无线传感器网络中定位跟踪技术的研究
|
摘要
无线传感器网络集成了传感器技术、微机电技术、分布式信息处理技术和无线通信技术,它已成为当前IT领域研究的热点之一。由于网络自组织、广覆盖、高容错性以及高精度测量等固有优点以及组网成本低、构建灵活、方便等特点,使得无线传感器网络在军事、民用等领域应用广泛。
本文深入研究了无线传感器网络中的定位跟踪问题,包括节点定位、生化气体源定位以及目标跟踪问题,并设计开发了面向定位跟踪应用研究的平台,为进一步的应用研究打下基础。在上述问题的研究中,针对不同的实际应用场景提出了具有理论和实际价值的定位、跟踪新方法,并通过计算机仿真对性能进行了验证和评价。
具体地,论文主要的研究成果和创新有:
(1)无线传感器网络中的节点定位研究
将无线传感器网络中的节点定位问题看作目标跟踪的对偶问题,提出一种基于虚拟信标点的节点定位方案,区别于基于固定信标点方式的现有定位算法。基于超球面交叉机制,提出了VB-ERL节点定位算法。它利用非线性最小二乘优化方法,求解由能量比对构成的最小化成本函数实现节点自我定位。为了克服VB-ERL节点定位算法存在的弊端,对节点定位问题又提出了一种贝叶斯框架下基于改进粒子滤波的VB-IPF算法,并实现在线迭代预估。
(2)无线传感器网络中的生化气体源定位研究
将无线传感器网络应用于生化气体源定位,以提高人们对突发事件的快速反应能力。首先提出了一种鲁棒性强的极大似然定位算法,对比研究了直接三边法以及非线性最小二乘法。为了消除集中式定位算法的固有缺陷及节省网络能量,将分层传感器网络应用于生化源定位,提出了一种分层传感器网络下的基于改进粒子滤波的分布式定位算法,通过子区域管理节点的状态传递,循环迭代预估得到收敛的生化气体源位置。
(3)无线传感器网络中的目标定位跟踪研究
目标定位跟踪技术无论是在军事还是民用领域都有着重要的应用价值。
首先研究了传感器网络下一种仅有角度测量的移动目标定位跟踪。从提高滤波算法的角度出发来提高目标预估定位精度,提出了一种无线传感器网络下的集中式融合方案,应用SRCDKF-PF算法及其改进措施进行预估。
其次,考虑无线传感器网络中的目标跟踪节能的需要,提出了一种轻量级的自适应机制的分布式目标跟踪算法。在跟踪算法中:采用节点密度自适应的节点激活机制,寻找定位精度与网络能耗之间的平衡;提出的退避定时机制用于头节点的选取及传输序列的确定;基于改进粒子滤波的定位算法提高了滤波的精度;提出的一种波浪式区域逐层唤醒机制用于快速重新定位丢失的目标。
(4)面向定位跟踪的平台设计与开发
面向定位跟踪的平台开发,包括无线传感器网络网关的开发、传感器节点的开发。开发了基于GPRS网络通讯的网络网关,实现与Internet外部网的连接。开发了基于CC1010传感器节点,重点阐述了RF通讯的设计。为进一步的应用和研究打下基础。
Wireless Sensor Network (WSN), which integrates the sensor, micro-electro-mechanism system (MEMS), wireless communication and distributed information processing, becomes a hot research topics at the current Information Technology field. The WSN has many advantages such as self-organization, high accuracy measurements, and high fault-toleration, widely coverage et al. Characteristics of low cost, low power, flexible deployment make it more widely applied ranging from the military areas to the abundant civil areas.
The dissertation deeply studied the localization and target tracking problems in wireless sensor network, including node self-localization, plume source localization and the target tracking problems. General localization and target tracking oriented platform is developed, which serves for further studying and practical applications. Due to the problems listed above, many new localization and tracking algorithms are proposed according to the practical applications in WSN, these algorithms have a certain values on theories and practical applications. Extensive simulations have been conducted to validate and evaluate the performance of the proposed algorithms.
The concrete contents of this dissertation are given as below:
(1) Research on node localization in wireless sensor network
Node localization in wireless sensor networks is treated as a functional dual of target tracking from a novel perspective in the dissertation. A node localization scheme is proposed based on the virtual beacons, which is different from the current fixed beacons node localization algorithm. A VB-ERL localization algorithm is proposed based on the hyper-sphere intersection mechanism. The nodes estimate their locations by solving the least cost function generated by many pairs of received virtual beacons-energy ratios. In order to eliminate the drawbacks of the VB-ERL algorithm, a localization algorithm named VB-IPF which based on the improved particle filter under Bayesian Frame is also proposed. It estimates the node location on line.
(2) Research on plume source localization in wireless sensor network
A wireless sensor networks is proposed to estimate the plume source location. Such WSN can be of tremendous help to emergency personnel trying to protect people from terrorist attacks or responding to an accident. First, a robust centralized localization algorithm named maximum likelihood estimation (MLE) algorithm is proposed. It’s performance is evaluated compared with the direct Trilateration (DT) algorithm and the nonlinear least square (NLS) algorithm. In order to save the energy and eliminate the various problems associated with the centralization algorithms, a hierarchical wireless sensor network is proposed to estimate the plume source location. The performed distributed algorithm is based on the improved particle filter. The source location is obtained by the manager nodes’estimation state transmission in each sub-region in turn.
(3) Research on target tracking in wireless sensor network
Target tracking applications in wireless sensor network have a great value ranging from the military to the abundant civil areas.
A bearings-only tracking for maneuvering target was firstly studied in wireless sensor network. A centralized fusion scheme in WSN was proposed to estimate the target based on the SRCDKF-PF algorithm and its improved methods. It improves the target estimation accuracy from the aspect of the filters improvements.
Second, a new adaptive, distributed lightweight target tracking algorithm is proposed considering the energy saving requirement in WSN. In the algorithm, an adaptive mechanism based on the node density is proposed to obtain optimal active region size. A backoff timer mechanism is proposed to elect the leader node and obtain the transmission order of the localization nodes’measurements. A localization mechanism based on the improved particle filter improves the tracking performance. A step by step recovery mechanism is proposed to relocate the missing target.
(4)Research on target tracking oriented platform of WSN
A target tracking oriented platform of WSN is designed and developed, including gateway and sensor node. The gateway implements the reliable link between WSN and the other networks such as Internet by TCP/IP protocol through the GPRS communication system. The sensor node based on CC1010 chip implements the communication among nodes in WSN. It offers a general target tracking oriented platform for studying of the future related problems in WSN.
