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Real-time localization estimator of mobile node in wireless sensor networks based on extended Kalman filter

Journal of Shanghai University(English Edition) 2011年第2期15卷 128-131页

作者：田金鹏郑国莘 Key Laboratory of Specialty Fiber Optics and Optical Access Networks School of Communication and Information Engineering Shanghai University

localization of the sensor nodes is a key supporting technology in wireless sensor networks （WSNs）. In this paper, a real-time localization estimator of mobile node in WSNs based on extended Kalman filter （KF） is proposed. Mobile node movement model is analyzed and online sequential iterative method is used to compute location result. The detailed steps of mobile sensor node self-localization adopting extended Kalman filter （EKF） is designed. The simulation results show that the accuracy of the localization estimator scheme designed is better than those of maximum likelihood estimation （MLE） and traditional KF algorithm.

关键词： wireless sensor networks (WSNs) node location localization algorithm Kalman filter (KF)

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Combined gamma radiation source detector and ultrasound imaging system: Proof of concept and first results

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Computers in Biology and Medicine 2025年 193卷 110378-110378页

作者： Thilo Mayer Georg Pohlner Jörg Starflinger Peter P. Pott Institute of Medical Device Technology University of Stuttgart Pfaffenwaldring 9 70569 Stuttgart Germany Institute of Nuclear Technology and Energy Systems University of Stuttgart Pfaffenwaldring 31 70569 Stuttgart Germany

Background The examination of lymphogenic metastasis is the basis for the treatment of tumors. It primarily targets the sentinel lymph nodes (SLN). Common imaging techniques to identify SLNs expose patients to high doses of radiation. Ultrasound imaging supported by radiation detectors is a more patient-friendly alternative that can be used intraoperatively. This work aims to develop a gamma source detector which can localize the source and can be combined with a commercial ultrasound system to a dual-modality system. Methods The problem is modeled, and a localization algorithm is developed that robustly determines position estimates from noisy sensor readings. An accuracy optimized arrangement of sensors is determined. The concept is verified by using a test setup based on infrared radiation. Furthermore first tests with gamma radiation are performed. Results An infrared radiation source with unknown radiant flux is localized with a spatial deviation of 3.64 ± 1.66 mm (2σ) on average within a wide measurement range of 40 × 20 × 60 mm 3 . A visualization setup to combine and display data from the developed sensor system and an ultrasound system is shown, that achieves a display rate of 3 frames/s. Tests with gamma radiation show that two gamma source positions can be distinguished. Conclusions The system presented allows 3D localization of a gamma radiation source with reduced radiation exposure to patients. The measurements are combined registration-free with ultrasound imaging to a dual-modality system and provide an enriched database for SLN identification. To reduce measurement times, more efficient sensors must be used.

关键词： Sentinel lymph nodes Ultrasound imaging Sensor fusion Gamma radiation localization localization algorithm Radio guided surgery Gamma-ultrasound scanner

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Ash deposition modeling using a visco-elastic approach

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FUEL 2012年 102卷 145-155页

作者： Losurdo, Marco Spliethoff, Hartmut Kiel, Jaap TU Muenchen D-85747 Garching Germany ECN NL-1755 ZG Petten Netherlands

In pulverized fuel (PF) combustors and gasifiers, ash particles may deposit on heat exchangers reducing efficiency, performance and, in some cases, damaging boilers and gasifiers. In general, ash particle composition, size (fragmentation) and mechanical properties (hardness and stickiness) are affected by the history of each particle along their trajectory. In the present work, visco-elastic models are used to predict the Young Modulus according to time, temperature and ash composition. In commercial CFD programs, particle adhesion is usually modelled either as fully trapped or bouncing off according to a specific restitution coefficient usually given as input to the wall boundary surface. The authors apply the mechanical adhesion approach proposed by Johnson (JKR theory) which takes into account the surface energy, particle size and the hardness of both the particle and the impacted surface. The energy restitution coefficients are calculated as the remaining kinetic energy after elastic-plastic particle deformation and work of adhesion due to inertia impaction. To implement this approach, a specific Lagrangian particle tracking code was developed to track particle and predict their fate post-processing CFD flow data fields. Numerical results are validated against hollow glass particle and biomass ash experiments carried out in the entrained flow reactor in use at The Energy Research Center of The Netherlands (ECN). Hollow glass particle were used to mimic the high silica content ash obtained from co-firing biomass facilities. The final goal of this work is to present a comprehensive approach to mathematically describe deposition and deposit build-up by means of mechanical and rheological models for visco-elastic solids. Numerical results compare fairly well to available experimental data of the average particle dispersion. (C) 2012 Published by Elsevier Ltd.

