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检索条件"主题词=Particle filter"

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Research on Receiver Autonomous Integrity Monitoring Algorithm using Genetic Algorithm Resampling particle filter

Research on Receiver Autonomous Integrity Monitoring Algorit...

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第四届中国卫星导航学术年会

作者： Pan He Chun Tan Huawen Huang Chongqing Insitute of Green and Intelligent Technology Chinese Academy of Sciences

With the rapid development of global navigation satellite system, Receiver Autonomous Integrity Monitoring （RAIM） has attracted attention from many researchers and there still are a lot of unsolved problems in this field. Traditional RAIM algorithms are built upon Kalman filter under the assumption that satellite signal noise follows Gaussian distribution. However, with the impact of ionospheric delay error and other factors, the measurement noise usually doesn’t follow Gaussian distribution. Under strong interference and harsh environmental conditions, particle filter is often employed to improve the efficiency of RAIM with non-Gaussian distribution errors. But those algorithms on particle filter are poor in convergence accuracy and stability because of particle degeneracy and this paper aims to provide a solution for particle degeneracy. Using the idea of approximate probability, this paper also takes use of particle filter in RAIM for fault detection and employs the idea of genetic operations to avoid particle degrading too early. Based on the classic particle filter procedure, simulation binary crossover operator, polynomial mutation operator and roulette wheeling selection method are used to produce new generation of particles from old generation in resampling process to increase particle diversity in state space as well as keeping good performance particles. The modified particle filter is then used in the fault detection and isolation process of RAIM with cumulative log likelihood ratio test. Finally, experiment are conducted using IGS tracking station observation data and the results showed that, our algorithm could be used detect and isolate faults under non-Gaussian noise environment, which proved the efficiency of our algorithm in RAIM. Comparing with RAIM algorithms based on traditional particle filters, our algorithm could improve the fault detection accuracy and convergence rate under non-Gaussian noise conditions as well as avoiding particle degenerac

关键词： Global navigation satellite system Receiver autonomous integrity monitoring particle filter Genetic Algorithms

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An adaptive particle filter （APF） for estimating states of nonlinear system with unknown parameters

An adaptive particle filter （APF） for estimating states of...

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第25届中国控制与决策会议

作者： Dexin Zhao Ting Li Zhiping Huang Shaojing Su Department of Instrument Science and Technology College of Mechatronics and Automation National University of Defense Technology

ISBN: (纸本)9781467355339

This paper presents an adaptive particle filter （APF） for estimating the states of the nonlinear system with unknown parameters. To implement this algorithm, the process noise covariance is adjusted according to the innovation-based adaptive estimation （IAE） approach, which only takes advantage of one state model without the requirement of knowing the parameters. In addition, the Maximum-A-Posterior （MAP） method is used to estimate the parameters to improving the performance of APF. Therefore, the APF can modify the prior distribution of the particles, and then alleviate the sample degeneracy problem which is common in particle filter （PF）. Numerical simulations of Logistic map are conducted to demonstrate the effectiveness of our proposed method.

关键词： particle filter IAE Nonlinear system State estimation Unknown parameters

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Infrared Dim Target Detection and Tracking Based on particle filter

Infrared Dim Target Detection and Tracking Based on Particle...

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第36届中国控制会议

作者： LIU Meiqin HUANG Zhicheng FAN Zhen ZHANG Senlin HE Yan College of Electrical Engineering Zhejiang University

Since the distance attenuation and the strong noise,Infrared Radiation(IR) dim target detection and tracking is challenging in recent *** this circumstance,conventional particle filter track-before-detect(PF-TBD) algorithm cannot detect and track *** this paper,a feasible two-layer particle filter based algorithm is proposed for this *** proposed algorithm can overcome the shortcomings of conventional particle filter(PF) *** introducing local particle swarm reset method and particle swarm optimization(PSO) algorithm,it is suitable for low-observable multi-target detection and tracking,and has a good performance of infrared dim target detection and tracking in simulations.

关键词： Low-Observable Multi-Target Dim Target particle filter

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An improved particle filter based on cuckoo search for visual tracking

An improved particle filter based on cuckoo search for visua...

