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Mitigating Quantization Effects on distributed sensor fusion: A Least Squares Approach

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2018年第13期66卷 3459-3474页

作者： Zhu, Shanying Chen, Cailian Xu, Jinming Guan, Xinping Xie, Lihua Johansson, Karl Henrik Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Arizona State Univ Ira A Fulton Sch Engn Tempe AZ 85281 USA Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore KTH Royal Inst Technol Sch Elect Engn ACCESS Linnaeus Ctr S-10044 Stockholm Sweden

In this paper, we consider the problem of sensor fusion over networks with asymmetric links, where the common goal is linear parameter estimation. For the scenario of bandwidth-constrained networks, existing literature shows that nonvanishing errors always occur, which depend on the quantization scheme. To tackle this challenging issue, we introduce the notion of virtual measurements and propose a distributed solution LS-DSFS, which is a combination of a quantized consensus algorithm and the least squares approach. We provide detailed analysis of the LS-DSFS on its performance in terms of unbiasedness and mean square property. Analytical results show that the LS-DSFS is effective in smearing out the quantization errors, and achieving the minimum mean square error (MSE) among the existing centralized and distributed algorithms. Moreover, we characterize its rate of convergence in the mean square sense and that of the mean sequence. More importantly, we find that the LS-DSFS outperforms the centralized approaches within a moderate number of iterations in terms of MSE, and will always consume less energy and achieve more balanced energy expenditure as the number of nodes in the network grows. Simulation results are presented to validate theoretical findings and highlight the improvements over existing algorithms.

关键词： distributed sensor fusion bandwidth-constrained network asymmetric links least squares approach

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On distributed sensor fusion in Batteryless Intermittent Networks 15

On Distributed Sensor Fusion in Batteryless Intermittent Net...

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15th Annual International Conference on distributed Computing in sensor Systems (DCOSS)

作者： Yildirim, Kasim Sinan Pawelczak, Przemyslaw Ege Univ Dept Comp Engn Izmir Turkey Delft Univ Technol Embedded & Networked Syst Delft Netherlands

ISBN: (纸本)9781728105703

distributed and collaborative computation has never been considered before in networks of batteryless sensors. This can bring many advantages for applications (e.g. longer transmission ranges, lower network costs), however introducing new research challenges. In this paper, we focus on the well-known distributed sensor fusion but in an intermittently-powered batteryless sensor network. The goal is to estimate a parameter collaboratively by considering individual sensor measurements. We show that, even though the nodes stop operation with high probability due to random power failures and they neither communicate with their neighbors nor perform computation most of the time, the simplest implementation of the fully-distributed sensor fusion based on average consensus improves the overall estimation quality of the network considerably. In the light of this, we anticipate that if harvested energy is used efficiently so that nodes have more opportunity to receive and send packets, existing fully-distributed protocols can be implemented with tiny modifications in networks of batteryless sensors.

关键词： Batteryless sensors Intermittent communication distributed sensor fusion

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A LEAST SQUARE APPROACH FOR distributed sensor fusion IN BANDWIDTH-CONSTRAINED sensor NETWORKS 41

A LEAST SQUARE APPROACH FOR DISTRIBUTED SENSOR FUSION IN BAN...

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41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Zhu, Shanying Xu, Jinming Chen, Cailian Guan, Xinping Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

ISBN: (纸本)9781479999880

In this paper, we consider a simple model of distributed sensor fusion problem in sensor networks with asymmetric links, where the common goal is linear parameter estimation. For the realistic scenario of bandwidth-constrained networks, we propose a least square approach, based on distributed quantized consensus algorithms, to compute the ideal centralized sample mean estimate. Analytical results show that the proposed approach is effective in smearing out the quantization errors, and outperforms the centralized approaches with respect to the estimation performance. Simulation results are provided to validate the analytical results.

