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Optimal H₂ filtering for sampled-data systems with measurement delays and packet dropouts

IET signal processing 2021年第3期15卷 182-194页

作者： Wang, Wei Han, Chunyan Univ Jinan Sch Elect Engn Jinan Shandong Peoples R China

This study examines the H-2 filtering problem for sampled-data systems that are subject to measurement delays and packet dropouts. The phenomenon of packet dropout is different for each observation component and is described as an independent and identically distributed Bernoulli process, which is more general than the scalar packet dropout case. The reorganized observation technique is introduced herein to address the time delays in the observations. An optimal filter is constructed using a deterministic continuous-time system with finite jumps, where the filter gains are determined by integrating a specific continuous-time Riccati equation with finite jumps, based on a suitable algebraic Lyapunov equation. Compared with the discrete-time filter, the optimal filter can provide the state estimates of the measurement sampling intervals and measurement sampling moments. Two simulation examples are explored to demonstrate the effectiveness of the proposed method.

关键词： finite jumps independent distributed Bernoulli process Lyapunov methods scalar packet dropout case continuous-time system filtering problem discrete time filters optimal filter Distributed parameter control systems continuous time systems state estimation Riccati equations Control system analysis and synthesis methods sampled data systems algebraic Lyapunov equation Algebra measurement sampling intervals continuous-time Riccati equation delays filter gains filtering methods in signal processing discrete-time filter Discrete control systems time delays signal processing theory Stability in control theory observation component measurement delays measurement sampling moments identically distributed Bernoulli process algebra reorganized observation technique filtering theory state estimates sampled-data systems

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Efficiency analysis of polynomial filtering algorithms in navigation data processing for a class of nonlinear discrete dynamical systems

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IET CONTROL THEORY AND APPLICATIONS 2021年第2期15卷 248-259页

作者： Stepanov, O. A. Vasiliev, V. A. Basin, M., V Tupysev, V. A. Litvinenko, Y. A. JSC Concern CSRI Elektropribor 30 Malaya Posadskaya Str St Petersburg 197046 Russia ITMO Univ St Petersburg Russia Autonomous Univ Nuevo Leon San Nicolas de los Gar Dept Phys & Math Sci Monterrey Mexico

A polynomial filtering algorithm is designed for estimating a Markov sequence based on linear measurements. The feature of the estimation problem is that the Markov sequence is described by a nonlinear shaping filter, which is a second-order polynomial with respect to the state vector components. The algorithm efficiency is illustrated by three examples of navigation data processing. It is shown that the polynomial filter provides accuracy close to the best potential one calculated using the particle filter. At the same time, the amount of computation required to implement this algorithm is much smaller than that for the particle filter. In addition, the polynomial filter provides a consistent calculated accuracy characteristic.

关键词： filtering methods in signal processing signal processing theory Interpolation and function approximation (numerical analysis) Markov processes Interpolation and function approximation (numerical analysis) Markov processes

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A novel direct field-oriented control strategy for fault-tolerant control of induction machine drives based on EKF

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IET ELECTRIC POWER APPLICATIONS 2021年第8期15卷 979-997页

作者： Tabasian, Rahemeh Ghanbari, Mahmood Esmaeli, Abdolreza Jannati, Mohammad Islamic Azad Univ Gorgan Branch Dept Elect Engn Gorgan Golestan Iran Nucl Sci & Technol Res Inst Plasma & Nucl Fus Res Sch Tehran Iran

This article presents a novel Direct Field-Oriented Control (DFOC) strategy for Fault-Tolerant Control (FTC) of wye-connected 3-Phase Induction Machine (3-PIM) drives under the stator winding open-phase failure. In the proposed control strategy, instead of flux measurement, an Extended Kalman Filter (EKF) for flux estimation is used. The introduced controller with minor modifications can be used during normal and stator winding open-phase failure conditions. With the proposed DFOC system, the speed and torque pulsations that normally happen during the open-phase failure can be reduced. The performances of the proposed EKF-based DFOC strategy and the conventional control strategy for a faulted machine using simulations and experiments under different operation conditions are compared. Simulation and experimental results demonstrated an important improvement in speed and torque pulsations through this type of fault. Results also confirmed the superiority of the proposed EKF-based DFOC scheme over the conventional control scheme to balance the faulted machine phase currents.