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第30届中国控制与决策会议

作者： Fu Gui-xia Gao Ming-liang Zou Guo-feng Liu Wen-can Liu Li-na School of Electrical & Electronic Engineering Shandong University of Technology College of Electronics and Information Engineering Sichuan University

particle filter(PF) has been proven to be a powerful tool to solve visual tracking problem. However, the problem of sample impoverishment is a constraint of PF. To solve this problem, a cuckoo search-based particle filter is proposed. The particles in PF are optimized using cuckoo search. The meaningful particles are increased and can approximate the true state of the target more accurately. Experiments on visual tracking show that the proposed algorithm outperforms the standard particle filter in solve the visual tracking problems with various challenging conditions.

关键词： particle filter particle degradation Cuckoo search Target tracking

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Improved particle filter for Object Tracking

Improved Particle Filter for Object Tracking

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2011 Chinese Control and Decision Conference（CCDC）

作者： Tao Zhang is with College of Automation Electronic Engineering,Qingdao University of Sciences and Technology,Qingdao.Shumin Fei is with the Key Laboratory of Measurement and Control of Complex Systems of Engineering,Ministry of Education,Institute of Automation,Southeast University,Nanjing.

Robust real-time tracking of non-rigid objects is a challenging *** is a powerful feature for tracking deformable objects in image sequences with complex *** distribution is applied,as it is robust to partial occlusion,is rotation and scale invariant and computationally *** filter has been proven very successful for non-linear and non-Gaussian estimation tracking *** article presents the integration of color distributions into particle filtering.A target is tracked with a particle filter by comparing its histogram with the histograms of the sample positions using the Bhattacharyya ***,to solve the sample impoverishment （all particles collapse to a single point within a few iterations） in the particle-filter algorithm,a new resampling algorithm is proposed to tackle sample *** performance of the proposed filter is evaluated qualitatively on various real-world video *** experimental results show that the improved color-based particle filter algorithm can reduce sample impoverishment effectively and track the moving object very well.

关键词： particle filter Object Tracking Robust Tracking

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An Adaptive Feedback Turning SIR particle filter and Its Application on Active Fault-tolerant Control of Auxiliary Power Unit

An Adaptive Feedback Turning SIR Particle Filter and Its App...

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第37届中国控制会议

作者： Kai Peng Fan Yang Ranran Wu Yingjie Hu Jiashuai Liu Ding Fan School of Power and Energy Northwestern Polytechnical University Xi'an Aeronautics Computing Technique Research Institute AVIC

With the development of aero-engine control technology,the complexity of the control system is getting higher and higher,and the requirements of high security and reliability have made active fault-tolerant control more *** of the bad working environment,sensors are very prone to *** particle filter can be used to implement the estimation of the engine state parameters in the active fault-tolerant control and fault diagnosis of sensors,and an adaptive feedback correction mechanism is provided to improve particle degradation in SIR particle filter,which will improve the estimation precision of the engine condition measured by sensors that may *** An APU,exhaust gas temperature is originally adopted for closed-loop control in the starting process,and a novel closed-loop control based on the rotor acceleration is designed to reconstruct the control law when the exhaust gas temperature sensor fails while the exhaust temperature value estimated by the particle filter is used for over-temperature protection *** simulations show that there is no severe jump in the engine states after exhaust temperature malfunctions and the switching process is stable,and the starting time and exhaust temperature meet the design requirements.

关键词： SIR particle filter APU Active Fault-tolerant Control

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A Robust Tracking Method Based on particle filter via Multi-Cues

A Robust Tracking Method Based on Particle Filter via Multi-...

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2011 13th IEEE Joint International Computer Science and Information Technology Conference(JICSIT 2011)

作者： Jia Li Chongqing Technology and Business Institute Chongqing 400052,ChinaYu Lu The Second Research Institute of Civil Aviation Administration of China Chengdu 610041,China

In view of the issues of multi-cues selection and fusion in the object tracking,a multi-cues fusion tracking method based on the particle filter is proposed in this paper. This method utilizes the combination between the grey histogram and the SVD(Singular Value Decomposition) invariance as the criteria of the similarity of each particle to enhance the stability.A feedback mechanism is also established according to the contribution each cue to the final result so that the parameters can be adaptively modified in the process of multi-cues fusion,which helps to guarantee the reliability. Experimental results show the proposed method is superior to the method using particle filter based on the common multi- cues fusion.