本文深入研究了无线传感器网络中的定位跟踪问题,包括节点定位、生化气体源定位以及目标跟踪问题,并设计开发了面向定位跟踪应用研究的平台,为进一步的应用研究打下基础。在上述问题的研究中,针对不同的实际应用场景提出了具有理论和实际价值的定位、跟踪新方法,并通过计算机仿真对性能进行了验证和评价。
具体地,论文主要的研究成果和创新有:
(1)无线传感器网络中的节点定位研究
将无线传感器网络中的节点定位问题看作目标跟踪的对偶问题,提出一种基于虚拟信标点的节点定位方案,区别于基于固定信标点方式的现有定位算法。基于超球面交叉机制,提出了VB-ERL节点定位算法。它利用非线性最小二乘优化方法,求解由能量比对构成的最小化成本函数实现节点自我定位。为了克服VB-ERL节点定位算法存在的弊端,对节点定位问题又提出了一种贝叶斯框架下基于改进粒子滤波的VB-IPF算法,并实现在线迭代预估。
(2)无线传感器网络中的生化气体源定位研究
将无线传感器网络应用于生化气体源定位,以提高人们对突发事件的快速反应能力。首先提出了一种鲁棒性强的极大似然定位算法,对比研究了直接三边法以及非线性最小二乘法。为了消除集中式定位算法的固有缺陷及节省网络能量,将分层传感器网络应用于生化源定位,提出了一种分层传感器网络下的基于改进粒子滤波的分布式定位算法,通过子区域管理节点的状态传递,循环迭代预估得到收敛的生化气体源位置。
(3)无线传感器网络中的目标定位跟踪研究
目标定位跟踪技术无论是在军事还是民用领域都有着重要的应用价值。
首先研究了传感器网络下一种仅有角度测量的移动目标定位跟踪。从提高滤波算法的角度出发来提高目标预估定位精度,提出了一种无线传感器网络下的集中式融合方案,应用SRCDKF-PF算法及其改进措施进行预估。
其次,考虑无线传感器网络中的目标跟踪节能的需要,提出了一种轻量级的自适应机制的分布式目标跟踪算法。在跟踪算法中:采用节点密度自适应的节点激活机制,寻找定位精度与网络能耗之间的平衡;提出的退避定时机制用于头节点的选取及传输序列的确定;基于改进粒子滤波的定位算法提高了滤波的精度;提出的一种波浪式区域逐层唤醒机制用于快速重新定位丢失的目标。
(4)面向定位跟踪的平台设计与开发
面向定位跟踪的平台开发,包括无线传感器网络网关的开发、传感器节点的开发。开发了基于GPRS网络通讯的网络网关,实现与Internet外部网的连接。开发了基于CC1010传感器节点,重点阐述了RF通讯的设计。为进一步的应用和研究打下基础。
Wireless Sensor Network (WSN), which integrates the sensor, micro-electro-mechanism system (MEMS), wireless communication and distributed information processing, becomes a hot research topics at the current Information Technology field. The WSN has many advantages such as self-organization, high accuracy measurements, and high fault-toleration, widely coverage et al. Characteristics of low cost, low power, flexible deployment make it more widely applied ranging from the military areas to the abundant civil areas.
The dissertation deeply studied the localization and target tracking problems in wireless sensor network, including node self-localization, plume source localization and the target tracking problems. General localization and target tracking oriented platform is developed, which serves for further studying and practical applications. Due to the problems listed above, many new localization and tracking algorithms are proposed according to the practical applications in WSN, these algorithms have a certain values on theories and practical applications. Extensive simulations have been conducted to validate and evaluate the performance of the proposed algorithms.
The concrete contents of this dissertation are given as below:
(1) Research on node localization in wireless sensor network
Node localization in wireless sensor networks is treated as a functional dual of target tracking from a novel perspective in the dissertation. A node localization scheme is proposed based on the virtual beacons, which is different from the current fixed beacons node localization algorithm. A VB-ERL localization algorithm is proposed based on the hyper-sphere intersection mechanism. The nodes estimate their locations by solving the least cost function generated by many pairs of received virtual beacons-energy ratios. In order to eliminate the drawbacks of the VB-ERL algorithm, a localization algorithm named VB-IPF which based on the improved particle filter under Bayesian Frame is also proposed. It estimates the node location on line.
(2) Research on plume source localization in wireless sensor network
A wireless sensor networks is proposed to estimate the plume source location. Such WSN can be of tremendous help to emergency personnel trying to protect people from terrorist attacks or responding to an accident. First, a robust centralized localization algorithm named maximum likelihood estimation (MLE) algorithm is proposed. It’s performance is evaluated compared with the direct Trilateration (DT) algorithm and the nonlinear least square (NLS) algorithm. In order to save the energy and eliminate the various problems associated with the centralization algorithms, a hierarchical wireless sensor network is proposed to estimate the plume source location. The performed distributed algorithm is based on the improved particle filter. The source location is obtained by the manager nodes’estimation state transmission in each sub-region in turn.
(3) Research on target tracking in wireless sensor network
Target tracking applications in wireless sensor network have a great value ranging from the military to the abundant civil areas.
A bearings-only tracking for maneuvering target was firstly studied in wireless sensor network. A centralized fusion scheme in WSN was proposed to estimate the target based on the SRCDKF-PF algorithm and its improved methods. It improves the target estimation accuracy from the aspect of the filters improvements.
Second, a new adaptive, distributed lightweight target tracking algorithm is proposed considering the energy saving requirement in WSN. In the algorithm, an adaptive mechanism based on the node density is proposed to obtain optimal active region size. A backoff timer mechanism is proposed to elect the leader node and obtain the transmission order of the localization nodes’measurements. A localization mechanism based on the improved particle filter improves the tracking performance. A step by step recovery mechanism is proposed to relocate the missing target.
(4)Research on target tracking oriented platform of WSN
A target tracking oriented platform of WSN is designed and developed, including gateway and sensor node. The gateway implements the reliable link between WSN and the other networks such as Internet by TCP/IP protocol through the GPRS communication system. The sensor node based on CC1010 chip implements the communication among nodes in WSN. It offers a general target tracking oriented platform for studying of the future related problems in WSN.
引文
[1] Tilak S, Abu-Ghazaleh NB, Heinzelman W, A taxonomy of wireless micro-sensor network models, Mobile Computing and Communications Review, 2002, 1(2):1-8
[2] Akyildiz I, Su W, Sankarasubramaniam Y, Cayirci E, A survey on sensor networks, IEEE Communications Magazine, 2002 (8): 102–114
[3] 李建中,李金宝,石胜飞, 传感器网络及其数据管理的概念、问题与进展, 软件学报,2003,14(10):1717-1727
[4] 孙利民,李建中,陈渝等, 无线传感器网络, 清华大学出版社,2005
[5] 林瑞仲, 面向目标跟踪的无线传感器网络研究, [博士学位论文],浙江大学,2005
[6] 毛剑琳, 无线传感器网络中若干资源优化问题的研究, [博士学位论文],上海交通大学,2006
[7] Wade R, Mitchell WM, Petter F, Ten emerging technologies that will change the world. Technology Review, 2003, 106(1):22-49.
[8] Tubaishat M, Madria S, Sensor networks: an overview, IEEE Potentials, 2003, 22(2): 20-23
[9] Kumar S, Shehperd D, SensIT: sensor information technology for the war fighter, in: Proceedings of ISIF, 2001, pp. 3-9
[10] Cerpa A, Elson J, Estrin D, Girod L, Hamilton M, Zhao J, Habitat monitoring: Application driver for wireless communications technology, in: Proceedings of ACM SIGCOMM Workshop on Data Communications in Latin America and the Caribbean, April 2001.