关键词： fault-tolerant control machine vector control Control of electric power systems flux measurement Kalman filters direct field-oriented control strategy wye-connected 3-phase induction machine stator winding open-phase failure 3-PIM torque pulsations extended Kalman filter Mechanical variables control open-phase failure conditions flux estimation speed pulsations faulted machine phase currents torque control nonlinear filters filtering methods in signal processing FTC Asynchronous machines stators fault tolerant control induction motor drives EKF-based DFOC scheme induction machine drives Drives

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Dechirp-receiving radar target detection based on generalized Radon-Fourier transform

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IET RADAR SONAR AND NAVIGATION 2021年第9期15卷 1096-1111页

作者： You, Pengjie Ding, Zegang Liu, Siyuan Zhang, Guangwei Beijing Inst Technol Sch Informat & Elect Beijing Peoples R China Beijing Key Lab Embedded Real Time Informat Proc Beijing Peoples R China

The dechirp-receiving radar measures range by the frequency difference between the target echo and the reference signal. It can operate at a low sampling frequency while transmitting a wideband signal, which simplifies the radar hardware. However, when detecting high-speed and highly maneuvering targets, residual video phase (RVP), frequency mismatch, frequency modulation (FM) rate mismatch, and across range-Doppler unit (ARDU) problems occur after dechirp receiving, which cause difficulties in integrating the target echo and result in severe performance loss. To solve these problems, the dechirp generalized Radon-Fourier transform (DGRFT) and an algorithm for its fast implementation are proposed. The DGRFT compensates for the frequency and FM rate mismatch in the fast-time domain and the RVP in the fast-time frequency domain, and then implements joint envelope and phase compensations to overcome the ARDU phenomenon. After these compensations, the target echo can be effectively integrated. Experiments with simulated and measured data show that the performance of the DGRFT is better than that of the conventional moving target detector.

关键词： radar signal processing Fourier transforms conventional moving target detector frequency mismatch Radon transforms radar imaging fast-time frequency domain low sampling frequency frequency difference dechirp-receiving radar target detection radar hardware Doppler radar reference signal phase compensations radar tracking Optical, image and video signal processing Radar equipment, systems and applications dechirp generalized Radon-Fourier transform wideband signal radar resolution range-Doppler unit problems filtering methods in signal processing residual video phase DGRFT compensates target echo frequency modulation synthetic aperture radar severe performance loss frequency modulation rate mismatch joint envelope detecting high-speed frequency-domain analysis radar measures range RVP object detection radar detection target tracking dechirp receiving filtering theory airborne radar fast-time domain

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Interest point detection from multi-beam light detection and ranging point cloud using unsupervised convolutional neural network

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IET IMAGE processing 2021年第2期15卷 369-377页

作者： Yin, Deyu Zhang, Qian Liu, Jingbin Liang, Xinlian Wang, Yunsheng Chen, Shoubin Maanpaa, Jyri Hyyppa, Juha Chen, Ruizhi Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan 430079 Peoples R China Finnish Geospatial Res Inst Dept Remote Sensing & Photogrammetry Masala Finland Finnish Geospatial Res Inst Ctr Excellence Laser Scanning Res Masala Finland Hubei Univ Technol Sch Econ & Management Wuhan Peoples R China

Interest point detection plays an important role in many computer vision applications. This work is motivated by the light detection and ranging odometry task in autonomous driving. Existing methods are not capable of detecting enough interest points in unstructured scenarios where there are little constructions or trees around, and correspondingly light detection and ranging odometry will fail to continuous localisation. An interest point detector is proposed for detecting interest points from multi-beam light detection and ranging point cloud using unsupervised convolutional neural network. The point cloud is projected into a two-dimensional structured data according to the scanning geometry. Then the convolutional neural network filters trained in an unsupervised manner are used to generate a local feature map with the two-dimensional structured data as input. Finally, interest points are obtained by extracting the grids that have significant differences with their neighbour grids. Based on an odometry benchmark, the experiments show that the proposed interest point detector can capture more local details, which contributes to more than 16% error decrease in point cloud registration in highway scenes.