关键词： Object tracking particle filter Multi-cues fusion grey histogram SVD(Singular Value Decomposition) invariance

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Multiple Target Tracking Using particle filter Based Multi-scan Joint Probabilistic Data Association filter

Multiple Target Tracking Using Particle Filter Based Multi-s...

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第三十届中国控制会议

作者： LIU Jing~1,HAN Chongzhao~1,HU Yu~2 1.School of Electronics and Information Engineering,Xi''an JiaoTong University,Xi''an 710049,P.R.China 2.Schools of Aeronautics,Northwestern Polytechnical University,710072,P.R.China

＜正＞In this paper,a particle filter based multi-scan JPDA filter is proposed to deal with the data association problem in multiple target *** the proposed multi-scan JPDA algorithm,the distributions of interest are the marginal filtering distributions for each of the targets,and these distributions are approximated with *** multi-scan JPDA algorithm examines the joint association events in a multi-scan sliding window and calculates the marginal posterior probability based on the multi-scan joint association *** proposed algorithm is illustrated via an example involving tracking of two slowly maneuvering targets based on resolved measurements.

关键词： Multiple Target Tracking particle filter Multi-scan JPDA

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Target tracking based on particle filter algorithm with multiple cues fusion

Target tracking based on particle filter algorithm with mult...

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第26届中国控制与决策会议

作者： Tao Zhang Shumin Fei College of Automation Electronic Engineering Qingdao University of Sciences and Technology School of automation Southeast University

ISBN: (纸本)9781479937097

A robust tracking algorithm based on the particle filter with multi-cue adaptive fusion is proposed which can overcome the shortcoming of single visual cue in complex environments. The color and the texture based on the discrete wavelet transform（DWT） are used to describe the tracking target. The weights are adaptively adjusted using the democratic integration according to the current tracking situations, which increases the reliability of observation and improves the robustness of observation model. Due to the use of reliable cues for tracking, the shortcoming of single cue in complex scenes is improved. Meanwhile, the noise variance of each cue is updating to increase the discrimination of each cue. During designing particle filter based tracking algorithm, the likelihood model is constructed depending on adaptive cue fusion mechanism, thus enhancing the robustness of tracking algorithm. The experiments show that the result of better tracking are obtained in circumstances that the target is arbitrarily moving or rotating, partially or completely occlusion, as well as the light changes. When the target with similar color appears, the tracking algorithm with the texture model can distinguish the target with the background.

关键词： particle filter Multiple cue data fusion target tracking

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Research of GNSS Spoofer Localization using Information Fusion Based on particle filter

Research of GNSS Spoofer Localization using Information Fusi...

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第九届中国卫星导航学术年会

作者： Shunshun Shang Hong Li Mingquan Lu Department of Electronic Engineering Tsinghua University

A spoofer localization algorithm using information fusion based on the particle filter(PF) is proposed. There are many researches about the jammer localization, but less researches about the spoofer localization. The jamming signal, whose structure is unknown to us, usually is above the thermal noise. According to the effect of jamming signal bandwidth on the measuring of time and frequency, we cannot obtain the precise measurements of TDOA and FDOA simultaneously. Thus, we usually cannot implement the information fusion of time and frequency in the jammer localization. Besides, we cannot locate the spoofer directly with the method of jammer localization, because the spoofing signal is usually below the noise. However, we can obtain the precise measurements of time and frequency of the spoofing signal at the same time because the spoofing signal needs to disguise as the true GNSS signal. Based on this, we propose a localization algorithm using the information fusion of TDOA and FDOA. We couple the position and velocity together by the PF, which will not introduce the linearization error. By the analysis of the CRLB, we find the information fusion can improve the system performance. To verify the algorithm, we simulate and analyze the results of PF and the weighted least squares(WLS). Compared to the WLS without information fusion, the PF has a better performance of locating and tracking, which can work properly under the circumstances where the spatial layout is poor, the number of base stations is small and the measuring errors are large.

关键词： GNSS Information Fusion particle filter Localization CRLB TDOA FDOA

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