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3rd IEEE International Conference on Computer and Communications (ICCC)

作者： Zhao, Qi Zhao, Huailin Zhu, Bo Shanghai Inst Technol Sch Elect & Elect Engn Shanghai Peoples R China Tsinghua Univ State Key Lab Intelligent Technol & Syst Dept Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9781509063529

Accurate and precise frequency synchronization is an essential requirement for different areas in avionics system. Emerging practice for time synchronization is to utilize Time triggered Ethernet(TTE) network which is peer-to-peer network since it is highly deterministic. However, for some situations, TTE network contains uncertain communication delay, such as the node of the TTE network has an external clock source or contains a controller other than the TTE controller etc. This problem can be overcome by applying IEEE1588v2 synchronization protocol to TTE network. In this paper, the feasibility and the synchronization error of the algorithm not only are analyzed theoretically but also are verified from the simulation point of view. Specifically, the first step is the construction of model of the clock offset and clock drift state space between master and slave clocks. Subsequently, the kalman filter algorithm is used to estimate the clock offset and skew between master and slave clock and compensate for its. Lastly, the algorithm's performance is evaluated using simulation. In the simulation process, above method is applied to the TTE multi-hop system, considering the effect of timestamp accuracy on the synchronization effect. The result of this simulation shows that, the algorithm with the 1588 synchronization protocol on the TTE network has more accuracy and stability than without it, when the timestamp accuracy is microsecond or higher.

关键词： time synchronization TTEthernet protocol IEEE1588 protocol TTE multi-hop network Clock drift kalman filter algorithm

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Real-time Vehicle Detection and Tracking Based on YOLOv3 Pruning Model 33

Real-time Vehicle Detection and Tracking Based on YOLOv3 Pru...

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33rd Chinese Control and Decision Conference (CCDC)

作者： Lin, Mingxiu Li, Jiayi Zhang, Jiaxin Li, Xinghui Ji, Shiyao He, Yunli Northeastern Univ Coll Informat Sci & Engn Shenyang 110004 Peoples R China

ISBN: (纸本)9781665440899

Real-time detection and tracking of vehicles is very important in the field of automatic driving. In this paper, a YOLOv3 network based on pruning algorithm is proposed to solve the problem of real-time vehicle detection. Through reducing the number of channels and layers in the backbone network, the computation of the model is reduced. And thus, the rate of detection is greatly increased. On the basis of vehicle detection, the real-time tracking of multiple vehicle targets is completed by using kalman filter algorithm for prediction and Hungarian algorithm for data association. The experimental results show that compared with the original YOLOv3 network, the model size is compressed by 95% to 11.25 MB and the detection rate is doubled to 128.1 frames/s while the average accuracy is basically unchanged. The detection and tracking frame rate of the whole algorithm is 18fps, and the recall is 98.5%. The algorithm also has strong robustness on complex traffic roads, and can basically realize real-time detection and tracking of road vehicles.

关键词： Real-time detection and tracking pruning algorithm kalman filter algorithm Hungarian algorithm

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State Estimation for Ellipsoidally Constrained Dynamic Systems with Set-membership Pseudo Measurements

State Estimation for Ellipsoidally Constrained Dynamic Syste...

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IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

作者： Noack, Benjamin Baum, Marcus Hanebeck, Uwe D. Karlsruhe Inst Technol Inst Anthropomat & Robot Intelligent Sensor Actuator Syst Lab ISAS D-76021 Karlsruhe Germany

ISBN: (纸本)9781479977727

In many dynamic systems, the evolution of the state is subject to specific constraints. In general, constraints cannot easily be integrated into the prediction-correction structure of the kalman filter algorithm. Linear equality constraints are an exception to this rule and have been widely used and studied as they allow for simple closed-form expressions. A common approach is to reformulate equality constraints into pseudo measurements of the state to be estimated. However, equality constraints define deterministic relationships between state components which is an undesirable property in kalman filtering as this leads to singular covariance matrices. A second problem relates to the knowledge required to identify and define precise constraints, which are met by the system state. In this article, ellipsoidal constraints are introduced that can be employed to model a bounded region, to which the system state is constrained. This concept constitutes an easy-to-use relaxation of equality constraints. In order to integrate ellipsoidal constraints into the kalman filter structure, a generalized filter framework is utilized that relies on a combined stochastic and set-membership uncertainty representation.

