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Positioning method of expressway ETC gantry by multi-source traffic data

IET INTELLIGENT TRANSPORT SYSTEMS 2024年第3期18卷 540-554页

作者： Guo, Feng Zou, Fumin Luo, Sijie Chen, Haobin Yu, Xiang Zhang, Cheng Liao, Lyuchao Fuzhou Univ Coll Comp & Data Sci Fuzhou Fujian Peoples R China Fujian Univ Technol Fujian Key Lab Automot Elect & Elect Drive Fuzhou 350118 Fujian Peoples R China Hunan Univ Finance & Econ Coll Informat Technol & Management Changsha Hunan Peoples R China

With the rapid development of expressway Electronic Toll Collection (ETC) technology in China, the expressway management system is becoming digital and intelligent, which provides a solid foundation for expressway vehicle infrastructure cooperation and autonomous driving. The gantry position is the key part of the ETC system. However, there are still some problems (e.g. gantry position missing or false), which can seriously affect the intelligent development of expressways. To address these two issues, an ETC gantry positioning method is proposed. First, the ETC transaction data and the GPS data on expressways are preprocessed to remove abnormal data and retrieve missed data. Then, combined with Dead Reckoning (DR) and Median Center, the potential position of the gantry is calculated from ETC transaction data and GPS data. Finally, the switching strategy based on Kalman Filter (KF) is used to capture the final gantry position. By comparing the results of the proposal with the collected gantry position, it is found that the positioning error of the gantry position calculated by this proposal is about 37 m. The positioning accuracy is 98.78% with the threshold of 100 m. The experimental results show that the proposal can effectively locate the expressway gantry.

关键词： positioning error positioning accuracy expressway vehicle infrastructure cooperation intelligent development abnormal data Global Positioning System multisource traffic data expressway Electronic Toll Collection technology road traffic filtering methods in signal processing intelligent transportation systems road vehicles collected gantry position traffic engineering computing Kalman filters GPS data ETC transaction data expressway gantry ETC gantry positioning method potential position Traffic engineering computing final gantry position expressway management system

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A real-time fine echo generation method of extended false target with radially high-speed moving

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IET RADAR SONAR AND NAVIGATION 2023年第2期17卷 312-325页

作者： Lei, Wei Zhang, Yue Chen, Zengping Sun Yat Sen Univ Sch Elect & Commun Engn Shenzhen Campus66 Gongchang Rd Shenzhen 518107 Peoples R China

The false-target echo generation to Inverse Synthetic Aperture Radar (ISAR) is significant in jamming the enemy ISAR and promoting ISAR development. Generally, it requires false-target echo coherent with the radar, real time and fine. However, conventional methods, such as digital image synthesizer (DIS), cannot meet those requirements. Moreover, existing methods do not consider the target's radial moving. To meet those demands, we propose an improved method in this study. We equivalently model echo formation as the synthesizer of two independent parts: (1) echo of remote target with radial moving and (2) echo of nearby extended target. In part one, accuracy is improved by utilising the Inner Pulse Motion (IPM) model and complexity is simplified by deducing it as a frequency offset modulation. In part two, the fine extended target echo is constructed by using convolution filtering whose resources consumption can be greatly reduced by separating it into an offline stage and a real-time stage. Our method is verified by algorithm simulations and actual experiments. The results indicate that it can build the fine false-target echo in real-time and can adapt to the target's radial velocity, different resolution and size. Compared with the conventional DIS method, our method reduces the computational complexity significantly and has more comprehensive functions.

关键词： filtering methods in signal processing extended false target Radar equipment, systems and applications radial moving jamming echo formation fine extended target echo synthetic aperture radar high-speed moving real-time fine echo generation method radar imaging Optical, image and video signal processing conventional DIS method nearby extended target remote target real-time stage Electromagnetic compatibility and interference echo enemy ISAR digital image synthesizer false-target echo generation Inverse Synthetic Aperture Radar image filtering

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High-precision simulation technology for enhanced Loran signal simulators based on Lagrange farrow structure filter

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IET RADAR SONAR AND NAVIGATION 2023年第2期17卷 326-336页

作者： Ma, Hongyu Yuan, Yanning Li, Zheng Liu, Jiangfan Pu, Yurong Du, Yongxing Xi, Xiaoli Xian Univ Technol Dept Elect Engn Xian 710048 Peoples R China China Acad Launch Vehicle Technol Sci & Technol Space Phys Lab Beijing Peoples R China Inner Mongolia Univ Sci & Technol Dept Informat Engn Baotou Peoples R China

In this study, a real-time high accuracy signal simulation technique for an enhanced Loran (eLoran) signal simulator is proposed, which can be used to verify the performance of the eLoran receiver. The proposed method is based on a maximumly flat design of the low-pass filter, and high simulation accuracy can be obtained in the low-frequency band. The simulator structure is based on the variable fractional delay Farrow structure, which can regenerate eLoran signals with high-precision time of arrival (TOA) in real-time based on discrete samples on a hardware platform. By comparison of existing methods and the true TOA data validation, the proposed method has high performance for low-frequency narrow-band eLoran signals and the proposed technology can apply to arbitrary TOA real-time simulations.

