abbas city. In this study, 64 dust samples were collected from seven randomly selected dormitories located in various areas of the Bandar Abbas. The collected mites were isolated and mounted in Hoyer’s medium and identified using a morphological key. The associations between the environmental factors and the density of house dust mites were investigated. In total, 1,093 adult mites were collected and identified. They consisted of four species including Dermatophagoides pteronyssinus Trouessart (57.6%), Dermatophagoides farinae Hughes (24.3%) and Dermatophagoides evansi Fain (14.9%) (Acari: Pyroglyphidae), and Cheyletus malaccensis Oudemans (3.2%) (Acari: Cheyletidae). All of the dormitories were contaminated by more than one house dust mites species and the mean density of house dust mites in dormitories was 8.3 ± 0.2 mites/g of dust. There was a significant relationship between average house dust mites density and some of environmental factors such as relative humidity, temperature, floor covering type, and number of occupants (P < 0.05). Results of this study revealed that two major allergenic dust mites, D. pteronyssinus and D. farinae, were the most prevalent and collected from all of dormitories and some of indoor environmental factors found to influence mites’ population.

scholarly journals Performance Analysis of AOA-Based Localization Using the LS Approach: Explicit Expression of Mean-Squared Error

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Byung-Kwon Son ◽  
Do-Jin An ◽  
Joon-Ho Lee
Keyword(s):  
Explicit Expression ◽  
Mean Squared Error ◽  
Weighted Least Squares ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Squared Error ◽  
Distance Weighted ◽  
The Mean ◽  
Passive Localization ◽  
Location Estimate

In this paper, a passive localization of the emitter using noisy angle-of-arrival (AOA) measurements, called Brown DWLS (Distance Weighted Least Squares) algorithm, is considered. The accuracy of AOA-based localization is quantified by the mean-squared error. Various estimates of the AOA-localization algorithm have been derived (Doğançay and Hmam, 2008). Explicit expression of the location estimate of the previous study is used to get an analytic expression of the mean-squared error (MSE) of one of the various estimates. To validate the derived expression, we compare the MSE from the Monte Carlo simulation with the analytically derived MSE.

DUTY-CYCLED SPINNING BASED 3D MOTION CONTROL APPROACH FOR BEVEL-TIPPED FLEXIBLE NEEDLE INSERTION

2018 ◽  
Vol 18 (07) ◽  
pp. 1840017 ◽  
Author(s):  
QIN YAO ◽  
XUMING ZHANG
Keyword(s):  
Motion Control ◽  
Control Method ◽  
Tracking Error ◽  
Open Loop ◽  
Loop Control ◽  
3D Motion ◽  
Control Approach ◽  
Target Error ◽  
The Mean ◽  
Simulation Results

Flexible needle has been widely used in the therapy delivery because it can advance along the curved lines to avoid the obstacles like important organs and bones. However, most control algorithms for the flexible needle are still limited to address its motion along a set of arcs in the two-dimensional (2D) plane. To resolve this problem, this paper has proposed an improved duty-cycled spinning based three-dimensional (3D) motion control approach to ensure that the beveled-tip flexible needle can track a desired trajectory to reach the target within the tissue. Compared with the existing open-loop duty-cycled spinning method which is limited to tracking 2D trajectory comprised of few arcs, the proposed closed-loop control method can be used for tracking any 3D trajectory comprised of numerous arcs. Distinctively, the proposed method is independent of the tissue parameters and robust to such disturbances as tissue deformation. In the trajectory tracking simulation, the designed controller is tested on the helical trajectory, the trajectory generated by rapidly-exploring random tree (RRT) algorithm and the helical trajectory. The simulation results show that the mean tracking error and the target error are less than 0.02[Formula: see text]mm for the former two kinds of trajectories. In the case of tracking the helical trajectory, the mean tracking error target error is less than 0.5[Formula: see text]mm and 1.5[Formula: see text]mm, respectively. The simulation results prove the effectiveness of the proposed method.

scholarly journals NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2991 ◽  
Author(s):  
Jingyu Hua ◽  
Yejia Yin ◽  
Weidang Lu ◽  
Yu Zhang ◽  
Feng Li
Keyword(s):  
Hypothesis Test ◽  
Intermediate Position ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Target Node ◽  
Localization Algorithms ◽  
Anchor Nodes ◽  
Positioning Algorithm ◽  
Non Line Of Sight

The problem of target localization in WSN (wireless sensor network) has received much attention in recent years. However, the performance of traditional localization algorithms will drastically degrade in the non-line of sight (NLOS) environment. Moreover, variable methods have been presented to address this issue, such as the optimization-based method and the NLOS modeling method. The former produces a higher complexity and the latter is sensitive to the propagating environment. Therefore, this paper puts forward a simple NLOS identification and localization algorithm based on the residual analysis, where at least two line-of-sight (LOS) propagating anchor nodes (AN) are required. First, all ANs are grouped into several subgroups, and each subgroup can get intermediate position estimates of target node through traditional localization algorithms. Then, the AN with an NLOS propagation, namely NLOS-AN, can be identified by the threshold based hypothesis test, where the test variable, i.e., the localization residual, is computed according to the intermediate position estimations. Finally, the position of target node can be estimated by only using ANs under line of sight (LOS) propagations. Simulation results show that the proposed algorithm can successfully identify the NLOS-AN, by which the following localization produces high accuracy so long as there are no less than two LOS-ANs.

scholarly journals Adaptive Noise Cancellation of an Analog Fiber Optic Link

2021 ◽  
Author(s):  
Mohammad Nazrul Islam
Keyword(s):  
Optical Fiber ◽  
Fiber Optic ◽  
Signal To Noise Ratio ◽  
Optical Power ◽  
Noise Cancellation ◽  
Adaptive Noise Cancellation ◽  
Fiber Link ◽  
The Mean ◽  
Simulation Results ◽  
Adaptive Noise

There are three dominant noise mechanisms in an analog optical fiber link. These are shot noise that is proportional to the mean optical power, relative intensity noise (RIN) that is proportional to the square of the instanteaneous optical power. This report describes an adaptive noise cancellation of these dominant noise processes that persist an analog optical fiber link. The performance of an analog optical fiber link is analyzed by taking the effects of these noise processes. Analytical and simulation results show that some improvement in signal to noise ratio (SNR) and this filter is effective to remove noise adaptively from the optical fiber link.

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