[11] Mainwaring A, Polastre J, Szewczyk R, Culler D, Anderson J, Wireless sensor networks for habitat monitoring, in: ACM International Workshop on Wireless Sensor Networks and Applications (WSNA'02), 2002
[12] 任丰原, 黄海宁, 林闯, 无线传感器网络, 软件学报, 2003, 14(7):1282-1291
[13] Burrell J, Brooke T, Beckwith R, Vineyard computing: sensor networks in agricultural production, IEEE Pervasive Computing, 2004, 3(1):38–45.
[14] Baggio A, Wireless sensor networks in precision agriculture, in: The REALWSN'05 Workshop on Real-World Wireless Sensor Networks,2005, Stockholm, Sweden
[15] Noury N, Herve T, Rialle V, Virone G, Mercier E. Monitoring behavior in home using a smart fall sensor. In: Proceedings of the IEEE-EMBS Special Topic Conference on Microtechnologies in Medicine and Biology. Lyon: IEEE Computer Society, 2000. 607~610
[16] Intel, Health Research & Innovation, Digital home technologies for aging in place, www.intel.com/research/exploratory/digital_home.htm
[17] Galbreath JH, Townsend CP, Mundell SW, et al., Civil structure strain monitoring with power-efficient high-speed wireless sensor networks, in: International Workshop for Structural Health Monitoring, September 2003.
[18] Schmid T, Dubois-Ferriere H, Vetterli M, SensorScope: Experiences with a wireless building monitoring sensor network, in: The REALWSN'05 Workshop on Real-World Wireless Sensor Networks, Stockholm, Sweden, 2005
[19] 马祖长,孙怡宁,梅涛, 无线传感器网络综述, 通信学报, 2004, 25(4):114-124.
[20] Pottie GJ, Kaiser WJ, Wireless integrated sensor networks, Communications of the ACM, 2000,43(5):51-58
[21] Edgar HC, Wireless sensor networks: architectures and protocols, Boca Raton, Florida: CRC Press LLc,2004:1-40
[22] Kahn JM, Katz RH, Pister KSJ, Next century challenges: mobile networking for smart dust, International Conference on Mobile Computing and Networking (MOBICOM),1999, Seattle, 271-278
[23] Mainwaring A, Polastre J,Szewcyzk R.,Culler D, Anderson J., Wireless sensor networks for habitat monitoring. In: Proceedings of WSNA, 2002:88-97
[24] Sohrabi K,Gao Ilawadhi V, Protocols for self-organization of a wireless sensor network ,IEEE Personal Communications, 2000,7(5) 16-27
[25] Kalidindi R, Ray L, Kannan R, Iyengar S, Distributed energy aware MAC layer protocol for wireless sensor networks, in: Proceedings of International Conference on wireless Networks, 2003 :282-286
[26] Dulman S, van Hoesel L, Nieberg T, Havinga P, Collaborative communication protocols for wireless sensor networks, European Research on Middleware and Architectures for Complex and embedded Systems workshop, 2003
[27] Caccamo M, Lynn YZ, Sha L, Buttazzo G, An implicit prioritized access protocol for wireless sensor networks , in: Proceeding of RTSS’02 , 2002:39-48
[28] Rajendran V, Obraczka K, Garcia-Luna-Aceves JJ, Energy-efficient, collision-free medium access control for wireless sensor networks , in: Proceeding of SenSys03, 2003:181-192
[29] Sridharan A, Krishnamachari B, Max-Min fair collision-free scheduling for wireless sensor networks, in: Proceeding of IEEE International conference on performance, Computing and Communication, 2004:585-590
[30] Woo A, Culler D, A transmission control scheme for media access in sensor networks, In: Proceedings of the ACM MobiCom 2001. Rome: ACM Press, 2001, 221-235.
[31] van Dam T, Langendoen K, An Adaptive energy-efficient MAC protocol for wireless sensor networks, in: Proceedings of Sensys03, 2003:171-180
[32] Alec W, David E Culler, A transmission control scheme for media access in sensor networks, in: Proceeding of the Seventh Annual International Conference on Mobile Computing and Networking, 2002:221-235
[33] Kyle J, Balakrishan H, Tay YC, Sift: A MAC protocol for event-driven wireless sensor networks, Cambridge: MIT Lab for computer science, Technical Report MIT-LCS-TR-894 5,2,2003:1-12
[34] Stein G, Kabitzsch L, A radio protocol for low power wireless sensor networks, in: proceedings of FET’03, 2003:53-58
[35] Amre E1, Decotignie J-D, WiseMAC: An ultra low power MAC protocol for multi-hop wireless sensor network, in: Proceedings of ALGOSENSORS’04, Lecture Notes in computer Science, 2004:18-31
[36] Shih E, Cho S, Ickes N, Min R, Sinha A, Wang A, Chandrakasan A, Physical layer driven algorithm and protocol design for energy-efficient wireless sensor networks, in: Proceeding MOBICOM, 2001, 272-287
[37] Cho SH, Chandrakasan AP, Energy efficient protocols for low duty cycle wireless microsensor networks, in: ICASSP 2001, May 2001.
[38] Guo C, Zhong LC, Rabaey JM, Low power distributed MAC for ad hoc sensor radio networks, in: IEEE Global Telecommunications Conference (GLOBECOM '01), 2001, 2944-2948.
[39] Rhee L, Warrier A., Aia M, Min J, Z-MAC: a hybrid MAC for wireless sensor networks, in: Proceeding of ACM Conference on Embedded Networked Sensor Systems (Sensys’05), San Diego, USA, 2005, 90-101
[40] Hedetniemi S, Liestman A, A survey of gossiping and broadcasting in communication networks, IEEE Networks, 1988,18(4):319-349
[41] Estrin D, Govindan Heidemann J, Kumar S, Next century challenges: Scalable coordinate in sensor network.In:Proceedings of the 5th ACM/IEEE International Conference on Mobile Computing and Networking, Seattle:IEEE Computer Society,1999,263-270
[42] Shah R, Rabaey J. Energy aware routing for low energy ad hoc sensor networks. In: Proc. of the IEEE Wireless Communications and Networking Conf. Orlando: IEEE Communications Society, 2002. 350-355
[43] Braginsky D, Estrin D, Rumor routing algorithm for sensor networks. In: Proc. of the 1st workshop on sensor networks and applications. Atlanta: ACM Press, 2002. 22-31
[44] Schurgers C, Srivastava MB. Energy efficient routing in wireless sensor networks. In: Proc. of the MILCOM on Communications for Network-Centric Operations: Creating the Information Force. Virginia: IEEE Communications Society, 2001. 357-361
[45] Chu M, Haussecker H, Zhao F, Scalable information-driven sensor querying and routing for ad hoc heterogeneous sensor networks. International Journal on High Performance Computing Applications, 2002,16(3):293-313
[46] Yao Y, Gehrke J. The cougar approach to in-network query processing in sensor networks. SIGMOD Record, 2002,31(3):9-18
[47] Sadgopan N, Krishnamachari B, Helmy A, The ACQUIRE mechanism for efficient querying in sensor networks, in: proceeding of the 1th IEEE international workshop on sensor network protocols and applications (SNPA’03), 2003:149-155
[48] Heinzelman WR, Chandrakasan A, Balakrishnan H. Energy-efficient communication protocol for wireless microsensor networks. In: Proc. of the Hawaii Int'l Conf. on System Sciences. San Francisco: IEEE Computer Society, 2000. 3005-3014
[49] Lindsey S, Raghavendra CS, PEGASIS: Power efficient gathering in sensor information systems. In: Proc. of the IEEE Aerospace Conf. San Francisco: IEEE Computer Society, 2002, 1-6
[50] Manjeshwar A, Agrawal DP. TEEN: A protocol for enhanced efficiency in wireless sensor networks. In: Int'l Proc. of the 15th Parallel and Distributed Processing Symp. San Francisco: IEEE Computer Society, 2001. 2009-2015
[51] Karp B, Kung H. GPSR: Greedy perimeter stateless routing for wireless networks. In: Proc. of the 6th Annual Int'l Conf. on Mobile Computing and Networking. Boston: ACM Press, 2000, 243-254
[52] Yu Y, Govindan R, Estrin D, Geographical and energy aware routing: A Recursive Data Dissemination Protocol for Wireless Sensor Networks, Technical Report UCLA/CSD-TR-01-0023, University of Southern California, May 2001
[53] Lu C, Blum BM, Abdelzaher TF, Stankovic JA, He T, RAP: A real-time communication architecture for large-scale wireless sensor networks, in: Proceeding of the IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2002), San Jose, CA, September 2002, 55-68.
