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基于Kalman滤波与神经网络的高精度同步时钟算法

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电网技术 2019年第3期43卷 777-783页

作者：李依泽陆超王印峰熊春晖方陈凌平电力系统及发电设备控制和仿真国家重点实验室(清华大学电机系) 北京市海淀区100084 国网上海市电力公司电力科学研究院上海市虹口区200437

大规模分布式电源、储能与电动汽车的接入对配电网状态监测与运行控制带来了挑战。基于配电网同步相量测量单元(phasor measurement unit,PMU)的广域量测系统被认为是解决这一问题的有效方式。然而,采用低成本晶振时,现有的同步时钟算... 详细信息

大规模分布式电源、储能与电动汽车的接入对配电网状态监测与运行控制带来了挑战。基于配电网同步相量测量单元(phasor measurement unit,PMU)的广域量测系统被认为是解决这一问题的有效方式。然而,采用低成本晶振时,现有的同步时钟算法难以满足配电网PMU对同步时钟高精度、高稳定性、低成本的要求。为满足配电网PMU应用的需求,提出一种基于Kalman滤波器与BP神经网络的授时/守时算法。基于卫星信号误差与晶振频率数学模型,利用Kalman滤波器对卫星信号的随机误差进行滤除,提高授时精度,并提供准确的晶振状态数据。利用此数据训练BP神经网络模型,刻画出晶振频率的老化规律,提高守时性能。在卫星信号正常接入与失锁场景下,基于实际时钟装置量测数据进行测试验证。测试结果显示,文中所提算法在不提高现有硬件成本的基础上,有效提高了同步时钟的算法性能。

关键词：同步时钟配电网PMU 授时/守时算法 Kalman 滤波器 BP神经网络

Design of on-board calibration methods for a digital sun sensor based on Levenberg–Marquardt algorithm and Kalman filters

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Chinese Journal of Aeronautics 2020年第1期33卷 339-351页

作者： Ali RAHDAN Hossein BOLANDI Mostafa ABEDI Department of Electrical Engineering Iran University of Science&TechnologyTehran ***Iran Department of Electrical Engineering Shahid Beheshti UniversityTehran ***Iran

Digital sun sensor is one of the most important sensors used in the Attitude Determination System(ADS)of the satellite.Due to the harsh environmental conditions that exist in the space,various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this equipment.So,it is necessary to recalibrate the optical parameters of the aforementioned sensors.For this purpose,first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array,installation error,filter thickness and sensor misalignment.So,the mutual interfaces between the sensor parameters are considered in the developed model.In order to extract the sensor parameters,a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch algorithm.In addition,the Extended Kalman Filter(EKF)and the Unscented Kalman Filter(UKF)have been utilized as sequential strategies.It will be shown that by considering a worst case of variation amount for sensor parameters,an accuracy improvement of about 17°is achieved by the developed calibration algorithms.Comparison between the developed algorithms represents that UKF has higher accuracy,shorter time convergence but higher computational load.

关键词： Digital sun sensor Extended Kalman filter Levenberg–Marquardt On-board calibration Unscented Kalman filter

相对传感网络分布式卡尔曼滤波器的收敛性分析（英文）

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Frontiers of Information Technology & Electronic Engineering 2018年第9期19卷 1063-1075页

作者： Che LIN Rong-hao ZHENG Gang-feng YAN Shi-yuan LU College of Electrical Engineering Zhejiang University Zhejiang Province Marine Renewable Energy Electrical Equipment and System Technology Research Laboratory

严格分析了相对传感网络中分布式卡尔曼滤波问题。用无向图对相对传感网络建模,并假设网络中各节点具有相同动力学模型。给出整个系统可观测性的充要条件,并详细证明。通过局部信息和测量通信,设计了一种基于卡尔曼滤波技术的分布式次... 详细信息

严格分析了相对传感网络中分布式卡尔曼滤波问题。用无向图对相对传感网络建模,并假设网络中各节点具有相同动力学模型。给出整个系统可观测性的充要条件,并详细证明。通过局部信息和测量通信,设计了一种基于卡尔曼滤波技术的分布式次优估计器,并与集中式最优估计器比较。给出系统收敛对应的网络拓扑充分条件,并结合系统参数给出n个线性矩阵不等式(linear matrix inequality, LMI)方程的数值解。数值仿真验证了所提算法的有效性。

关键词： Kalman 过滤技术分布式网络集中分析联合系统动态模型线性矩阵

Study on optimal state estimation strategy with dual distributed controllers based on Kalman filtering

