基于无线传感网的智能家居软系统设计
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摘要
现在的中国正迎来一个”数字城市”、”数字社区”建设与“低碳经济”发展的热潮,3G技术和物联网应用对智能家居的发展也起到很重要的推动作用,而智能家居能够有效实现“低碳经济、绿色经济”。基于无线传感器网络的智能家居系统,将有效解决普通无线产品面临的诸多问题。用户所安装的各产品设备根据实际安装情况组成具有安全保证的传输网络,保证了系统智能操作的正确性、检测上报数据和用户控制下行数据传输的有效性。有效实现多设备的协同处理及准确判断能力。本论文利用切合家庭应用场景的自组网协议,利用众多的传输设备,配合涵盖面极广的检测手段,结合移动网络和现场图像,设计了一种基于无线传感网的智能家居检测系统。
论文首先详细介绍课题的研究背景和国内外研究的现状,阐述了选题的意义。其次概况介绍了无线智能家居系统的系统架构与系统硬件平台,提出了检测设备、传输设备和网关设备的总体设计方案。第三,重点介绍了整个系统协议设计的原则、拓扑结构、协议解释、Frame结构、各网络层的数据结构以及接口函数。确定系统应采用分层的网络协议、竞争的数据发送方式、自动更换频点、自动分配地址的四跳拓扑结构,实现检测上报数据和用户控制下行数据传输的有效性。第四,重点介绍了无线智能家居系统应用层的网关软件设计,包括用户交互层,逻辑判断层和物理功能模块层,介绍了SmartHouseUI, SmartHouseAPP, LibSinkControl, GsmGprsCom, Libcamera,各模块的设计以及数据接口。系统软件设计遵循接口明晰、组合灵活、扩展性强的准则,具有非常强的扩展功能。第五,对这个系统协议软件从功能测试、容错能力测试、性能测试三方面进行了全面测试与分析,并给出了网关上位机软件的九大界面图集,同时从功能测试(传感器组网功能、网络拓扑更新功能、用户查询功能、用户手机控制网关功能)、稳定性测试(系统稳定工作的能力)、可靠性测试(系统电磁辐射的抗干扰能力)、健壮性测试(无线传感器网络的抗变化性)几方面对整个系统进行了联调。结果表明该系统在检测信息采集与智能控制方面有较高的准确性和可靠性,具有较强的应用价值。最后,对所做的工作进行了总结并对日后该系统的发展提出了更加有利的想法与展望。
Nowadays, China is encountering a hot tide that waves the construction of "digital city", "digital community "and the development of "low-carbon economy". The applications of 3G technology and WSN (Wireless Sensor Network) also play a very important role in promoting the development of smart house which can effectively achieve "low-carbon economy, green economy." The smart house system based on WSN will effectively solve many problems that ordinary wireless products are facing. According to the actual condition of installation, all sorts of equipments installed by users make up the transmission networks that have been guaranteed for their safty, correctness of the smart system operation and effectiveness of detecting uploaded data and the downstream data transmission controlled by users, achieving the capability of collaborative processing and accurate judgement of multiple equipments.This paper designs a detecting system based on WSN, which makes use of many transmission equipments, combines with the widely-covered detecting means, mobile network and on-spot images.
Firstly, the paper introduces the background and current researching progress of wireless sensor network at house and abroad and states the significance of the subject. Secondly, the system configuration and platform of system hardware are introduced, and the whole designing scheme of the detection, transmission and gateway equipments is put forward. Thirdly, the paper focuses on introducing the principle of the whole system protocol design, the structure of topology and frame, the explanation of protocol, the data structure of each network layer and interface functions, determining that system should adopt a network protocol with several layers, competitive data sending mode, four-jump topology structure that can automatically replace frequency points and assign addresses to achieve the effectiveness of detecting uploaded data and the downstream data transmission controlled by users.Fourthly, the paper mainly introduces the gateway software design of application layer in smart house system, including the interactive layer for users, the layer for logic judgement and the layer for physical function block.And the SmartHouseUI. SmartHouseAPP. LibSinkControl. GsmGprsCom. Libcamera. the design of each block and data interface are also mentioned. The design of system software follows the rules that the system should has clarified interface, flexible combination and strong expansibility. Fifthly, the system protocol software has been completely tested and analyzed in three aspects of the function test, the tolerance test and the performance test. and nine interface graphs of the gateway embedded software were given, meantime the system has been jointly debugged from the test of function, performance, reliability and robustness, such as the sensor network function, the topology updating function, the user's query function, the user mobile phone control gateway function, the stable working ability of system, the electromagnetism radiation anti-interference ability of system, the wireless sensor networks anti variability. The results indicate that the system has show high accuracy and reliability in detecting the collection of information, and also has strong application value. Finally, the summary is made with respect to the work done and more favorable ideas and expectations are put forward with respect to the development of the system in future.