[54] Niculescu D, Nath B, Trajectory based forwarding and its applications, in: Proceeding of the 9th Annual Int'l Conf. on Mobile Computing and Networking. San Diego: ACM Press, 2003, 260-272.
[55] He T, Stankovic JA, Lu C, Abdelzaher T, SPEED: A stateless protocol for real-time communication in sensor networks, in: Proceeding of the 23rd International Conference on Distributed Computing Systems, 2003, 46 - 55
[56] Sohrabi K, Gao J, Ailawadhi V, Pottie GJ, Protocols for self-organization of a wireless sensor network, IEEE Personal Communications, 2000,7(5l):l6-27
[57] Akkaya K, Younis M, An Energy-aware Qos routing protocol for wireless sensor network , in: Proceeding of ICDCSW’03, 2003:710-719
[58] Savidge L, Huang L, Aghajan H, Goldsmith A, QoS-based geographic routing for event-driven image sensor networks, in: proceeding of the 2nd International Conference on Broadband Networks, 2005, 68-77.
[59] Felemban, E, Lee CG, Ekici E, MMSPEED: Multipath multi-SPEED protocol for QoS guarantee of reliability and timeliness in wireless sensor networks, IEEE Transactions on Mobile Computing, 2006, 5(6): 738 - 754.
[60] Wan CY, Campbell AT, Krishnamurthy L, Pump-slowly, fetch-quickly (PSFQ): a reliable transport protocol for sensor networks, IEEE Journal on Selected Areas in Communications, 2005, 23(4):862-872
[61] Fred Stann, John Heidemann, RMST: Reliable data transport in sensor networks, In Proceedings of the First International Workshop on Sensor Net Protocols and Applications, Anchorage, Alaska, USA, IEEE, 2003, 102-112
[62] Sankarasubramaniam Y, Akan O, Akyildiz I, ESRT: Event-to-Sink reliable transport in wireless sensor networks, IEEE/ACM Trans. On Networking, 2005, 13(5):1003 - 1016
[63] Shane B, Eisenman, Chieh-Yih Wan and Andrew T. Campbell, PSFQ++: critique and suggestions for Source-to-Sink reliable transport, Technical Report CU/EE/TAP-TR-2004-11-002, November 10, 2004:1-6
[64] Karenos, K, Kalogeraki V, Krishnamurthy SV, Cluster-based congestion control for supporting multiple classes of traffic in sensor networks, in: proceeding of The Second IEEE Workshop on Embedded Networked Sensors (EmNetS-II), 2005,107-114
[65] Tan K, Jiang F, Zhang Q, and. Shen X, Congestion control in multi-hop wireless networks, sensor and Ad Hoc communications and networks, IEEE SECON’05. 2th Annual IEEE Communications Society Conference on, 2005, 96-106
[66] Elson J, Girod L, Estrin D. Fine-Grained network time synchronization using reference broadcasts. In: Proc. of the 5th Symp. on Operating Systems Design and Implementation. ACM Press, 2002. 147-163
[67] Ping S, Delay measurement time synchronization for wireless sensor networks, Intel research Berkeley lab, 2003, http: //www.intel_research.net/publications/berkeley/081120031327_137.pdf
[68] Maroti M, Kusy B, Simon G, et al., The flooding time synchronization protocol, Technical Report, Vanderbilt University,2004
[69] He T, Huang CD, Blum BM, Stankovic JA, Abdelzaher T, Range-Free localization schemes in large scale sensor networks. In: Proceeding of the 9th Annual Int'1 Conf. on Mobile Computing and Networking. San Diego: ACM Press, 2003. 81-95
[70] Hightower J, Vakili C, Borriello G, Want R, Design and calibration of the spot on ad-hoc location sensing system, CSE Techniuqe Report, University of Washington, August 2001.
[71] Savvides A, Han C, Strivastava MB, Dynamic fine-grained localization in ad-hoc networks of sensors, in Proc. MobiCom, 2001.
[72] Whitehouse K, The design of calamari: an ad-hoc localization system for sensor networks, Master’s Thesis, University of California at Berkeley, 2002.
[73] Moore D, Leonard J, Rus D, Teller S, Robust distributed network localization with noisy range measurements, in Proc. SenSys, 2004.
[74] B.D. Van Veen and K.M. Buckley, Beamforming: A versatile approach to spatial filtering, IEEE ASSP Mag., 1988, 5(2): 4–24
[75] Stoica P, Moses RL, Introduction to spectral analysis. Englewood Cliffs, NJ: Prentice-Hall, 1997.
[76] Ottersten B, Viberg M, Stoica P, Nehorai A, Exact and large sample ML techniques for parameter estimation and detection in array processing, in Haykin, Litva, and Shepherd, Editors, Radar Array Processing, Springer-Verlag, Berlin, 1993, 99–151.
[77] Priyantha NB, Chakraborty A, Balakrishnan H, The Cricket location-support system, In Mobile Computing and Networking, pp.32–43, 2000.
[78] Patwari N, Hero III AO, Perkins M, et al., Relative location estimation in wireless sensor networks, IEEE Trans. Signal Processing, 2003, 51( 8): 2137–2148
[79] Niculescu D, Nath B, Ad hoc positioning system (APS) using AOA, In: Proceed of IEEE INFOCOM, San Francisco, CA, Mar. 2003.
[80] Biswas P, Ye Y, A distributed method for solving semidefinite programs arising from ad hoc wireless sensor network localization, Dept. of Computer Science, Stanford Univ., Stanford, CA, Tech. Rep., Oct.2003.
[81] Shang Y, Ruml W, Zhang Y, Fromherz MPJ, Localization from mere connectivity, In: Proceed of. The Mobihoc‘03, June 2003, pp. 201–212.
