事件触发容积卡尔曼滤波及其在火控探测网络中的应用

doi:10.3969/j.issn.1000-1093.2018.03.001

兵工学报 ›› 2018, Vol. 39 ›› Issue (3): 417-427.doi: 10.3969/j.issn.1000-1093.2018.03.001

事件触发容积卡尔曼滤波及其在火控探测网络中的应用

梁苑¹，盛安冬¹，武兆斌²，张蛟²，戚国庆¹，李银伢¹

(1.南京理工大学自动化学院, 江苏南京 210094; 2.63961部队, 北京 100012)

收稿日期:2017-07-19 修回日期:2017-07-19 上线日期:2018-05-07
作者简介:梁苑(1989—)，男，博士研究生。E-mail: lyy1989316@163.com
基金资助:
国家自然科学基金项目（61273076）

Event-triggered Cubature Kalman Filtering Algorithm and Its Application in the Detection Network for Fire Control

LIANG Yuan¹， SHENG An-dong¹， WU Zhao-bin²， ZHANG Jiao²， QI Guo-qing¹， LI Yin-ya¹

(1.School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China;2.Unit 63961 of PLA, Beijing 100012, China)

Received:2017-07-19 Revised:2017-07-19 Online:2018-05-07

摘要/Abstract

摘要： 为减小传感器网络中各探测单元和融合中心间的数据传输量，设计了基于双重判断准则的事件触发机制，以控制各探测单元到融合中心的数据传输。为得到比已有事件触发融合估计算法更高的估计精度，提出了一种基于所提事件触发机制和平方根容积卡尔曼滤波的非线性融合估计方法。仿真和试验结果表明：所提方法与基于周期传输机制的容积卡尔曼滤波相比，可减小数据传输量；与已有事件触发融合估计方法相比，可在数据传输量基本一致情况下获得更高的估计精度。

关键词: 火控探测网络, 事件触发机制, 容积卡尔曼滤波, 不完全量测

Abstract: An event-triggered mechanism based on dual-criterion is designed to reduce the amount of data transfer between each detection unit and the data fusion center in a sensor network. The proposed event-triggered mechanism has been utilized to schedule the data transfer between each detection unit and the data fusion center. And a nonlinear fusion estimator based on the aforementioned event-triggered mechanism and the square-root cubature Kalman filter is proposed to obtain better estimation performance than those of existing event-triggered fusion estimation algorithms. The simulated results and experimental results show that the proposed event-triggered fusion estimator can reduce the data transfer amount compared with the fusion estimator based on periodic transmission mechanism and offer better estimation performance than those of existing event-triggered fusion estimators. Key

Key words: detectionnetworkforfirecontrol, event-triggeredmechanism, cubatureKalmanfilter, intermittentmeasurement

中图分类号:

梁苑，盛安冬，武兆斌，张蛟，戚国庆，李银伢. 事件触发容积卡尔曼滤波及其在火控探测网络中的应用[J]. 兵工学报, 2018, 39(3): 417-427.

LIANG Yuan， SHENG An-dong， WU Zhao-bin， ZHANG Jiao， QI Guo-qing， LI Yin-ya. Event-triggered Cubature Kalman Filtering Algorithm and Its Application in the Detection Network for Fire Control[J]. Acta Armamentarii, 2018, 39(3): 417-427.

参考文献

［1］ Arasaratnam I, Haykin S. Cubature Kalman filters［J］. IEEE Transactions on Automatic Control, 2009, 54(6):1254-1269.
［2］孙枫, 唐李军. Cubature卡尔曼滤波与Unscented卡尔曼滤波估计精度比较［J］. 控制与决策，2013，28(2):303-308.
SUN Feng, TANG Li-jun. Estimation precision comparison of cubature Kalman filter and unscented Kalman filter［J］. Control and Decision, 2013, 28(2):303-308. (in Chinese)
［3］王俭臣, 齐晓慧. 基于气动参数辨识的飞控系统传感器故障估计［J］. 兵工学报, 2015, 36(1):103-110.
WANG Jian-chen, QI Xiao-hui. Sensor fault estimation method for flight control systems based on aerodynamic parameter identification［J］. Acta Armamentarii, 2015, 36(1):103-110. (in Chinese)
［4］黄湘远, 汤霞清, 武萌, 等. 基于5阶降维平方根-容积卡尔曼滤波的动基座对准应用研究［J］. 兵工学报, 2016, 37(2):219-225.
HUANG Xiang-yuan, TANG Xia-qing, WU Meng, et al. Research on initial alignment of moving base with 5th-degree dimensionality reduction SR-CKF［J］. Acta Armamentarii, 2016, 37(2): 219-225. (in Chinese)
［5］ Arasaratnam I. Sensor fusion with square-root cubature information filtering［J］. Intelligent Control and Automation, 2013, 4(1):11-17.
［6］刘华, 吴文, 王世元. 基于平方根CKF 的多传感器序贯式融合跟踪算法［J］. 系统工程与电子技术, 2015, 37(7):1494-1498.
LIU Hua, WU Wen, WANG Shi-yuan. Multi-sensor sequential fusion tracking algorithm based on square-root cubature Kalman filter［J］. Systems Engineering and Electronics, 2015, 37(7):1494-1498. (in Chinese)
［7］丁家琳, 肖建, 张勇. 基于CKF的分布式滤波算法及其在目标跟踪中的应用［J］. 控制与决策, 2015, 30(2): 296-302.
DING Jia-lin, XIAO Jian, ZHANG Yong. Distributed algorithm-based CKF and its applications to target tracking［J］. Control and Decision, 2015, 30(2):296-302. (in Chinese)
［8］ Liu Y, He You, Wang H P. Squared-root cubature information consensus filter for non-linear decentralized state estimation in sensor networks［J］. IET Radar, Sonar and Navigation, 2014, 8(8): 931-938.
［9］ Gungor V C, Hancke G P. Industrial wireless sensor networks: challenges, design principles, and technical approaches［J］. IEEE Transactions on Industrial Electronics, 2009, 56(10):4258-4265.