关键词： Lagrangian particle tracking localization algorithm Biomass Rheology Adhesion

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A novel distributed sensor positioning system using the dual of target tracking

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IEEE TRANSACTIONS ON COMPUTERS 2008年第2期57卷 246-260页

作者： Zhang, Liqiang Cheng, Qiang Wang, Yingge Zeadally, Sherali Indiana Univ Dept Comp & Informat Sci South Bend IN 46615 USA Siemens Corp Siemens Med Solut Princeton NJ 08540 USA Wayne State Univ Dept Elect & Comp Engn Detroit MI 48202 USA Univ District Columbia Dept Comp Sci & Informat Technol Washington DC 20008 USA

As one of the fundamental issues in wireless sensor networks (WSNs), the sensor localization problem has recently received extensive attention. In this work, we investigate this problem from a novel perspective by treating it as a functional dual of target tracking. In traditional tracking problems, static location-aware sensors track and predict the position and/or velocity of a moving target. As a dual, we utilize a moving location assistant (LA) (with a global positioning system (GPS) or a predefined moving path) to help location-unaware sensors to accurately discover their positions. We call our proposed system Landscape. In Landscape, an LA (an aircraft, for example) periodically broadcasts its current location (we call it a beacon) while it moves around or through a sensor field. Each sensor collects the location beacons, measures the distance between itself and the LA based on the received signal strength (RSS), and individually calculates their locations via an Unscented Kalman Filter (UKF)-based algorithm. Landscape has several features that are favorable to WSNs, such as high scalability, no intersensor communication overhead, moderate computation cost, robustness to range errors and network connectivity, etc. Extensive simulations demonstrate that Landscape is an efficient sensor positioning scheme for outdoor sensor networks.

关键词： wireless sensor networks localization algorithm Unscented Kalman Filter

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Design of Logistics Sorting algorithm Based on Deep Learning and Sampling Evaluation

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2024年第1期17卷 1-16页

作者： Feng, Chun Shanxi Vocat & Tech Coll Finance & Trade Econ & Trade Dept Taiyuan 030031 Peoples R China

The advancement of automation and Internet of Things technology has bolstered the automation process in the logistics sector. To address the challenge of localizing and generating grasping positions for intelligent robots in logistics sorting, this study developed an algorithm for item localization. The algorithm relies on enhanced YOLOv3 target detection and instance segmentation technologies to design a position generation algorithm for the robotic arm, which was further refined using sampling evaluation. The experimental results showed that the research-improved target detection model performed better on different datasets in terms of F1 value, accuracy and Area under the Curve (AUC) metrics, with the highest values of 95.77%, 94.05%, and 91.30%, respectively, which was effective in localizing document-like parcels. Meanwhile, the instance segmentation algorithm with fused features took significantly lower values than other target detection algorithms in terms of average absolute value error and root mean square error. The accuracy rate and all-class average precision value were higher than other target detection models, and the fluctuation of the value taken was smaller, which was suitable for logistics parcel localization. The position generation model, based on a sampling evaluation, yielded significantly different values compared to other algorithms. The relative position error and absolute trajectory error indexes were all below 0.4. The combined indexes of grasping accuracy and error indicate the superior performance of the research-designed algorithms. They can effectively enhance the sorting effects of real logistics scenarios. This research contributes to the improvement of the automated sorting system through the use of visual robotic arm technology. Additionally, it encourages the development of logistics automation and the establishment of intelligent logistics factories.

关键词： Intelligent logistics Convolutional neural network YOLOv3 localization algorithm Sampling evaluation Position generation algorithm

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Source positioning in a large-scale tiny-sensor network of arbitrary topology

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2014年第1期2014卷 1页

作者： Penkin, Dmitriy Janssen, Gerard Yarovoy, Alexander Delft Univ Technol Microwave Sensing Signals & Syst Grp NL-2628 CD Delft Netherlands Delft Univ Technol Circuits & Syst Grp NL-2628 CD Delft Netherlands

To effectively localise a source node in a dense wireless tiny-sensor network with an arbitrary 2D/3D node distribution, a novel approach suitable to describe the hop progress of source-to-sink path in such a system is proposed. In this approach, the network topology is described as a regular lattice and relates the statistical parameters of the hop count in the source-to-sink propagation path to the fractal properties of a percolating cluster. Based on this approach, a mathematical model is developed to estimate the probability P(r, t) of successful reception of the message by a sink node spaced at distance r from a source in a given time t. The accuracy analysis of the positioning method demonstrates its high performance for the very broad spectrum of values of the occupation probability pocc.