[82] Shang Y, Ruml W, Improved MDS-based localization, in IEEE Proc.Infocom‘04, 2004: 2640–2651.
[83] Bulusu N, Heidemann J, Estrin D, GPS-less low cost outdoor localization for very small devices. IEEE Personal Communication,2000,7(5):28-34
[84] D. Niculescu and B. Nath, Ad hoc positioning system (APS), In: Proceed of the IEEE GlobeCom, San Sntonio, AZ, Nov, 2001
[85] Nagpal R, Organizing a global coordinate system from local information on an amporphous computer. AI Memo 1666, MIT AI Laboratory, August 1999
[86] He T, Huang C, Blum BM, Stankovic JA, Abdelzaher T, Range-free localization schemes for large scale sensor networks. In: Proceed of 9th Annual Int’1 Conf on Mobile Computing and Networking (Mobicom), San Diego, CA., 2003: 81-95
[87] Sichitiu ML, Ramadurai V, Localization of wireless sensor networks with a mobile beacon, Center for Advances Computing Communications, North Carolina State Univ., Tech. Rep.TR-03/06, Jul. 2003.
[88] Sun GL, Guo W, Comparison of distributed localization algorithms for sensor network with a mobile beacon, In: Proceed of IEEE Int. Conf. Networking, Sensing Control (ICNSC), Taipei, Taiwan, R.O.C., Mar. 2004, pp. 536–540.
[89] Galstyan A, Krishnamachari B, Lerman K, et al. Distributed online localization in sensor networks using mobile target, In: Proceed of the international Symposium on information Processing Sensor Networks, Berkeley, CA, 2004:61-70
[90] Priyantha NB, Balakrishnan H, Demaine E, and Teller S, Mobile-assisted localization in wireless sensor networks, In: Proceed of the IEEE Infocom, vol. 1, March 2005, pp. 172– 183.
[91] Kuo-Feng Ssu; Chia-Ho Ou; Jiau, HC, Localization with mobile anchor points in wireless sensor networks, IEEE Transactions on Vehicular Technology, 2005,54(3):1187-1197
[92] Hu L and Evans D, Localization for mobile sensor networks, in: ACM Mobicom’04, Philadelphia, Pennsylvania, September,2004
[93] Zhang L, Cheng Q, Wang Y and Zeadally S, A novel high performance distributed sensor positioning system, online technical report, www.ece.eng.wayne.edu/~qcheng/Landscape.pdf
[94] Gupta R, Das SR, Tracking moving targets in a smart sensor network. The VTC Fall 2003 Symposium,Oct,2003
[95] Mechitov K, Sundresh S, Kwon Y, Agha G, Cooperative tracking with binary-detection sensor networks, In: Proceeding 1st Int. Conf. on Embedded Networked Sensor System(SenSys03), Los Angeles,CA, November 5-7,2003
[96] Zhao F, Shin J, Reich J, Information-Driven dynamic sensor collaboration for tracking applications, IEEE Signal Processing Magazine, 2002, 19(2):61-72
[97] Chu M, Haussecker H, Zhao F, Scalable information-driven sensor querying and routing for ad hoc heterogeneous sensor networks. International Journal on High Performance Computing Applications, 2002,16(3):293-313.
[98] Liu J, Cheung P, Guinbas L, et al., A Dual-Space approach to tracking and sensor management in wireless sensor networks, Proc. 1st ACM Int’1 workshop on wireless sensor network and applications, Atlanta, GA. 2003.131-139
[99] Ramanathan P, Location-centric approach for collaborative target detection, classification, and tracking, IEEE CAS Workshop, 2002.
[100] Brook R, Ramanathan P, Sayeed A, distributed target classification and tracking in sensor networks, Proc. of IEEE, 2003, 91(8):1163-1171
[101] Brooks R, Griffin C, Traffic model evaluation of ad hoc target tracking algorithms, International Journal of High Performance Computing Applications, 2002, 16(3): 221-234
[102] Brooks R, Griffin C, and Friedlander DS, Self-Organized distributed sensor network entity tracking, International Journal of High Performance Computing Applications, 2002,16(3): 207-219
[103] Zhang W, Cao G, DCTC: Dynamic convoy tree-based collaboration for target tracking in sensor networks, IEEE Transactions on Wireless Communications, 2004,3(5):1689-1701
[104] Guo D, Wang X, Dynamic sensor collaboration via sequential Monte Carlo, IEEE Journal on Selected Areas in Communication, 2004, 22(6):1037-1047
[105] Sheng X, Hu Y, Distributed particle filter with GMM approximation for multiple target localization and tracking in wireless sensor network, In: Proceeding of the international symposium of information processing in sensor networks,(Los Angeles, CA), 2005. 181-188
[106] Xiao W, Adaptive sensor scheduling for target tracking in wireless sensor network, Advanced Signal Processing Algorithms, Architectures, and Implementations XV. In Proceedings of the SPIE, 2005, Volume 5910, pp.104-112
[107] Lee J, Cho K, Lee S, et al., Distributed and energy-efficient target localization and tracking in wireless sensor networks, Computer Communications, 2006, 29(2006):2494-2505
[108] Megerian S, Koushanfar F, Qu G, Veltri G,. Potkonjak M, Exposure in wireless sensor networks: theory and practical solutions, Journal of Wireless Networks, 2002, 8(5): 443–454
[109] Meguerdichian S, Koushanfar F, Qu G, Potkonjak M, Exposure in wireless Ad Hoc sensor networks, In: proceeding of International Conference on Mobile Computing and Networking (MobiCom ’01), pp. 139–150, Rome, Italy, July 2001.
[110] Clouqueur T, Phipatanasuphorn V, Ramanathan P, Saluja KK, Sensor deployment strategy for target detection, The First ACM International Workshop on Wireless Sensor Networks and Applications (WSNA’02), Sep. 2002.
[111] Chakrabarty K, Iyengar SS, Qi H, Cho EC, Grid coverage for surveillance and target location in distributed sensor networks, IEEE Transactions on Computers.2002,51(12):1448-1453.
[112] Jung, B, Sukhatme GS, Tracking Targets using Multiple Robots: The effect of environment occlusion, Autonomous Robots, 2002,13(3):191-205
[113] Bejar R, Krishnamachari B, Gomes C, Selman B, Distributed constraint satisfaction in a wireless sensor tracking system, Workshop on Distributed Constraint Reasoning, International Joint Conference on Artificial Intelligence, Seattle, Washington, August 2001.
[114] Li D, Wong K, Hu Y, Sayeed A, Detection, classification, tracking of targets in micro-sensor networks, IEEE Signal Processing Magazine, 2002,19(2):17–29
[115] Fang Q, Zhao F, Guibas L, Counting targets: building and managing aggregates in wireless sensor networks, Palo Alto Research Center Technical Report, pp.2002–10298, June 2002.
[116] 邓小龙,基于粒子滤波的目标跟踪与系统辨识方法的研究, [博士学位论文],上海交通大学,2005
[117] 李安平,复杂环境下的视频目标跟踪算法研究, [博士学位论文],上海交通大学,2006
[118] 张尧庭,贝叶斯统计推断, 科学出版社,1991
[119] Kalman R.E., A new approach to linear filtering and prediction and prediction problems, Trans. ASME, Journal of basic Engineering, 1960,82D(1):35-45
[120] Jazwinski AH, Stochastic processes and filtering theory, New York, Academic Press,1970.