关键词： Optical, image and video signal processing filtering methods in signal processing Mobile robots Computer vision and image processing techniques

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Mixed Poisson Gaussian noise reduction in fluorescence microscopy images using modified structure of wavelet transform

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IET IMAGE processing 2021年第7期15卷 1383-1398页

作者： Rasal, Tushar Veerakumar, Thangaraj Subudhi, Badri Narayan Esakkirajan, Sankaralingam Natl Inst Technol Goa Dept Elect & Commun Engn Ponda 403401 Goa India Indian Inst Technol Jammu Dept Elect Engn Nagrota 181221 Jammu & Kashmir India PSG Coll Technol Dept Instrumentat & Control Syst Engn Coimbatore 641004 Tamil Nadu India

Fluorescence microscopy is an important investigation tool of discoveries in the field of biological sciences where the imaging phenomena are limited by the noise. This paper introduces the integration of biorthogonal wavelet filters along with mixed Poisson-Gaussian unbiased risk estimate (MPGURE) based subband adaptive thresholding function for the restoration of low photon count microscopy images. The proposed algorithm consists of four steps. In the first step, variance stabilization transform along with a multi-scale Wiener filtering approach is used to filter out the noise and blurring effect. In the second step, deconvolved images are further decomposed by the biorthogonal wavelet filters. The modified wavelet subband structure is used for the identification of noisy and noise-free subbands. In the next stage, different noisy coefficients are thresholded using the MPGURE-based thresholding operation. The different thresholded images are combined along with different optimum coefficients. Finally, inverse variance stabilization transformation is applied to obtain the final restored output. Performance of the proposed algorithm is tested on 14 different benchmark image data sets with performance evaluation measures like signal-to-noise ratio, peak signal-to-noise ratio, mean structural similarity index measur, and correlation coefficient. Simulation results of the proposed algorithm claim better results than other state-of-the-art techniques.

关键词： Optical, image and video signal processing filtering methods in signal processing Interpolation and function approximation (numerical analysis) Computer vision and image processing techniques Integral transforms Other topics in statistics Interpolation and function approximation (numerical analysis) Integral transforms Other topics in statistics Patient diagnostic methods and instrumentation Biology and medical computing

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Real-time long-term tracking with reliability assessment and object recovery

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IET IMAGE processing 2021年第4期15卷 918-935页

作者： Liu, Jun Ye, Ping Zhang, Xingchen Xiao, Gang Shanghai Jiao Tong Univ Sch Aeronaut & Astronaut Shanghai 200240 Peoples R China Sichuan Univ Sci & Engn Sch Automat & Informat Engn Zigong Sichuan Peoples R China

In recent years, many visual tracking algorithms based on discriminative correlation filters have been proposed and proved to be successful in short-term tracking. However, most algorithms do not handle long-term tracking well due to factors such as occlusion and deformation. The aim of this paper is to propose a long-term tracking method with reliability assessment and object recovery. First, the relationship between the overlap rate and the response value is extensively studied, and then from the perspective of the time axis, the tracking process is evaluated by the fluctuation trend of the continuous response value. In the object recovery mechanism, we propose to alternately use local search and global search to improve the efficiency of detection. To this end, a sliding window is designed for cyclic shifting in the local region to achieve dense sampling within the region of interest, and EdgeBox is used in the global search to achieve target detection. Further, flexible switching between local search and global search is achieved by the difference in displacement of the object. Extensive experimental results on several benchmark datasets demonstrate that the proposed long-term tracker can achieve state-of-the-art accuracy with real-time speed of about 27 frames per second.