关键词： kalman filters covariance matrices state estimation stochastic processes kalman filter algorithm closed-form expressions easy-to-use relaxation ellipsoidal constraints ellipsoidally constrained dynamic systems equality constraints generalized filter framework linear equality constraints prediction-correction structure pseudo measurements set-membership pseudo measurements set-membership uncertainty representation singular covariance matrices stochastic representation Covariance matrices Mathematical model Measurement uncertainty Shape Stochastic processes Xenon kalman filters State estimation Markov chain variance covariance matrix Covariance matrix Stochastic Processes measurement uncertainty Xenon Dynamic systems Mathematical Model Equality

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An Efficient Approach for Edge Detection Technique using kalman filter with Artificial Neural Network

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INTERNATIONAL JOURNAL OF ENGINEERING 2021年第12期34卷

作者： Siddharth, D. Saini, D. K. J. Singh, P. Rama Univ Dept CSE Kanpur 209217 Uttar Pradesh India Swami Rama Himalayan Univ SRHU Himalayan Sch Sci & Technol Dept Comp & Informat Sci Dehra Dun 248016 Uttarakhand India

Edge identification is a technique for recognizing and detecting sharper breaks in an image. The halt is caused by a rapid change in the value of the pixel force dark level. Convoluting the picture with an administrator (Two-Directional channel) that is set to be noise sensitive is the standard approach for edge location. Edge finder is a method for locating precisely adjusted intensity esteem alterations that incorporate many significant neighborhoods image preparation methods. Edge recognition is a fundamental method in a wide range of image processing applications, including movement analysis, design identification, object recognition, clinical picture creation, and so on. It's recently shown up in a variety of edge detection systems, demonstrating both the advantages and disadvantages of these computations. The kalman filter with ANN method has two benefits that make it suitable for dealing with improvement issues: quicker merging and lower calculation rates. In this study, The ANN method was used to improve object localization accuracy. kalman filtering is used to object coordinates acquired using the ANN method. Using ANN + kalman filtering increases localization accuracy and lowers localization error distances, according to the findings.

关键词： Grey level image Edge detection filter kalman filter algorithm Artificial Neural Network

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Optimal Placement and Sizing of Multiple DGs in a Practical Distribution System

Optimal Placement and Sizing of Multiple DGs in a Practical ...

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Annual Meeting of the IEEE-Industry-Applications-Society (IAS)

作者： Lee, Soo Hyoung Park, Jung-Wook Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

ISBN: (纸本)9781467303323

The selection of placement and size for the multiple distributed generations (DGs) based on renewable energies becomes an important issue to operate modern power systems safely and reliably. This paper extends the previous study in [1] by treating the problems for their optimal locations and sizes in more realistic way based on the power loss sensitivities and kalman filter algorithm, respectively. In particular, the proposed method is implemented by the simulation on a part of practical distribution network of 60 MVA-scale, which is located at the Do-gok area in Seoul, Korea. The new factor, called as the optimal locator index (OLI), is developed to determine the optimal locations in a systematic and effective manner by the power loss sensitivities. Also, the kalman filter algorithm is applied to determine the optimal sizes by choosing the step size of 10 KW, which is much smaller increment than the 10 MW step used in [1], without requiring high computational efforts. This selected step size of 10 KW is realistic and suitable to apply it for the practical test system.

关键词： distributed generation grid connection kalman filter algorithm load-concentration-bus optimal location optimal size optimal locator index power loss sensitivity power-margin

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The Application of Multi - Source Information Fusion Technology in Vehicle Integrated Navigation System 2018

The Application of Multi - Source Information Fusion Technol...

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6th International Conference on Bioinformatics and Computational Biology (ICBCB)

作者： Tang, Bin-hui Zeng, Wei-jun Zhou, Zhen-xing Sichuan Univ Dept Comp Sci & Technol Jincheng Coll Chengdu 610000 Sichuan Peoples R China A Yunnan Agr Univ Dept Water Resources Kunming 650201 Yunnan Peoples R China Chinese Peoples Liberat Army Mil Representat Off Chengdu 610000 Sichuan Peoples R China

ISBN: (纸本)9781450363488

By analyzing the advantages and disadvantages of GPS, Beidou satellite positioning and navigation system and inertial navigation system, a design method of Beidou / GPS / INS integrated navigation system is proposed. This method uses the improved kalman filter algorithm, and combines the integrated navigation system with multi-sensor such as laser radar for sufficient information fusion. The integrated navigation system model uses the dispersive filter structure of federated filtering to establish local filters respectively and deduces the state equation and observation equation of combined navigation. The filter cross-covariance matrix is used to solve the cross-correlation between local filters and affect the positioning accuracy problem. The simulation results show that the integrated navigation system has higher positioning accuracy than single navigation system, and can effectively enhance the real-time and fault-tolerance of the system and facilitate the troubleshooting and isolation of the navigation subsystems.