论文首先详细介绍课题的研究背景和国内外研究的现状,阐述了选题的意义。其次概况介绍了无线智能家居系统的系统架构与系统硬件平台,提出了检测设备、传输设备和网关设备的总体设计方案。第三,重点介绍了整个系统协议设计的原则、拓扑结构、协议解释、Frame结构、各网络层的数据结构以及接口函数。确定系统应采用分层的网络协议、竞争的数据发送方式、自动更换频点、自动分配地址的四跳拓扑结构,实现检测上报数据和用户控制下行数据传输的有效性。第四,重点介绍了无线智能家居系统应用层的网关软件设计,包括用户交互层,逻辑判断层和物理功能模块层,介绍了SmartHouseUI, SmartHouseAPP, LibSinkControl, GsmGprsCom, Libcamera,各模块的设计以及数据接口。系统软件设计遵循接口明晰、组合灵活、扩展性强的准则,具有非常强的扩展功能。第五,对这个系统协议软件从功能测试、容错能力测试、性能测试三方面进行了全面测试与分析,并给出了网关上位机软件的九大界面图集,同时从功能测试(传感器组网功能、网络拓扑更新功能、用户查询功能、用户手机控制网关功能)、稳定性测试(系统稳定工作的能力)、可靠性测试(系统电磁辐射的抗干扰能力)、健壮性测试(无线传感器网络的抗变化性)几方面对整个系统进行了联调。结果表明该系统在检测信息采集与智能控制方面有较高的准确性和可靠性,具有较强的应用价值。最后,对所做的工作进行了总结并对日后该系统的发展提出了更加有利的想法与展望。
Nowadays, China is encountering a hot tide that waves the construction of "digital city", "digital community "and the development of "low-carbon economy". The applications of 3G technology and WSN (Wireless Sensor Network) also play a very important role in promoting the development of smart house which can effectively achieve "low-carbon economy, green economy." The smart house system based on WSN will effectively solve many problems that ordinary wireless products are facing. According to the actual condition of installation, all sorts of equipments installed by users make up the transmission networks that have been guaranteed for their safty, correctness of the smart system operation and effectiveness of detecting uploaded data and the downstream data transmission controlled by users, achieving the capability of collaborative processing and accurate judgement of multiple equipments.This paper designs a detecting system based on WSN, which makes use of many transmission equipments, combines with the widely-covered detecting means, mobile network and on-spot images.
Firstly, the paper introduces the background and current researching progress of wireless sensor network at house and abroad and states the significance of the subject. Secondly, the system configuration and platform of system hardware are introduced, and the whole designing scheme of the detection, transmission and gateway equipments is put forward. Thirdly, the paper focuses on introducing the principle of the whole system protocol design, the structure of topology and frame, the explanation of protocol, the data structure of each network layer and interface functions, determining that system should adopt a network protocol with several layers, competitive data sending mode, four-jump topology structure that can automatically replace frequency points and assign addresses to achieve the effectiveness of detecting uploaded data and the downstream data transmission controlled by users.Fourthly, the paper mainly introduces the gateway software design of application layer in smart house system, including the interactive layer for users, the layer for logic judgement and the layer for physical function block.And the SmartHouseUI. SmartHouseAPP. LibSinkControl. GsmGprsCom. Libcamera. the design of each block and data interface are also mentioned. The design of system software follows the rules that the system should has clarified interface, flexible combination and strong expansibility. Fifthly, the system protocol software has been completely tested and analyzed in three aspects of the function test, the tolerance test and the performance test. and nine interface graphs of the gateway embedded software were given, meantime the system has been jointly debugged from the test of function, performance, reliability and robustness, such as the sensor network function, the topology updating function, the user's query function, the user mobile phone control gateway function, the stable working ability of system, the electromagnetism radiation anti-interference ability of system, the wireless sensor networks anti variability. The results indicate that the system has show high accuracy and reliability in detecting the collection of information, and also has strong application value. Finally, the summary is made with respect to the work done and more favorable ideas and expectations are put forward with respect to the development of the system in future.