关键词： filtering methods in signal processing high-precision time simulator structure real-time simulations low-pass filter time of arrival TOA enhanced Loran signal simulator precision simulation technology maximumly flat design eLoran receiver real-time high accuracy signal simulation technique FIR filters narrow-band eLoran signals high simulation accuracy variable fractional delay farrow structure Lagrange farrow structure filter radionavigation time-of-arrival estimation Radionavigation and direction finding Global Positioning System low-pass filters low-frequency band

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Robust adaptive cubature Kalman filter for tracking manoeuvring target by wireless sensor network under noisy environment

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IET RADAR SONAR AND NAVIGATION 2023年第2期17卷 179-190页

作者： Fang, Xuming Huang, Dandan Jinling Inst Technol Nanjing Peoples R China

The existing adaptive Kalman filters for tracking manoeuvring targets by wireless sensor networks can easily lose robustness when both the measurement and process noises are unknown and time-varying, resulting in large positioning errors. To solve this problem, a wireless sensor network manoeuvring target tracking algorithm using a novel robust adaptive cubature Kalman filter is proposed. This innovative robust adaptive cubature Kalman filter consists of a derived third-order biased noise statistic estimator and conventional cubature Kalman filter. This derived noise statistic estimator can simultaneously sense time-varying and unknown measurement and process noises and ensure that the adaptive cubature Kalman filter's robustness is not lost. The robustness of the novel robust adaptive cubature Kalman filter is strictly proven in this study. Extensive practical experiments and numerical simulations show that the proposed robust adaptive cubature Kalman filter always has higher target tracking accuracy than other existing adaptive Kalman filters, regardless of whether the mobile target is manoeuvring or not, the noise is unknown or time-varying, and the number of anchor nodes is few or many.

关键词： time-varying filtering methods in signal processing higher target tracking accuracy conventional cubature Kalman filter third-order biased noise statistic estimator novel robust adaptive cubature Kalman filter adaptive Kalman filters wireless sensor networks innovative robust adaptive cubature Kalman filter target tracking robust control derived noise statistic estimator existing adaptive Kalman filters unknown measurement process noises wireless sensor network manoeuvring target Wireless sensor networks

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Received signal strength indicator-based set-membership filtering indoor localization under multipath effect

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IET CONTROL THEORY AND APPLICATIONS 2023年第2期17卷 160-171页

作者： Yang, Bo Dong, Rongrong Shang, Junqiang Liu, Yadong Shanxi Univ Sch Math Sci Taiyuan 030006 Peoples R China Shanxi Univ Sch Automat & Software Engn Taiyuan Peoples R China

The indoor moving target localization based on the received signal strength indicator is studied in this paper. By introducing filtering algorithms, a novel dynamic parameters set-membership filtering (DPSMF) is proposed to reduce the interference of the multipath effect and noises. First, the higher-order remainder is included in the bounded range based on the interval mathematics method to improve the linearization accuracy of the Taylor series expansion of the measurement function. Second, the parameters to be determined in the channel model are set to local dynamic parameters, which are obtained by solving a particular semi-definite programming problem. Third, the optimized localization estimations of the target node at each sampling instant and the ellipsoid set containing the real state of the system are obtained based on the DPSMF. Finally, an example is given to verify the effectiveness of the proposed DPSMF algorithm.

关键词： filtering methods in signal processing Optimisation techniques ellipsoid set local dynamic parameters optimized localization estimations dynamic parameters set-membership filtering indoor radio RSSI multipath effect filtering theory filtering algorithms received signal strength indicator-based set-membership filtering interval mathematics method higher-order remainder indoor navigation wireless sensor networks target localization DPSMF Wireless sensor networks indoor localization

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Geodesic Gramian denoising applied to the images contaminated with noise sampled from diverse probability distributions

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IET IMAGE processing 2023年第1期17卷 144-156页

作者： Gajamannage, Kelum Park, Yonggi Sadovski, Alexey Texas A&M Univ Dept Math & Stat 6300 Ocean Dr Corpus Christi TX 78412 USA