[121] Wan EA, Van Der Merwe R, The unscented Kalman filter for nonlinear estimation, In: proceeding of the Symposium on Adaptive Systems for Signal Processing, Communication and control, 2000, pp:153 - 158.
[122] Julier SJ, The scaled unscented transformation, In: Proceeding of America Control Conference, Anchorage Alaska:IEEE,2002,6:4555-4559
[123] Kitagawa G, Non-Gaussian state-space modeling of non-stationary time series, Journal of computation and graphical statistics, 1987,82(400):1032-1063
[124] Alspach DL, Sorerison HW, Nonlinear Bayesian estimation using Gaussian sum approximation. IEEE Trans. Automatic Control, 1972,17(4):439-448
[125] Rabiner LR, A tutorial on hidden markov models and selected applications in speech recognition, Proceeding of the IEEE, 1989,77(2):257-285
[126] 胡拱涛, 主/被动目标跟踪研究, [博士学位论文] 上海交通大学,2005
[127] Gordon NJ, Salmond DJ, Smith AF, Novel approach to nonlinear/non Gaussian Bayesian state estimation , IEE Proceedings-F (0143-7070), 1993, 140(2):107-113.
[128] Liu JS, Chen R, Sequential Monte Carlo methods for dynamic system, Journal of the American Statistical Association, 1998, 93(443) : 1032-1044
[129] Kitagawa G, Monte carlo filter and smoother for Non-Gaussian nonlinear state space models, Journal of computation and graphical statistics, 1996, 5(1):1-25
[130] Doucet A, On sequential simulation-based methods for Bayesian filtering, Technical Report CUED-F-ENG-TR310,Dept. of. Engineering, University of Cambridge,1998
[131] Crisan D, Doucet A, A survey of convergence results on particle filtering methods for practitioners, IEEE Trans. Signal Processing, 2002, 5(3):738-746
[132] Arulampalam MS, Maskell S, Gordon N, and Clapp T, A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE Trans. on signal Processing, 2002,50(2):174-188
[133] Carlin BP, Polson NG, Stoffer DS, A Monte Carlo approach to non-normal and nonlinear state-space modeling, Journal of the American Statistical Assoc., 1992,87(418):493-500
[134] Andrieu C, Djuric P, Doucet A, Model selection by MCMC computation, Signal processing, 2001, 81(1):19-37,
[135] Gilks W, Berzuini C, Following a moving target-Monte Carlo inference for Bayesian dynamic models, Journal of royal Statistic society B, 2004, 63(1):127-146,
[136] Andrieu C, de Freitas N, Doucet A, et al., An introduction to MCMC for machine learning. Machine Learning (0885-6125), 2003, 50(1/2):5-43
[137] Chen R, Liu JS, Predictive updating methods with application to Bayesian classification, Journal of the Royal Statistical Society B, 1996, 58:397-415
[138] Tanizaki H, Mariano RS, Prediction filtering and smoothing in non-linear and non-normal cases using monte carlo integration, Journal of applied econometrics, 1994, 9(2):163-179
[139] Tanizaki H, Mariano RS, Nonlinear and Non-Gaussian state space modeling with monte carlo simulations. Journal of Econometrics, 1998,83(1&2):263-290
[140] de Freitas JFG, Niranjan M, Gee AH and Doucet A, Sequential monte carlo methods to train neural network models, Neural Computation, 2000,12(4):955-993,
[141] van der Merwe R, de Freitas N, Doucet A and Wan E, The unscented particle filter, Technical Report CUED/F-INFENG-TR380, Cambridge University Engineering Department, 2000
[142] Garrick Ing, Distributed particle filters for object tracking in sensor networks, , McGill University, 2005,1-102
[143] Zhao F, Guibas L, Wireless Sensor Networks: An information processing approach, Boston: Elsevier-Morgan Kaufmann Publishers, 2004
[144] Mao G, Fidan B, Brian DO Anderson, Wireless sensor network localization techniques, Computer Networks,2007, 51(10):2529-2553
[145] Capkun S, Hamdi M, Hubaux J-P., GPS-Free positioning in mobile ad-hoc networks, Cluster Computing,2002,5(2):157-167
[146] Doherty L, Pister KSJ, Ghaoui LE, Convex position estimation in wireless sensor networks, In: Proceeding of the IEEE INFOCOM 2001,Vo1.3, Anchorage: IEEE Computer and Communications Societies,2001. 1655-1663.
[147] Meguerdichian S, Koushanfar F, Potkonjak M, Srivastava MB, Coverage problems in wireless ad-hoc sensor networks, In: Proceeding of the IEEE INFOCOM 2001. Vol.3, Anchorage: IEEE Computer and Communications Societies, 2001, 1380-1387.
[148] Bulusu N, Heidemann J, Estrin D, Adaptive beacon placement, In: Proceedings of 21st IEEE International Conference on Distributed Computing Systems, IEEE Computer Society, Los Angeles, CA, United States ,2001, 489-498.
[149] Hightower J, Boriello G., Location systems for ubiquitous computing, Computer, 2001, 34(8):57-66
[150] Sun G, Chen J,Guo W; Liu, KJR,Signal processing techniques in network-aided positioning: a survey of state-of-the-art positioning designs, IEEE Signal Processing Magazine, 2005,22(4): 12–23.
[151] Sayed AH, Tarighat A, Khajehnouri N, Network-based wireless location: challenges faced in developing techniques for accurate wireless location information, IEEE Signal Processing Magazine, 2005,22(4): 24–40.
[152] Gustafsson F,Gunnarsson F,Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements, IEEE Signal Processing Magazine,2005,22(4): 41–53.
[153] Camp T, Boleng J, Davies V, A survey of mobility models for Ad Hoc networks research, wireless communications and mobile computing, Special issue on Mobile Ad Hoc Networking Research, Trends and Applications, 2002,2(5):483-502
[154] Li D, Hu Y, Energy-based collaborative source localization using acoustic microsensor array, EURASIP Journal on Applied Signal Processing 2003:4,321–337
[155] 王福豹,史龙,任丰原, 无线传感器网络中的自身定位系统和算法, 软件学报,2005, 16(5):857-868
[156] Zhang Y, Ackerson L, Duff D et al, STAM: A System of tracking and mapping in real environments, IEEE Wireless Magazine, 2004, 11(6):87-96
[157] Michalis P Michaelides, Christos G Panayiotou. Plume source position estimation using sensor networks, in: proceedings of the 13th Mediterranean conference on control an automation, Limassol Cyprus 2005:731-736
[158] Michalis P Michaelides, Christos G Panayiotou, Event source position estimation using sensor networks, Control and Automation, MED '06.14th Mediterranean Conference on June 2006:1- 6
[159] Glenn T. Nofsinger, Tracking based plume detection, DARTMOUTH COLLEGE,2006
[160] Farrell J., Pang S, Li W, Plume mapping via hidden markov methods, IEEE Transactions on Systems, Man and Cybernetics-PART B: Cybernetics, 2003, 33(6):850-863
[161] Zarzhitsky D, Spears DF, Spears WM, Distributed robotics approach to chemical plume tracing , Edmonton, Alberta: In: Proceeding of the IEEE/RSJ International Conference on Intelligent Robots and Systems.(IROS’05), 2005:4034-4039
[162] Ishida H, Nakayama G, Nakamoto T, Moriizumi T, Controlling a gas/odor plume-tracking robot based on transient responses of gas sensors, IEEE Sensors Journal, 2005, 5(3):537-545
[163] Adam T. Hayes, Alcherio Martinoli, Distributed odor source localization, IEEE Sensors Journal, 2002, 2(3): 260-271
[164] Kulesz J, Development of a common data highway for comprehensive incident management, Tech. Rep., 2003
[165] Brennan S, Mielke A, Torney D and Maccabe A, Radiation detection with distributed sensor networks, IEEE Computer Magazine, 2004, 37(8): 57–59
[166] Braun JJ, Glina Y, Stein D and Fox E, Multi-sensor information fusion for biological sensor networks and cbrn detection, In: Proceeding of Conf. Science and Technology for Chem-Bio Information Systems, Williamsburg, VA, October 2004.