关键词： inertial navigation system kalman filter algorithm laser radar dispersive filter structure filter error mutual covariance matrix

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Research on Four Axis Aircraft Based on STM32 6

Research on Four Axis Aircraft Based on STM32

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6th International Conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Su, Jie Zheng, Jijun Jiang, Zhenhai Liu, Shaoshuai Dalian Neusoft Univ Informat Dalian 116021 Liaoning Peoples R China Dalian 4810 Shipyard Dalian 116023 Liaoning Peoples R China

ISBN: (纸本)9781665432634

Four axis aircraft is a new type of unmanned aerial vehicle. Different from the traditional single axis aircraft, four propellers can reverse the anti-torque torque of each other without the need for the anti-torque , so its structure is more compact and its lift is greater. In order to control the flight attitude of the four axis aircraft effectively, this paper uses STM32 as the main controller, carries MPU6050 inertial measurement unit with three axis accelerometer and three axis gyroscope integration as the attitude Euler angle measurement unit, further uses the extended kalman filter algorithm to calculate the attitude of the four axis aircraft accurately, and uses PID algorithm to realize the attitude control of the aircraft. Finally, the smooth flight of the aircraft is realized with multiple system tests and debugging.

关键词： STM32 PID algorithm kalman filter algorithm

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Application of kalman filtering algorithm in Laser Triangulation Measurement 36

Application of Kalman Filtering Algorithm in Laser Triangula...

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36th Chinese Control Conference (CCC)

作者： Wen Xiao-qin Liang Jun-yuan South China Univ Technol Sch Automat Sci & Engn Ministerial Key Lab Autonomous Syst & Networked C Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9789881563934

In order to improve the measurement precision of the laser displacement sensor. First, the cause of the error caused by the measured surface features is analyzed from the measurement principle of laser triangulation. Then, according to the result of error analysis, the kalman filter algorithm is applied to the sensor data to carry out error compensation. Finally, the experiments were carried out with LS-100CP laser displacement sensor and MATLAB. The experimental results show that the kalman filter algorithm in the application of laser triangula(1)tion measurement is feasible, effective and have a good practical value.

关键词： kalman filter algorithm triangulation method data processing measurement precision

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IMM EKF based Sensor Fusion for Vehicle Positioning Under Various Road Surface Conditions 20

IMM EKF based Sensor Fusion for Vehicle Positioning Under Va...

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20th International Conference on Control, Automation and Systems (ICCAS)

作者： Heo, Hyeon Uk Kim, Dae Jung Chung, Chung Choo Hanyang Univ Dept Elect Engn Seoul 04763 South Korea Hanyang Univ Dept Elect & Biomed Engn Seoul 04763 South Korea

ISBN: (纸本)9788993215199

In this paper, we propose an estimation of the accurate vehicle position using Interacting Multiple Model Extended kalman filter (IMM EKF) when road surface varies. Since the vehicle has different cornering stiffness as the road surface varies, it is difficult to accurately estimate the position of the vehicle. To resolve this problem, we present the IMM EKF considering each model of different roads to improve the estimation performance. From the numerical simulation using MATLAB/CARSIM, we observed that the performance of the proposed algorithm improves vehicle positioning performance.

关键词： Autonomous Driving Interacting Multiple Model kalman filter algorithm Vehicle Positioning

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An analysis of risk aversion in biotechnology adoption: the case of US genetically modified corn

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EMPIRICAL ECONOMICS 2021年第5期60卷 2613-2635页

作者： Yoo, Do-il Chavas, Jean-Paul Seoul Natl Univ Dept Agr Econ & Rural Dev 200-82271 Gwanak Ro Seoul 08826 South Korea Univ Wisconsin Dept Agr & Appl Econ 518 Taylor Hall427 Lorch St Madison WI 53706 USA

This paper analyzes the role of risk aversion in biotechnology adoption with the application on the US genetically modified corn. A dynamic programming analysis of technology adoption is conducted using the kalman filter as a representation of the associated learning process. The relevant Bellman equation is jointly solved within model estimation using a minimum-distance estimator. Results show that the more the risk-averse farmers are, the later they adopt GM technology, such effects being statistically significant. Sensitivity analysis results examine the factors affecting farmers' behavior. They document the role of risk aversion in technology adoption. They also uncover the presence of farm heterogeneity in the process of adopting a new technology.

关键词： Biotechnology adoption kalman filter algorithm Minimum-distance estimator (MDE) Risk aversion

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