As quotidian use of sophisticated cameras surges, people in modern society are more interested in capturing fine-quality images. However, the quality of the images might be inferior to people's expectations due to the noise contamination in the images. Thus, filtering out the noise while preserving vital image features is an essential requirement. Existing denoising methods have assumptions, on the probability distribution in which the contaminated noise is sampled, for the method to attain its expected denoising performance. In this paper, the recent Gramian-based filtering scheme to remove noise sampled from five prominent probability distributions from selected images is utilized. This method preserves image smoothness by adopting patches partitioned from the image, rather than pixels, and retains vital image features by performing denoising on the manifold underlying the patch space rather than in the image domain. Its denoising performance is validated, using six benchmark computer vision test images applied to two state-of-the-art denoising methods, namely BM3D and K-SVD.

关键词： filtering methods in signal processing prominent probability distributions patch space image domain differential geometry expected denoising performance diverse probability distributions sophisticated cameras selected images benchmark computer vision test images BM3D denoising method Gramian-based filtering scheme Optical, image and video signal processing Computer vision and image processing techniques geodesic Gramian denoising image denoising noise contamination image smoothness probability fine-quality images vital image features contaminated noise K-SVD denoising method computer vision Other topics in statistics image filtering

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A boost converter-based MPPT steady-state oscillation-free fast tracking control strategy for photovoltaic power systems

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IET POWER ELECTRONICS 2023年第3期16卷 483-497页

作者： Li, Ning Zhang, Changjie Wei, Deng Liu, Ming Zhang, Yan Xian Univ Technol Sch Elect Engn Xian 710048 Peoples R China Xi An Jiao Tong Univ Sch Elect Engn Xian Peoples R China

With the conventional perturbation and observation (P&O) method, photovoltaic (PV) converters have long maximum power point (MPP) tracking times and three-point oscillations at the steady state that can lead to output power losses and inefficiencies in grid connections. To overcome these drawbacks, a fast tracking and steady-state-oscillation-free control strategy is proposed. The strategy first stores four random duty cycle values on the basis of the duty cycle variation characteristics of the PV panel power adjustment, then calculates the odd and even duty cycle difference and judges the steady state by varying the duty cycle difference threshold. The strategy next obtains the MPP duty cycle using a median filtering algorithm (MFA) to suppress the steady-state oscillation and improves the tracking speed by resetting the appropriate duty cycle step according to the slope of the PV curve of the PV panel output and the corresponding adaptive coefficients. The proposed algorithm was simulated and experimentally validated under various irradiance conditions, and the results show that the algorithm can improve the PV panel output efficiency compared to both the conventional P&O and the adaptive P&O methods.

关键词： photovoltaic converters filtering methods in signal processing random duty cycle values Energy resources Solar power stations and photovoltaic power systems grid connections DC-DC power convertors maximum power point tracking P&O method solar power maximum power point trackers adaptive coefficients losses irradiance conditions Solar cells and arrays PV panel power median filters median filtering algorithm solar cell arrays boost converter-based MPPT steady-state oscillation-free fast tracking control strategy duty cycle difference threshold power generation control duty cycle variation characteristics Control of electric power systems power grids Power electronics, supply and supervisory circuits perturbation and observation method photovoltaic power systems three-point oscillations power convertors

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Estimation of the electrical parameters of overhead transmission lines using Kalman filtering with particle swarm optimization

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IET GENERATION TRANSMISSION & DISTRIBUTION 2023年第1期17卷 27-38页

作者： Pereira, Ronaldo F. R. Albuquerque, Felipe P. Liboni, Luisa Helena B. Costa, Eduardo C. Marques Monteiro, Jose Humberto A. Univ Fed Acre Exact & Technol Sci Ctr CCET Rio Branco Brazil Univ Sao Paulo Dept Elect Syst Engn PSI Sao Paulo SP Brazil Fed Inst Educ Sci & Technol Sao Paulo IFSP Dept Elect & Comp Engn Sertaozinho SP Brazil

The parameter estimation for transmission systems is important to power flow analysis, planning the expansion of electric power systems, stability, dispatch and economic analysis. This type of task is developed through systems identification methods, being the least squares method and its variations the most common techniques to obtain the transmission line parameters. However, these techniques have some disadvantages, such as non-recursive parameter estimation or the availability of an ideally transposed line, in order to address a problem with symmetric matrices, which simplifies the estimation process. In this paper, a non-linear method (Extended Kalman Filter) is presented to obtain the states of the transmission line terminals jointly with the vectorized matrix of parameters;such approach is strongly affected by the initial conditions;these conditions are usually obtained manually, which requires a lot of time and effort. Therefore, an optimization method (Particle Swarm Optimization) is applied in order to improve the convergence of the EKF, which reduces the time for adjusting the hyper-parameters and improves the estimated results. The proposed method showed accurate results for non-transposed systems, and also in comparison with results obtained from the same EKF-based method without the proposed optimization technique.