[167] Braun JJ, Glina Y, Su JK, Urban biodefense oriented aerosol anomaly detection using sensor data fusion, In: Proceeding of 1st Joint Conf. Battle Management for Nuclear, Chemical, Biological and Radiological Defense, November 2002.
[168] Braun JJ, Glina Y, Su JK, Dasey TJ, Computational intelligence in biological sensing, in: Proceedings of SPIE, 5416, 2004
[169] Sheng X, Hu Y, Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks, IEEE Transactions on Signal Processing, 2005, 53(1): 44-53.
[170] 周宏仁,敬忠良,王培德, 机动目标跟踪, 国防工业出版社, 1991,1-366
[171] 陈利斌, 机动目标跟踪理论和算法研究, [博士学位论文],西北工业大学,2003,1-98
[172] Li XR, Jilkov VP, A survey of maneuvering target tracking: dynamic models, in: Proceeding of SPIE Conference on Signal and Data Processing of Small Targets, April, 2000, Vol. 4048, pp. 212-235
[173] Aidala VJ, Kalman filter behavior in bearing-only tracking applications. IEEE Trans. On Aerospace and Electronic systems (0018-9251), 1979, 15(1):29-39
[174] Aidala VJ, Hammel S, Utilization of modified polar coordinates for bearing-only tracking, IEEE Trans. On automatic Control(0018-9286),1983,28(3):283-294
[175] Aidala VJ, Nardone S, Biased estimation properties of the pseudo-linear tracking filter, IEEE Trans. On Aerospace and Electronic systems (0018-9251), 1982, 18(4):432-441
[176] van der Merwe R, Wan E, Sigma-point Kalman Filters for probabilistic inference in dynamic state-space models , PhD thesis, OGI School of Science & Engineering at Oregon Health & Science University Portland, OR, April 2004.
[177] Lee J, Cho K, Lee S, et al., Distributed and energy-efficient target localization and tracking in wireless sensor networks, Computer Communications, 2006, 29(2006):2494-2505
[178] Xu Y, Winter J, Lee W, Prediction-based strategies for energy saving in object tracking sensor networks, In: Proceeding of the 2004 IEEE International Conference on Mobile Data Management (MDM’04), 2004, 346-357
[179] Dunkels A, Voigt J, Alonso T, Ritter H. and Schiller J, Connecting wireless sensornets with TCP/IP networks, In Conference on Wired/Wireless Internet Communications, 2004, LNCS 2957,pp 143–152, 2004
[180] Dunkels A, Full TCP/IP for 8-bit architectures, In: Proceedings of the First International Conference on Mobile Systems, Applications, and Services (MOBISYS ‘03), May 2003
[181] 吕捷, GPRS 技术, 北京邮电大学出版社,2001
[182] 赵锋,王艳玮,范建华等,GPRS 终端拨号上网连接认证注册全过程研究, 计算机工程与应用,2004,40(23):158-160
[183] Perkins D, Requirements for an internet standard Point-to-Point protocol, RFC1547, Carnegie Mellon University, 1993.
[184] Richard Stevens W, TCP/IP 详解, 机械工业出版社,1999
[185] Chipcon AS, Single chip very low RF transceiver with 8051 compatible microcontroller, http://www.chipcon.com/files/CC1010_Data_Sheet_1_3.pdf
[186] 邓 小 龙 , 谢 剑 英 , 基 于 粒 子 滤 波 的 仅 有 角 测 量 的 被 动 跟 踪 , 上 海 交 通 大 学 学报,2005,39(6):993-996
[2] Akyildiz I, Su W, Sankarasubramaniam Y, Cayirci E, A survey on sensor networks, IEEE Communications Magazine, 2002 (8): 102–114
[3] 李建中,李金宝,石胜飞, 传感器网络及其数据管理的概念、问题与进展, 软件学报,2003,14(10):1717-1727
[4] 孙利民,李建中,陈渝等, 无线传感器网络, 清华大学出版社,2005
[5] 林瑞仲, 面向目标跟踪的无线传感器网络研究, [博士学位论文],浙江大学,2005
[6] 毛剑琳, 无线传感器网络中若干资源优化问题的研究, [博士学位论文],上海交通大学,2006
[7] Wade R, Mitchell WM, Petter F, Ten emerging technologies that will change the world. Technology Review, 2003, 106(1):22-49.
[8] Tubaishat M, Madria S, Sensor networks: an overview, IEEE Potentials, 2003, 22(2): 20-23
[9] Kumar S, Shehperd D, SensIT: sensor information technology for the war fighter, in: Proceedings of ISIF, 2001, pp. 3-9
[10] Cerpa A, Elson J, Estrin D, Girod L, Hamilton M, Zhao J, Habitat monitoring: Application driver for wireless communications technology, in: Proceedings of ACM SIGCOMM Workshop on Data Communications in Latin America and the Caribbean, April 2001.
[11] Mainwaring A, Polastre J, Szewczyk R, Culler D, Anderson J, Wireless sensor networks for habitat monitoring, in: ACM International Workshop on Wireless Sensor Networks and Applications (WSNA'02), 2002
[12] 任丰原, 黄海宁, 林闯, 无线传感器网络, 软件学报, 2003, 14(7):1282-1291
[13] Burrell J, Brooke T, Beckwith R, Vineyard computing: sensor networks in agricultural production, IEEE Pervasive Computing, 2004, 3(1):38–45.
[14] Baggio A, Wireless sensor networks in precision agriculture, in: The REALWSN'05 Workshop on Real-World Wireless Sensor Networks,2005, Stockholm, Sweden
[15] Noury N, Herve T, Rialle V, Virone G, Mercier E. Monitoring behavior in home using a smart fall sensor. In: Proceedings of the IEEE-EMBS Special Topic Conference on Microtechnologies in Medicine and Biology. Lyon: IEEE Computer Society, 2000. 607~610
[16] Intel, Health Research & Innovation, Digital home technologies for aging in place, www.intel.com/research/exploratory/digital_home.htm
[17] Galbreath JH, Townsend CP, Mundell SW, et al., Civil structure strain monitoring with power-efficient high-speed wireless sensor networks, in: International Workshop for Structural Health Monitoring, September 2003.