引文
[1]佚名.展望物联网大潮下的中国智能家居产业[OE/BL].www.im2m.com.cn/Item/13512.aspx,2010.
[2]王成祥.家庭安防报警产品分析与展望[J].安防科技,2003,32(4)：25-28.
[3]何友,王国宏.多传感器信息及应用[M].北京：电子工业出版社,2000,36(7)：8-10.
[4]Dempster A P. A Generalization of Bayesian Inference[J]. Journal of the Royal Statistical Society,1968, Series B30:205-247.
[5]安建妮.信息融合与合成视景技术研究[D].西安：西安科技大学出版社,2010.
[6]何小川.简述未来住宅的智能化发展[J].安徽建筑,2004,7(5)：37-40.
[7]郑相全等.无线自组网技术实用教程[M].北京：清华大学出版社,2004.
[8]谷有臣,孔英等.传感器技术的发展和趋势综述[J].物理实验,2002,22(12)：40-42.
[9]周贤伟.无线传感器网络与安全[M].北京：国防工业出版社,2007,29(28)：4-5.
[10]Shafer G. A Mathematical Theory of Evidence[M]. Princeton:Princetion Princeton University Press, 1976.
[1]]秦菲, 郭雷, 高世伟. 一种基于运动检测的粒子滤波跟踪方法[J].光电工程,2009,36(7)：45-49.
[12]巫春玲, 韩崇昭.用于弹道目标跟踪的有限差分扩展卡尔曼滤波算法[J].西安交通大学学报,2008,42(2)：143-146,242.
[13]马德义.IP网视频会议的图像加密方法研究[D].北京：北京工业大学出版社,2007.
[14]WU Chun-ling, HAN Chong-zhao. Finite-Difference Extended Kalman Filtering Algorithm for Ballistic Target Tracking [J]. Journal of Xi'an Jiao Tong University,2008,42(2):143-146.
[15]魏小龙.MSP430系列单片机接口技术及系统设计实例[M].北京：北京航空航天大学出版社,2002,7(5)：15-3.
[16]单片433/868/915MHZ无线收发器nRF905[Z].讯通科技.
[17]Terry J.10 Emerging Technologies that Will Change the World[J]. Technology Review,2003,106(1): 33-49.
[18]高传善,杨珉等.无线传感器网络路由协议研究综述[J].世界科技研究与发展,2005,27(8)：1-8.
[19]马祖长,孙怡宁等.无线传感器网络综述[J].通信学报,2004,25(4)：114-124.
[20]崔莉,鞠海玲等.无线传感器网络研究进展[J].计算机研究与发展,2005,42(1)：163-174.
[21]王建,沈元隆.星形网络的可靠性分析及其路由选择[J].西安邮电学院学报,2006,01.
[22]郭梯云,邬国扬等.移动通信[M].西安：西安电子科技大学出版社,2000.
[23]Wei Ye. John Heinemann. Deborah Estrin. An Energy-Efficient MAC Protocol for Wireless Sensor Networks[C]. In:Proc.Of the 21st International Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM 2002), NEW YORK. NY. USA. June,2002.
[24]T.V.Dam. K.Langendoen. An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks[C]. The First ACM Conference on Embedded Networked Sensor Systems (Sensys,03), Los Angeles, CA, USA, November,2003.
[25]郭午平.无线传感器网络的研究现状及发展[C].中国通信学会信息通信网络技术委员会2005年年会.
[26]JAMALN.AL-KARAKI. THE HASHEMITE UNIVERSITY AHMED E.KAMAL, IOWASTATE UNIVERSITY. ROUTING TECHNIQUES IN WIRELESS SENSOR NETWORKS[R]:A SURVEY.IEEE Wireless Communications,2004, 11(6):6-28.
[27]孙利民,李建中等.无线传感器网络[M].北京：清华大学出版社,2005,8(16)：4-6.
[28]Pahlavan K, Levesque A. Wireless Information Networks[M]. New York:John Wiley&Sons, Inc,1995.