关键词： Random network Lattice model Percolation theory Multihop channel Hop count Source-to-sink path localization algorithm

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Research on Underwater Wireless Sensor Network and MAC Protocol and Location algorithm

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IEEE ACCESS 2019年 7卷 56606-56616页

作者： Xi, Zhenghao Kan, Xiu Cao, Le Liu, Huaping Manogaran, Gunasekaran Mastorakis, George Mavromoustakis, Constandinos X. Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201620 Peoples R China Tsinghua Natl Lab Informat Sci & Technol State Key Lab Intelligent Technol & Syst Beijing 100084 Peoples R China Univ Calif Davis John Muir Inst Environm Davis CA 95616 USA Technol Educ Inst Crete Dept Business Adm Iraklion 72100 Greece Univ Nicosia Dept Comp Sci CY-1700 Nicosia Cyprus

In recent years, underwater wireless sensor networks (UWSNs) have received extensive attention due to their application in the development of marine resources. The underwater acoustic channel has a long delay, low bandwidth, and highly dynamic changes in the underwater environment so that the existing technologies and protocols in the traditional wireless sensor network cannot be directly applied to underwater. This paper studies the medium access control (MAC) protocol and positioning technology of UWSNs and introduces the typical underwater line sensor network MAC protocol. Aiming at the problem of spatial fairness caused by the propagation characteristics of the underwater acoustic channel and the triple terminal problem caused by the long propagation delay in UWSNs, and effectively implementing the multi-channel mechanism, an underwater multi-channel based on a single transceiver is proposed, which is SFM-MAC. The existing underwater positioning algorithms are divided into two categories, centralized positioning algorithm and distributed positioning algorithm, and each type of algorithm is briefly explained. In this paper, the Markov chain is used to construct the reservation model of the control channel, and the theoretical analysis of multi-channel throughput is given. The theoretical throughput of the multi-channel MAC protocol under the condition of reserved collision is obtained. Finally, this paper verifies the actual performance of SFM-MAC through simulation experiments.

关键词： Underwater wireless sensor networks MAC protocol localization algorithm fairness hidden terminal

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A random graph model for optical networks of sensors

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2003年第3期2卷 186-196页

作者： Díaz, J Petit, J Serna, M Univ Politecn Cataluna Dept Llenguatges & Sist Informat ES-08034 Barcelona Spain

The main contribution of this paper is presenting a new model for Smart Dust networks communicating through optical links and showing its applicability when the goal of the network is monitoring an area under the surveillance of a base station. We analyze the basic parameters of these networks as a new model of random graphs and propose simple distributed protocols for basic communication. These protocols are designed to minimize the energy consumption.

关键词： optical networks of sensors random scaled sector graphs localization algorithm random model of network

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Characterization and field validation of smart rocks for bridge scour monitoring

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STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL 2019年第5-6期18卷 1669-1685页

作者： Tang, Fujian Chen, Yizheng Li, Zhaochao Hu, Xiuyan Chen, Genda Tang, Yan Dalian Univ Technol State Key Lab Coastal & Offshore Engn Dalian Peoples R China Dalian Univ Technol Sch Civil Engn Dalian Peoples R China Missouri Univ Sci & Technol Dept Civil Architectural & Environm Engn 1304 N Pine St Rolla MO 65409 USA Tongji Univ Sch Civil Engn Shanghai Peoples R China

In this study, two types of smart rocks are proposed, characterized, and validated for bridge scour monitoring, including the arbitrary oriented system smart rock and the automatically pointing to south system smart rock. Effect of the smart rocks on the geomagnetic field is numerically studied, and algorithms to localize the position of the smart rocks are developed. Field validation tests are conducted at an open area in Rolla, MO, USA. Results show that the magnetic intensity decreases in cubic function with a distance away from the smart rock. The algorithm can effectively localize the position of smart rocks during validation tests. The effective monitoring range of the two smart rocks is dependent on the flux (or size) of the magnet used to fabricate the smart rocks, the accuracy of the magnetometer, the direction of smart rocks, as well as the intensity and variation of the ambient magnetic field. Compared with arbitrary oriented system smart rock, less measurement points are needed to localize the automatically pointing to south system smart rock.

关键词： Bridge scour smart rock magnetic field localization algorithm monitoring range

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Effective algorithms for WSN With Weight Principle in Web of Things

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IEEE SENSORS JOURNAL 2014年第1期14卷 228-233页

作者： Zhao Ju-Min An Wen-Xiu Li Deng-Ao Zhao Dong-Dong Cui Yuan-Yuan Taiyuan Univ Technol Informat Engn Coll Taiyuan 030006 Peoples R China

Wireless sensor networks (WSNs) are widely used in variety fields, especially in the Web of Things. The sensor localization information is important for the capability of it. The centroid algorithm is a kind of no ranging location algorithm, which is widely used in the positioning in WSN. To improve the positioning accuracy, this paper puts forward an improved weighted centroid algorithm, then self-corrected. We take any four beacon nodes to improve the node localization accuracy, retaining the simplicity of algorithm and saving nodes energy. These four beacon nodes compose a quadrangle, which is then divided into two triangles to seek centroids and get their average values. Thereafter, we measure each beacon node and empower the values, then use the centroid localization algorithm again to locate object nodes. The simulations show that the algorithm effectively improves the positioning accuracy of the unknown nodes.

关键词： Web of Things localization algorithm weighted centroid TDOA

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