关键词： distributed sensor fusion bandwidth-constrained network asymmetric links consensus algorithm

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Feature-based map merging with dynamic consensus on information increments

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AUTONOMOUS ROBOTS 2015年第3期38卷 243-259页

作者： Aragues, Rosario Sagues, Carlos Mezouar, Youcef Clermont Univ CNRS Inst Pascal UMR 6602 F-63000 Clermont Ferrand France Univ Zaragoza Inst Invest Ingn Aragon Zaragoza 50018 Spain

We study the problem of feature-based map merging in robot networks. Along its operation, each robot observes the environment and builds and maintains a local map. Simultaneously, each robot communicates and computes the global map of the environment. The communication between the robots is range-limited. Our contributions are the proposal and careful study of the properties of an algorithm that considers separately robot poses and features positions, and that reaches consensus on the latest global map using the map increments between the previous and the current time steps. We give proofs of unbiasedness and consistency of this global map for all the robots, at each iteration. Our algorithm is fully distributed and does not rely on any particular communication topology. Under mild connectivity conditions on the communication graph, our merging algorithm asymptotically converges to the global map. The proposed approach has been experimentally validated using real RGB-D images.

关键词： distributed robot systems Networked robots distributed sensor fusion Mapping

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distributed Kalman filtering: a bibliographic review

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IET CONTROL THEORY AND APPLICATIONS 2013年第4期7卷 483-501页

作者： Mahmoud, Magdi S. Khalid, Haris M. King Fahd Univ Petr & Minerals Dept Syst Engn Dhahran 31261 Saudi Arabia

In recent years, a compelling need has arisen to understand the effects of distributed information structures on estimation and filtering. In this study, a bibliographical review on distributed Kalman filtering (DKF) is provided. The study contains a classification of different approaches and methods involved to DKF. The applications of DKF are also discussed and explained separately. A comparison of different approaches is briefly carried out. Focuses on the contemporary research are also addressed with emphasis on the practical applications of the techniques. An exhaustive list of publications, linked directly or indirectly to DKF in the open literature, is compiled to provide an overall picture of different developing aspects of this area.

关键词： distributed sensors Kalman filters sensor fusion distributed sensor fusion DKF classification methods distributed information structures bibliographic review distributed Kalman filtering distributed sensors Kalman filters sensor fusion distributed sensor fusion DKF classification methods distributed information structures bibliographic review distributed Kalman filtering

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Performance analysis of averaging based distributed estimation algorithm with additive quantization model

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AUTOMATICA 2017年 80卷 95-101页

作者： Zhu, Shanying Liu, Shuai Soh, Yeng Chai Xie, Lihua Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

In this paper, we consider the distributed sensor fusion problem over sensor networks under directed communication links and bandwidth constraint. We investigate the impact of the additive quantization model on the proposed two-stage averaging based algorithm. Existing works on the effect of the additive model show that convergence can be guaranteed only if the quantization error variances form a convergent series. We show that the proposed algorithm achieves the performance of the optimal centralized estimate even if the quantization error variances are not vanishing. This is guaranteed by establishing a law of the iterated logarithm for weighted sums of independent random vectors. Moreover, an explicit bound of the convergence rate of the proposed algorithm is given to quantify its almost sure performance. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： distributed sensor fusion Additive quantization model Directed topology Log log law

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Cooperative control and communication of intelligent swarms:a survey

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Control Theory and Technology 2020年第2期18卷 114-134页

作者： Kun HOU Yajun YANG Xuerong YANG Jiazhe LAI Department of Aerospace Science and Technology University o f Aerospace EngineeringBeijing 101416China ZSchool of Aeronautics and Astronautics Sun Yat-Sen UniversityGuangzhou Guangdong 510275China

Individuals exchange information,experience and strategy based on *** is the basis for individuals to form swarms and the bridge of swarms to realize cooperative *** this paper,the multirobot swarm and its cooperative control and communication methods are reviewed,and we summarize these methods from the task,control,and perception *** on the research,the cooperative control and communication methods of intelligent swarms are divided into the following four categories:task assignment based methods(divided into market-based methods and alliance based methods),bio-inspired methods(divided into biochemical information inspired methods,vision based methods and self-organization based methods),distributed sensor fusion and reinforcement learning based methods,and we briefly define each method and introduce its basic *** on WOS database,we divide the development of each method into several stages according to the time distribution of the literature,and outline the main research content of each ***,we discuss the communication problems of intelligent swarms and the key issues,challenges and future work of each method.