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High Technology Letters 2019年第1期25卷 105-110页

作者：陈雅雯 Wang Zhuwei Fang Chao Xu Guangshu Zhang Yanhua School of Information and Communications Engineering Beijing University of Technology

Considering dual distributed controllers, a design of optimal state estimation strategy is studied for the wireless sensor and actuator network(WSAN). In particular, the optimal linear quadratic(LQ) control strategy with estimated plant state is formulated as a non-cooperative game with network-induced delays. Then, using the Kalman filter approach, an optimal estimation of the plant state is obtained based on the information fusion of the distributed controllers. Finally, an optimal state estimation strategy is derived as a linear function of the current estimated plant state and the last control strategy of multiple controllers. The effectiveness of the proposed closed-loop control strategy is verified by the simulation experiments.

关键词： optimal state estimation strategy wireless sensor and actuator network (WSAN) distributed controllers Kalman filter network-induced delays

Attitude estimation method based on extended Kalman filter algorithm with 22 dimensional state vector for low-cost agricultural UAV

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High Technology Letters 2020年第2期26卷 125-135页

作者：吴和龙 Pei Xinbiao Li Jihui Gao Huibin Bai Yue Changchun Institute of Optics Fine Mechanics and PhysicsChinese Academy of SciencesChangchun 130033P.R.China University of Chinese Academy of Sciences Beijing 100049P.R.China

To overcome the shortcomings of traditional artificial spraying pesticides and make more efficient prevention of diseases and pests,a coaxial sixteen-rotor unmanned aerial vehicle(UAV)with pesticide spraying system is designed.The coaxial sixteen-rotor UAV’s basic structure and attitude estimation method are explained.The whole system weights 25 kg,cruising speed can reach 15 m/s,and the flight time is more than 20 min.When the UAV takes large load,the traditional extended Kalman filter(EKF)attitude estimation method can not meet the work requirements under the condition of strong vibration,the attitude measure accuracy is poor and the attitude angle divergence is easily caused.Hence an attitude estimation method based on EKF algorithm with 22 dimensional state vector is proposed which can solve these problems.The UAV system consists of STM32F429 as controller,integrating following measure sensors:accelerometer and gyroscope MPU6000,magnetometer LSM303D,GPS NEO-M8N and barometer.The attitude unit quaternion,velocity,position,earth magnetic field,biases error of gyroscope,accelerometer and magnetometer are introduced as the inertial navigation systems(INS)state vector,while magnetometer,global positioning system(GPS)and barometer are introduced as observation vector,thus making the estimate of the navigation information more accurate.The control strategy of coaxial sixteen-rotor UAV is based on the control method of combining active disturbance rejection control(ADRC)and proportion integral derivative(PID)control.Actual flight data are used to verify the algorithm,and the static experiment shows that the precision of roll angle and pitch angle of the algorithm are±0.1°,the precision of yaw angle is±0.2°.The attitude angle output of MTi sensor is used as reference.The dynamic experiment shows that the accuracy of attitude estimated by EKF algorithm is quite similar to that of MTi’s output,moreover,the algorithm has good real-time performance which meets the need of high maneuverability of agricultural UAV.

关键词： coaxial sixteen-rotor unmanned aerial vehicle(UAV) extended Kalman filter(EKF) quaternion low-cost

基于SiamCAR与Kalman滤波的红外地面目标抗遮挡跟踪算法

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光电技术应用 2023年第4期38卷 33-40页

作者：朱卓付国栋刘琦妍杨尧中国电子科技集团公司光电研究院天津西北工业大学无人系统技术研究院西安

针对红外地面目标跟踪过程中,由于背景遮挡造成的跟踪鲁棒性差,甚至丢失目标的问题,提出SiamCAR-Kal算法。该算法在SiamCAR算法基础上利用分类分支的响应对遮挡状态进行判定,并利用Kalman滤波算法基于历史信息预测目标位置。针对长时全... 详细信息

针对红外地面目标跟踪过程中,由于背景遮挡造成的跟踪鲁棒性差,甚至丢失目标的问题,提出SiamCAR-Kal算法。该算法在SiamCAR算法基础上利用分类分支的响应对遮挡状态进行判定,并利用Kalman滤波算法基于历史信息预测目标位置。针对长时全遮挡Kalman滤波精度低的问题,提出扩张搜索策略,对目标进行重新捕获。实验结果表明,所提算法可以有效提升跟踪精度,并解决因遮挡导致的目标丢失问题。对红外地面目标序列进行测试,对比已有典型SiamCAR跟踪算法,该算法在OPE评价指标下,成功率提升3.2%、精确度提升4.5%。