[29]Bharghavan V, Demers A, Shenker S, Zhang L.M ACAW:A Media Access Protocol for Wireless LANs[A]. In Proceedings of SIGCOMM'94[C],1994,9(27):212-225.
[30]Walrod J.Sensor Network Technology for Joint Undersea Warfare[A]. Proc.Of the NDIA Joint Undersea Warfare Conference[C]. San Diego,2002.
[31]Doherty L. Algorithms for Position and Data Recovery in Wireless Sensor Networks[R]. Master's Report, University of California, Berkeley,2000.
[32]M.A.M.Vieira, C.N.Coelho Jr. D.C.da Silva Jr. and J.M.da Mata."Survey on wireless sensor network devices"[C]. IEEE ETFA'03, sept.2003, PP.:537-44.
[33]P.Bergamo, G.Mazzini," Localizaion in Sensor Networks with Fading and Mobilty" [C]. IEEE,2005.
[34]Wang jinhao, Qing zhiguang. Geng ji, Li zhi jun. Mobile clustering rekeying in tracking Sensor network[J]. Journal of Harbin Institute of Technology,2006.11(13):409-414.
[35]J.M.Kahn, R.H.Katz, K.S.J.Pister. Next Century Challenges:Mobile Networking for "Smart Dust" [C]. ACM MobiCom'99,1999.
[36]Byrne J A.21 Ideas for the 21st Century[J]. Business Week,1999,8:78-167.[37]梁华,陈振.非坚持型CSMA与坚持型CSMA退避算法的性能分析与比较[J].计算机技术与自动化,2006,03.
[38]陈玉,王晟等.Adhoc中基于主动网的自适应FEC[J].电子科技大学学报,2006,05.
[39]英春,史美林.自主网路由协议综述[J].通信学报,2001,22(11)：93-103.
[40]马宝甫.一种混合纠错算法及其单片机软件实现[J].山东科技大学学报(自然科学版),1997,03.
[41]Johnson D, Maltz D.Dynamic Source Routing in AD-Hoc Wireless Networks[M]. In Mobile Computing, 1996:153-181.
[42]Charles E.Perkins, Elizabeth M R.Ad-hoc On-demand Distance Vector Routing[A]. In Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications[C].1999:80-100.
[43]李建中,李金宝.传感器网络及其数据管理的概念、问题与进展[J].软件学报,2003,14(10)：1717-1727.
[44]Perkins C E, Bhagwat P.Highly Dynamic Destination-Sequenced Distance-Vecto Routing(DSDV)for Mobile Computers[A]. ACM SIGCOMM'94[C],1994:234-244.
[45]Muthy S, Garcia J.An Efficent Routing Protocol for Wireless Network[J]. ACM BalzeMobile Networks and Applications Jounal,1996,1(2):183-197.
[46]Polastre J, Szewczyk R. Mainwaring A, Culler D, Anderson J.Analysis of wireless sensor networks for habitat monitoring[J]. Wire Sensor Networks,2004,399-423.
[47]朱光喜,徐宁.无线信道ARQ算法的一点改进[J].计算机与数字工程,2006,01.
[48]郭峰,曾兴文等.无线局域网[M].北京：电子工业出版社.
[49]WANG Jun-qiu, YAGI Yasushi. Integrating Shape and Color Features for Adaptive Real-time Object Tracking[C]//Proceedings of the 2006 IEEE International Conference on Robotics and Biomimetics, Kunming, China, December 17-20,2006:1-6.
[50]LI Ning, LI Y F. Method for Image Segmentation Based on an Encoder-segmented Neural Network and its Application[J]. Optical Engineering(S0091-3286),1999.38(5):908-920.
[51]郑惠江,王太勇,何改云.视频监控中运动物体的检测与跟踪[J].计算机工程与应用,2010,46(31)：192-195.
[52]Guo Fu-cheng, Li Zong-hua, Sun Zhong-kang. The Modified Covariance Extended Kalman Filter in Passive Location and Tracking[J].2004, V26(6):917-922.
[53]FU Wei-cui, Zhan-zhong. Electrostatic Target Tracking Based on Improved Extended Kalman Filter [J]. Opto-Electronic Engineering,2009.36(7):24-27 (in chinese).