关键词： initial conditions filtering methods in signal processing electrical parameters Extended Kalman Filter Optimisation techniques hyper-parameters Kalman filters particle swarm optimization overhead transmission lines recursive estimation Power transmission, distribution and supply transmission line parameters ideally transposed line transmission systems systems identification methods parameter estimation particle swarm optimisation optimization technique nonlinear filters transmission line terminals estimation process economic analysis symmetric matrices EKF-based method optimization method dispatch analysis nonlinear method matrix algebra electric power systems Kalman filtering nontransposed systems Interpolation and function approximation (numerical analysis) Power engineering computing least squares approximations power flow analysis power transmission lines optimisation Overhead power lines nonrecursive parameter estimation

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Recursive fusion estimation for mobile robot localization under multiple energy harvesting sensors

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IET CONTROL THEORY AND APPLICATIONS 2022年第1期16卷 20-30页

作者： Lu, Yanyang Karimi, Hamid Reza Luoyang Inst Sci & Technol Sch Intelligent Mfg Luoyang Peoples R China Donghua Univ Coll Informat Sci & Technol Shanghai Peoples R China Politecn Milan Dept Mech Engn I-20156 Milan Italy

This paper is concerned with the recursive fusion estimation-based mobile robot localization (RL) problem by employing multiple energy harvesting sensors (EHSs). In the addressed RL problem, multiple sensors with energy harvesting capacity are deployed to produce measurements used for RL. When the sensors own sufficient energy, the sensors can output measurements and then send them to the corresponding local filter. Otherwise, the sensor energy-induced missing measurement phenomenon will occur. In order to obtain the missing measurement rate, at each time instant, the relationship between the totality of the sensor energy and its probability distribution is derived recursively. This paper aims at seeking out a practicable solution to the addressed mobile RL problem. First, in the presence of the sensor energy-induced measurement missing phenomenon, an upper bound (UB) of the local localization error covariance is recursively acquired. Then, such a derived UB is minimized by suitably devising the desired local filter parameter. Subsequently, the covariance intersection fusion method is adopted to achieve the addressed RL problem. In the end, a simulation is conducted to verify the practicability of the developed RL scheme.

关键词： filtering methods in signal processing Sensing devices and transducers signal processing theory Mobile robots Sensor fusion Other topics in statistics Other topics in statistics

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Online current cut-off frequency self-tuning active damping speed controller for permanent magnet synchronous motors

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IET POWER ELECTRONICS 2022年第1期15卷 57-66页

作者： You, Sung Hyun Kim, Ki-Chan Kim, Seok-Kyoon Chosun Univ Dept Elect Engn Gwangju South Korea Hanbat Natl Univ Dept Elect Engn Daejeon South Korea Hanbat Natl Univ Dept Creat Convergence Engn Daejeon 34158 South Korea

This study suggests a dynamic current cut-off frequency-based pole-zero cancellation speed controller for permanent magnet synchronous motors (PMSMs). The proposed self-tuning algorithm automatically increases the current cut-off frequency during only the transient periods and restores it as approaching the steady-state operation. The outer loop control injects the active damping effect, resulting in a closed-loop order reduction by pole-zero cancellation from the particularly structured feedback gain. These two benefits contribute to the following advantages: (a) lowering the steady-state current cut-off frequency to improve the relative stability margin and (b) securing the capability of assigning the desired cut-off frequency to both the inner and outer loops in the first-order low-pass filter form. A 500-W PMSM experimental prototype platform confirms the effectiveness of the proposed controller.

关键词： permanent magnet synchronous motors angular velocity control Control of electric power systems Stability in control theory dynamic current cut-off frequency-based pole-zero cancellation speed controller Self-adjusting control systems steady-state current cut-off frequency outer loop control permanent magnet motors Velocity, acceleration and rotation control 500-W PMSM experimental prototype platform signal processing theory closed loop systems closed-loop order reduction first-order low-pass filter form Synchronous machines low-pass filters self-adjusting systems poles and zeros Control system analysis and synthesis methods filtering methods in signal processing vibration control Mechanical variables control control system synthesis damping feedback Drives online current cut-off frequency synchronous motor drives machine control stability relative stability margin self-tuning self-tuning active damping speed controller

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