关键词：抗遮挡红外地面目标 SiamCAR Kalman

THE EFFECT OF SAMPLE OPTIMIZATION ON THE ENSEMBLE Kalman FILTER IN FORECASTING TYPHOON RAMMASUN(2014)

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Journal of Tropical Meteorology 2018年第4期24卷 433-447页

作者：李霁杭万齐林高郁东肖辉 Key Laboratory of Regional Numerical Weather Prediction Guangzhou Institute of Tropical and Marine Meteorology

In a limited number of ensembles, some samples do not adequately reflect the true atmospheric state and can in turn affect forecast performance. This study explored the feasibility of sample optimization using the ensemble Kalman filter(EnKF) for a simulation of the 2014 Super Typhoon Rammasun, which made landfall in southern China in July 2014. Under the premise of sufficient ensemble spread, keeping samples with a good fit to observations and eliminating those with poor fit can affect the performance of En KF. In the sample optimization, states were selected based on the sample spatial correlation between the ensemble state and observations. The method discarded ensemble states that were less representative and, to maintain the overall ensemble size, generated new ensemble states by reproducing them from ensemble states with a good fit by adding random noise. Sample selection was performed based on radar echo data. Results showed that applying En KF with optimized samples improved the estimated track, intensity,precipitation distribution, and inner-core structure of Typhoon Rammasun. Therefore, the authors proposed that distinguishing between samples with good and poor fits is vital for ensemble prediction, suggesting that sample optimization is necessary to the effective use of En KF.

关键词： data assimilation ensemble prediction sample optimization Typhoon Rammasun ensemble Kalman filter

Marginalized cubature Kalman filtering algorithm based on linear/nonlinear mixed-Gaussian model

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High Technology Letters 2018年第4期24卷 362-368页

作者：胡玉梅 Hu Zhentao Jin Yong School of Automation Northwestern Polytechnical University College of Computer and Information Engineering Henan University

Aiming at improving the estimation accuracy and real-time of nonlinear system with linear Gaussian sub-structure,a novel marginalized cubature Kalman filter is proposed in Bayesian estimation framework. Firstly,the marginalized technique is adopted to model the target system dynamics with nonlinear state and linear state separately,and the two parts are estimated by cubature Kalman filter and standard Kalman filter respectively. Therefore,the linear part avoids the generation and propagation process of cubature points. Accordingly,the computational complexity is reduced.Meanwhile,the accuracy of state estimation is improved by taking the difference of nonlinear state estimation as the measurement of linear state. Furthermore,the computational complexity of marginalized cubature Kalman filter is discussed by calculating the number of floating-point operation. Finally,simulation experiments and analysis show that the proposed algorithm can improve the performance of filtering precision and real-time effectively in target tracking system.

关键词： state estimation marginalized modeling mixed-Gaussian model cubature Kalman filter

High-precision Positioning and Deformation Monitoring Analysis of BD/GPS Based on Improved Kalman Filter Fusion

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Journal of Systems Science and Information 2019年第3期10卷 270-282页

作者： Xiulin QIU Qinghua LIU Ru LI School of Computing Jiangsu University of Science and Technology

The real time kinematic of global positioning system(GPS-RTK) provides precise positioning for bridge deformation monitoring and monitoring bridge health status. In order to solve the problem that the satellite signal is vulnerable to the influence of the positioning environment when monitoring bridges in the valleys and urban buildings[1], and the problem that Kalman fusion algorithm is difficult to detect the divergence caused by interruption or wrong data(2)This paper proposes an improved Kalman filter fusion position method based on the BD/GPS fusion positioning. This improved algorithm introduces the environmental information. The confidence level is calculated with membership function by defining the confidence region of sensor, so as to the fusion weight coefficient is determined. This paper analyzes the performance of BD/GPS positioning in bridge monitoring through comparing the traditional fusion method with the improved fusion method. Experiments show that the improved algorithm eliminates the problem of error divergence;the average number of visible satellites in BD/GPS fusion positioning is increased by 7 compared with that of GPS single system positioning,the GDOP value is reduced by 21.83%, and the positioning error is reduced by 2.51 cm. The feasibility of all-weather monitoring in the mountains, buildings and other areas is verified, and millimeter accuracy is provided, which greatly improves the performance of bridge deformation monitoring.

关键词： GPS Beidou Kalman algorithm BD/GPS fusion deformation monitoring