［10］ Battistelli G, Benavoli A, Chisci L. Data-driven communication for state estimation with sensor networks［J］. Automatica, 2012, 48(5):926-935.
［11］ Liu Q Y, Wang Z D, He X, et al. Event-based recursive distributed filtering over wireless sensor networks［J］. IEEE Transactions on Automatic Control, 2015, 60(9): 2470-2475.
［12］ Li W L, Jia Y M, Du J P. Event-triggered Kalman consensus filter over sensor networks［J］. IET Control Theory & Applications, 2016, 10(1):103-110.
［13］ Li L, Yu D D, Xia Y Q, et al. Event-triggered UKF for nonlinear dynamic systems with packet dropout［J］. International Journal of Robust and Nonlinear Control, 2017, 27(18):4208-4226.
［14］ Wang Z D, Daniel W C H, Liu X H. Variance-constrained filtering for uncertain stochastic systems with missing measurements［J］. IEEE Transactions on Automatic Control, 2003, 48(7): 1254-1258.
［15］ Li W L, Jia Y M, Du J P. Distributed Kalman consensus filter with intermittent observations［J］. Journal of the Franklin Institute, 2015, 352(9):3764-3781.
［16］陈烨, 李银伢, 戚国庆, 等. 多通道解耦事件触发机制及其在光电传感网络中的应用［J］. 自动化学报, 2017, 43(2):227-237.
CHEN Ye, LI Yin-ya, QI Guo-qing, et al. A multi-channel decoupled event triggered transmission mechanism and its application to optic-electric sensor network［J］. Acta Automatica Sinica, 2017, 43(2):227-237. (in Chinese)

第39卷
第3期2018 年3月兵工学报ACTA
ARMAMENTARIIVol.39No.3Mar.2018

[1]	梁苑，戚国庆，陈烨，李银伢，盛安冬. 不完全量测下事件触发水面扩展目标跟踪[J]. 兵工学报, 2024, 45(4): 1219-1228.
[2]	于镝, 王亚洁, 赵博, 刘琼. 动态事件触发机制下多智能体系统固定时间跟踪[J]. 兵工学报, 2023, 44(5): 1403-1413.
[3]	陈林秀，郝明瑞，赵佳佳. 混合噪声条件下的目标被动定位算法[J]. 兵工学报, 2021, 42(9): 1923-1930.
[4]	卢雨，衣晓. 基于动态规划和双变量容积卡尔曼滤波的空基外辐射源定位算法[J]. 兵工学报, 2021, 42(4): 808-816.
[5]	王宁，李银伢，戚国庆，盛安冬. 不完全量测下基于信息一致性的分布式容积卡尔曼滤波算法[J]. 兵工学报, 2021, 42(11): 2396-2408.
[6]	徐博，李盛新，金坤明，王连钊. 基于径向基函数神经网络辅助容积卡尔曼滤波的多自主水下航行器协同定位方法[J]. 兵工学报, 2019, 40(10): 2119-2128.
[7]	陈烨，盛安冬，戚国庆，李银伢. 不完全量测下事件触发卡尔曼一致滤波及在光电探测网中的应用[J]. 兵工学报, 2018, 39(4): 625-634.
[8]	黄湘远，汤霞清，武萌，吴伟胜. 基于5阶降维平方根-容积卡尔曼滤波的动基座对准应用研究[J]. 兵工学报, 2016, 37(2): 219-225.
[9]	王俭臣, 齐晓慧. 基于气动参数辨识的飞控系统传感器故障估计[J]. 兵工学报, 2015, 36(1): 103-110.

事件触发容积卡尔曼滤波及其在火控探测网络中的应用

Event-triggered Cubature Kalman Filtering Algorithm and Its Application in the Detection Network for Fire Control

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 9

编辑推荐

Metrics

本文评价