[54]Li Ning, SHI Yi-zhen, ZHOU Jian-jiang. A Real-time Object Tracking Algorithm Based on Self-adaptive Feature Selection[J]. Opto-Electronic Engineering,2009,36(7):1-7 (in Chinese).
[2]王成祥.家庭安防报警产品分析与展望[J].安防科技,2003,32(4)：25-28.
[3]何友,王国宏.多传感器信息及应用[M].北京：电子工业出版社,2000,36(7)：8-10.
[4]Dempster A P. A Generalization of Bayesian Inference[J]. Journal of the Royal Statistical Society,1968, Series B30:205-247.
[5]安建妮.信息融合与合成视景技术研究[D].西安：西安科技大学出版社,2010.
[6]何小川.简述未来住宅的智能化发展[J].安徽建筑,2004,7(5)：37-40.
[7]郑相全等.无线自组网技术实用教程[M].北京：清华大学出版社,2004.
[8]谷有臣,孔英等.传感器技术的发展和趋势综述[J].物理实验,2002,22(12)：40-42.
[9]周贤伟.无线传感器网络与安全[M].北京：国防工业出版社,2007,29(28)：4-5.
[10]Shafer G. A Mathematical Theory of Evidence[M]. Princeton:Princetion Princeton University Press, 1976.
[1]]秦菲, 郭雷, 高世伟. 一种基于运动检测的粒子滤波跟踪方法[J].光电工程,2009,36(7)：45-49.
[12]巫春玲, 韩崇昭.用于弹道目标跟踪的有限差分扩展卡尔曼滤波算法[J].西安交通大学学报,2008,42(2)：143-146,242.
[13]马德义.IP网视频会议的图像加密方法研究[D].北京：北京工业大学出版社,2007.
[14]WU Chun-ling, HAN Chong-zhao. Finite-Difference Extended Kalman Filtering Algorithm for Ballistic Target Tracking [J]. Journal of Xi'an Jiao Tong University,2008,42(2):143-146.
[15]魏小龙.MSP430系列单片机接口技术及系统设计实例[M].北京：北京航空航天大学出版社,2002,7(5)：15-3.
[16]单片433/868/915MHZ无线收发器nRF905[Z].讯通科技.
[17]Terry J.10 Emerging Technologies that Will Change the World[J]. Technology Review,2003,106(1): 33-49.
[18]高传善,杨珉等.无线传感器网络路由协议研究综述[J].世界科技研究与发展,2005,27(8)：1-8.
[19]马祖长,孙怡宁等.无线传感器网络综述[J].通信学报,2004,25(4)：114-124.
[20]崔莉,鞠海玲等.无线传感器网络研究进展[J].计算机研究与发展,2005,42(1)：163-174.
[21]王建,沈元隆.星形网络的可靠性分析及其路由选择[J].西安邮电学院学报,2006,01.
[22]郭梯云,邬国扬等.移动通信[M].西安：西安电子科技大学出版社,2000.
[23]Wei Ye. John Heinemann. Deborah Estrin. An Energy-Efficient MAC Protocol for Wireless Sensor Networks[C]. In:Proc.Of the 21st International Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM 2002), NEW YORK. NY. USA. June,2002.
[24]T.V.Dam. K.Langendoen. An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks[C]. The First ACM Conference on Embedded Networked Sensor Systems (Sensys,03), Los Angeles, CA, USA, November,2003.
[25]郭午平.无线传感器网络的研究现状及发展[C].中国通信学会信息通信网络技术委员会2005年年会.
[26]JAMALN.AL-KARAKI. THE HASHEMITE UNIVERSITY AHMED E.KAMAL, IOWASTATE UNIVERSITY. ROUTING TECHNIQUES IN WIRELESS SENSOR NETWORKS[R]:A SURVEY.IEEE Wireless Communications,2004, 11(6):6-28.
[27]孙利民,李建中等.无线传感器网络[M].北京：清华大学出版社,2005,8(16)：4-6.
[28]Pahlavan K, Levesque A. Wireless Information Networks[M]. New York:John Wiley&Sons, Inc,1995.
[29]Bharghavan V, Demers A, Shenker S, Zhang L.M ACAW:A Media Access Protocol for Wireless LANs[A]. In Proceedings of SIGCOMM'94[C],1994,9(27):212-225.