关键词： Intelligent swarm cooperative control communication task assignment bio-inspired methods distributed sensor fusion reinforcement learning

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Consensus-based distributed Variational Multi-object Tracker in Multi-sensor Network 12

Consensus-based Distributed Variational Multi-object Tracker...

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12th sensor Signal Processing for Defence Conference (SSPD)

作者： Li, Qing Gan, Runze Godsill, Simon Univ Cambridge Dept Engn Cambridge England

ISBN: (纸本)9798350337327

The growing need for accurate and reliable tracking systems has driven significant progress in sensor fusion and object tracking techniques. In this paper, we design two variational Bayesian trackers that effectively track multiple targets in cluttered environments within a sensor network. We first present a centralised sensor fusion scheme, which involves transmitting sensor data to a fusion center. Then, we develop a distributed version leveraging the average consensus algorithm, which is theoretically equivalent to the centralised sensor fusion tracker and requires only local message passing with neighbouring sensors. In addition, we empirically verify that our proposed distributed variational tracker performs on par with the centralised version with equal tracking accuracy. Simulation results show that our distributed multi-target tracker outperforms the suboptimal distributed sensor fusion strategy that fuses each sensor's posterior based on arithmetic sensor fusion and an average consensus strategy.

关键词： distributed sensor fusion multiple object tracking variational inference average consensus data association

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Decentralised Gradient-based Variational Inference for Multi-sensor fusion and Tracking in Clutter 27

Decentralised Gradient-based Variational Inference for Multi...

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27th International Conference on Information fusion (fusion)

作者： Li, Qing Gan, Runze Godsill, Simon Univ Cambridge Engn Dept Cambridge England

ISBN: (纸本)9798350371420;9781737749769

This paper investigates the task of tracking multiple objects in clutter under a distributed multi-sensor network with time-varying connectivity. Designed with the same objective as the centralised variational multi-object tracker, the proposed method achieves optimal decentralised fusion in performance with local processing and communication with only neighboring sensors. A key innovation is the decentralised construction of a locally maximised evidence lower bound, which greatly reduces the information required for communication. Our decentralised natural gradient descent variational multi-object tracker, enhanced with the gradient tracking strategy and natural gradients that adjusts the direction of traditional gradients to the steepest, shows rapid convergence. Our results verify that the proposed method is empirically equivalent to the centralised fusion in tracking accuracy, surpasses suboptimal fusion techniques with comparable costs, and achieves much lower communication overhead than the consensus-based variational multi-object tracker.

关键词： distributed sensor fusion multiple object tracking data association variational inference decentralised gradient descent natural gradient decentralised optimisation

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UAS Collision Warning and Passive sensor fusion Algorithms for Multiple Acoustic Transient Emitter Localization

UAS Collision Warning and Passive Sensor Fusion Algorithms f...

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作者： Dou, Wenbo University of Connecticut

学位级别：Ph.D., Doctor of Philosophy

This dissertation considers two important topics in the area of estimation, target tracking and sensor fusion. The first topic is closest point of approach (CPA) prediction for unmanned aircraft systems (UAS) collision warning and the second topic is passive sensor fusion for multiple acoustic transient emitter *** operate within a controlled airspace, UAS must have the capability to sense and avoid collisions with non-cooperative aircraft. This dissertation presents an inexpensive system design and develops an algorithm for estimating the CPA between the ownship and the intruder and a collision warning scheme using only bistatic range and range rate measurements from a multistatic *** it is vital for soldiers to be able to accurately localize sources of hostile fire in the battlefield for situational awareness and threat assessment, this dissertation develops both centralized and distributed passive sensor fusion algorithms to accurately estimate the number of acoustic transient emitters and their locations using bearing and time of arrival measurements.

关键词： multistatic radar UAS collision warning passive sensor fusion multi-target localization multi-shooter localization distributed sensor fusion distributed set consensus distributed data association

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