关键词： Optical, image and video signal processing filtering methods in signal processing Computer vision and image processing techniques Video signal processing

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Performance analysis of M-ary OQAM/FBMC with impact of nonlinear distortion over compound Rician K-factor unshadowed/κ-μ shadowed fad ing channels

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IET COMMUNICATIONS 2021年第1期15卷 60-77页

作者： Al-Rubaye, Ghanim A. Mustansiriyah Univ Coll Engn Dept Elect Engn Baghdad Iraq

In this paper, the bit error rate (BER) analyses of M-ary offset QAM for filter bank-based multicarrier (M-ary OQAM/FBMC) contaminated by nonlinear distortion (NLD) are investigated over different channel scenarios, such as unshadowed line-of-sight (LOS) Rician K-factor (RK-f) fading channel, non-line-of-sight (NLOS) kappa-mu shadowed fading model and compound unshadowed/shadowed fading model. NLDs produced by high power amplifier (HPA) play the main role in the degradation of the BER in multicarrier communication systems over fading channels. Therefore, the complex Gaussian noise and the complex NLD are modelled as an independent parameter by using Bussgang's theorem. In this work, closed-form of BER, ergodic capacity, outage probability and outage capacity probability expressions for the M-ary OQAM/FBMC system over different unshadowed/shadowed fading channel scenarios and environments with amplitude (AM) and phase (PM) distortion induced by the HPA have been theoretically derived as general expressions without numerical integration method. Extensive Monte-Carlo simulation results demonstrate a closed agreement with all analytical derived expressions.

关键词： Reliability Modulation and coding methods filtering methods in signal processing Radio links and equipment Monte Carlo methods Error statistics (inc. error probability)

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A new two-stage method for single image rain removal

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IET IMAGE processing 2021年第2期15卷 492-503页

作者： Zhu, Jian Liu, Peiyu Luo, Yu Ling, Jie Wu, Enhua Guangdong Univ Technol Sch Comp Sci Guangzhou Peoples R China Univ Macau Fac Sci & Technol Taipa Macao Peoples R China Chinese Acad Sci Inst Software State Key Lab Comp Sci Beijing Peoples R China

Compared with video de-raining, single image de-raining is more technically difficult due to the lack of temporally redundant information. This paper proposes a new two-stage method for single image de-raining. In the first stage, the authors develop an effective two-step model to detect the rain streaks by taking pixel intensity, and direction of rain streaks as priors. In the second stage, the rain repair process is performed at the patch level. The authors first define a way to search for similar patches of each patch, and then group the similar patches together to form a matrix. Finally, a low-rank matrix completion technique is utilized to recover the rain-stained pixels based on the rain map obtained from the first stage. Compared with several state-of-the-art methods, authors' proposed method is competitive in terms of the abilities of removing rain streaks, and preserving image details.

关键词： image representation rain repair process rain map filtering methods in signal processing image enhancement image reconstruction video signal processing Computer vision and image processing techniques single image de-raining image restoration geophysical image processing two-stage method Optical, image and video signal processing image segmentation single image rain removal image sequences temporally redundant information rain streaks matrix algebra rain-stained pixels filtering theory Video signal processing image denoising Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research rain preserving image details

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A critical comparison on attitude estimation: From gaussian approximate filters to coordinate-free dual optimal control

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IET CONTROL THEORY AND APPLICATIONS 2021年第10期15卷 1297-1313页

作者： Koumpis, N. P. Panagiotou, P. A. Arvanitakis, I. Delft Ctr Syst & Control Fac Mech Maritime & Mat Engn Mekelweg 2 NL-2628 CD Delft Netherlands Univ Sheffield Fac Elect & Elect Engn Sheffield S Yorkshire England Coventry Univ Fac Engn Environm & Comp Coventry W Midlands England

This paper conveys attitude and rate estimation without rate sensors by performing a critical comparison, validated by extensive simulations. The two dominant approaches to facilitate attitude estimation are based on stochastic and set-membership reasoning. The first one mostly utilizes the commonly known Gaussian-approximate filters, namely the EKF and UKF. Although more conservative, the latter seems to be more promising as it considers the inherent geometric characteristics of the underline compact state space and accounts-from first principles-for large model errors. The set-theoretic approach from a control point of view is addressed, and it is shown that it can overcome reported deficiencies of the Bayesian architectures related to this problem, leading to coordinate-free optimal filters. Lastly, as an example, a modified predictive filter is derived on the tangent bundle of the special orthogonal group TSO(3).

关键词： filtering methods in signal processing signal processing theory Spatial variables control Other topics in statistics Combinatorial mathematics Other topics in statistics Combinatorial mathematics Optimal control

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