[30]Walrod J.Sensor Network Technology for Joint Undersea Warfare[A]. Proc.Of the NDIA Joint Undersea Warfare Conference[C]. San Diego,2002.
[31]Doherty L. Algorithms for Position and Data Recovery in Wireless Sensor Networks[R]. Master's Report, University of California, Berkeley,2000.
[32]M.A.M.Vieira, C.N.Coelho Jr. D.C.da Silva Jr. and J.M.da Mata."Survey on wireless sensor network devices"[C]. IEEE ETFA'03, sept.2003, PP.:537-44.
[33]P.Bergamo, G.Mazzini," Localizaion in Sensor Networks with Fading and Mobilty" [C]. IEEE,2005.
[34]Wang jinhao, Qing zhiguang. Geng ji, Li zhi jun. Mobile clustering rekeying in tracking Sensor network[J]. Journal of Harbin Institute of Technology,2006.11(13):409-414.
[35]J.M.Kahn, R.H.Katz, K.S.J.Pister. Next Century Challenges:Mobile Networking for "Smart Dust" [C]. ACM MobiCom'99,1999.
[36]Byrne J A.21 Ideas for the 21st Century[J]. Business Week,1999,8:78-167.[37]梁华,陈振.非坚持型CSMA与坚持型CSMA退避算法的性能分析与比较[J].计算机技术与自动化,2006,03.
[38]陈玉,王晟等.Adhoc中基于主动网的自适应FEC[J].电子科技大学学报,2006,05.
[39]英春,史美林.自主网路由协议综述[J].通信学报,2001,22(11)：93-103.
[40]马宝甫.一种混合纠错算法及其单片机软件实现[J].山东科技大学学报(自然科学版),1997,03.
[41]Johnson D, Maltz D.Dynamic Source Routing in AD-Hoc Wireless Networks[M]. In Mobile Computing, 1996:153-181.
[42]Charles E.Perkins, Elizabeth M R.Ad-hoc On-demand Distance Vector Routing[A]. In Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications[C].1999:80-100.
[43]李建中,李金宝.传感器网络及其数据管理的概念、问题与进展[J].软件学报,2003,14(10)：1717-1727.
[44]Perkins C E, Bhagwat P.Highly Dynamic Destination-Sequenced Distance-Vecto Routing(DSDV)for Mobile Computers[A]. ACM SIGCOMM'94[C],1994:234-244.
[45]Muthy S, Garcia J.An Efficent Routing Protocol for Wireless Network[J]. ACM BalzeMobile Networks and Applications Jounal,1996,1(2):183-197.
[46]Polastre J, Szewczyk R. Mainwaring A, Culler D, Anderson J.Analysis of wireless sensor networks for habitat monitoring[J]. Wire Sensor Networks,2004,399-423.
[47]朱光喜,徐宁.无线信道ARQ算法的一点改进[J].计算机与数字工程,2006,01.
[48]郭峰,曾兴文等.无线局域网[M].北京：电子工业出版社.
[49]WANG Jun-qiu, YAGI Yasushi. Integrating Shape and Color Features for Adaptive Real-time Object Tracking[C]//Proceedings of the 2006 IEEE International Conference on Robotics and Biomimetics, Kunming, China, December 17-20,2006:1-6.
[50]LI Ning, LI Y F. Method for Image Segmentation Based on an Encoder-segmented Neural Network and its Application[J]. Optical Engineering(S0091-3286),1999.38(5):908-920.
[51]郑惠江,王太勇,何改云.视频监控中运动物体的检测与跟踪[J].计算机工程与应用,2010,46(31)：192-195.
[52]Guo Fu-cheng, Li Zong-hua, Sun Zhong-kang. The Modified Covariance Extended Kalman Filter in Passive Location and Tracking[J].2004, V26(6):917-922.
[53]FU Wei-cui, Zhan-zhong. Electrostatic Target Tracking Based on Improved Extended Kalman Filter [J]. Opto-Electronic Engineering,2009.36(7):24-27 (in chinese).
[54]Li Ning, SHI Yi-zhen, ZHOU Jian-jiang. A Real-time Object Tracking Algorithm Based on Self-adaptive Feature Selection[J]. Opto-Electronic Engineering,2009,36(7):1-7 (in Chinese).