[18] Schmid T, Dubois-Ferriere H, Vetterli M, SensorScope: Experiences with a wireless building monitoring sensor network, in: The REALWSN'05 Workshop on Real-World Wireless Sensor Networks, Stockholm, Sweden, 2005
[19] 马祖长,孙怡宁,梅涛, 无线传感器网络综述, 通信学报, 2004, 25(4):114-124.
[20] Pottie GJ, Kaiser WJ, Wireless integrated sensor networks, Communications of the ACM, 2000,43(5):51-58
[21] Edgar HC, Wireless sensor networks: architectures and protocols, Boca Raton, Florida: CRC Press LLc,2004:1-40
[22] Kahn JM, Katz RH, Pister KSJ, Next century challenges: mobile networking for smart dust, International Conference on Mobile Computing and Networking (MOBICOM),1999, Seattle, 271-278
[23] Mainwaring A, Polastre J,Szewcyzk R.,Culler D, Anderson J., Wireless sensor networks for habitat monitoring. In: Proceedings of WSNA, 2002:88-97
[24] Sohrabi K,Gao Ilawadhi V, Protocols for self-organization of a wireless sensor network ,IEEE Personal Communications, 2000,7(5) 16-27
[25] Kalidindi R, Ray L, Kannan R, Iyengar S, Distributed energy aware MAC layer protocol for wireless sensor networks, in: Proceedings of International Conference on wireless Networks, 2003 :282-286
[26] Dulman S, van Hoesel L, Nieberg T, Havinga P, Collaborative communication protocols for wireless sensor networks, European Research on Middleware and Architectures for Complex and embedded Systems workshop, 2003
[27] Caccamo M, Lynn YZ, Sha L, Buttazzo G, An implicit prioritized access protocol for wireless sensor networks , in: Proceeding of RTSS’02 , 2002:39-48
[28] Rajendran V, Obraczka K, Garcia-Luna-Aceves JJ, Energy-efficient, collision-free medium access control for wireless sensor networks , in: Proceeding of SenSys03, 2003:181-192
[29] Sridharan A, Krishnamachari B, Max-Min fair collision-free scheduling for wireless sensor networks, in: Proceeding of IEEE International conference on performance, Computing and Communication, 2004:585-590
[30] Woo A, Culler D, A transmission control scheme for media access in sensor networks, In: Proceedings of the ACM MobiCom 2001. Rome: ACM Press, 2001, 221-235.
[31] van Dam T, Langendoen K, An Adaptive energy-efficient MAC protocol for wireless sensor networks, in: Proceedings of Sensys03, 2003:171-180
[32] Alec W, David E Culler, A transmission control scheme for media access in sensor networks, in: Proceeding of the Seventh Annual International Conference on Mobile Computing and Networking, 2002:221-235
[33] Kyle J, Balakrishan H, Tay YC, Sift: A MAC protocol for event-driven wireless sensor networks, Cambridge: MIT Lab for computer science, Technical Report MIT-LCS-TR-894 5,2,2003:1-12
[34] Stein G, Kabitzsch L, A radio protocol for low power wireless sensor networks, in: proceedings of FET’03, 2003:53-58
[35] Amre E1, Decotignie J-D, WiseMAC: An ultra low power MAC protocol for multi-hop wireless sensor network, in: Proceedings of ALGOSENSORS’04, Lecture Notes in computer Science, 2004:18-31
[36] Shih E, Cho S, Ickes N, Min R, Sinha A, Wang A, Chandrakasan A, Physical layer driven algorithm and protocol design for energy-efficient wireless sensor networks, in: Proceeding MOBICOM, 2001, 272-287
[37] Cho SH, Chandrakasan AP, Energy efficient protocols for low duty cycle wireless microsensor networks, in: ICASSP 2001, May 2001.
[38] Guo C, Zhong LC, Rabaey JM, Low power distributed MAC for ad hoc sensor radio networks, in: IEEE Global Telecommunications Conference (GLOBECOM '01), 2001, 2944-2948.
[39] Rhee L, Warrier A., Aia M, Min J, Z-MAC: a hybrid MAC for wireless sensor networks, in: Proceeding of ACM Conference on Embedded Networked Sensor Systems (Sensys’05), San Diego, USA, 2005, 90-101
[40] Hedetniemi S, Liestman A, A survey of gossiping and broadcasting in communication networks, IEEE Networks, 1988,18(4):319-349
[41] Estrin D, Govindan Heidemann J, Kumar S, Next century challenges: Scalable coordinate in sensor network.In:Proceedings of the 5th ACM/IEEE International Conference on Mobile Computing and Networking, Seattle:IEEE Computer Society,1999,263-270
[42] Shah R, Rabaey J. Energy aware routing for low energy ad hoc sensor networks. In: Proc. of the IEEE Wireless Communications and Networking Conf. Orlando: IEEE Communications Society, 2002. 350-355
[43] Braginsky D, Estrin D, Rumor routing algorithm for sensor networks. In: Proc. of the 1st workshop on sensor networks and applications. Atlanta: ACM Press, 2002. 22-31
[44] Schurgers C, Srivastava MB. Energy efficient routing in wireless sensor networks. In: Proc. of the MILCOM on Communications for Network-Centric Operations: Creating the Information Force. Virginia: IEEE Communications Society, 2001. 357-361
[45] Chu M, Haussecker H, Zhao F, Scalable information-driven sensor querying and routing for ad hoc heterogeneous sensor networks. International Journal on High Performance Computing Applications, 2002,16(3):293-313
[46] Yao Y, Gehrke J. The cougar approach to in-network query processing in sensor networks. SIGMOD Record, 2002,31(3):9-18
[47] Sadgopan N, Krishnamachari B, Helmy A, The ACQUIRE mechanism for efficient querying in sensor networks, in: proceeding of the 1th IEEE international workshop on sensor network protocols and applications (SNPA’03), 2003:149-155
[48] Heinzelman WR, Chandrakasan A, Balakrishnan H. Energy-efficient communication protocol for wireless microsensor networks. In: Proc. of the Hawaii Int'l Conf. on System Sciences. San Francisco: IEEE Computer Society, 2000. 3005-3014
[49] Lindsey S, Raghavendra CS, PEGASIS: Power efficient gathering in sensor information systems. In: Proc. of the IEEE Aerospace Conf. San Francisco: IEEE Computer Society, 2002, 1-6
[50] Manjeshwar A, Agrawal DP. TEEN: A protocol for enhanced efficiency in wireless sensor networks. In: Int'l Proc. of the 15th Parallel and Distributed Processing Symp. San Francisco: IEEE Computer Society, 2001. 2009-2015
[51] Karp B, Kung H. GPSR: Greedy perimeter stateless routing for wireless networks. In: Proc. of the 6th Annual Int'l Conf. on Mobile Computing and Networking. Boston: ACM Press, 2000, 243-254
[52] Yu Y, Govindan R, Estrin D, Geographical and energy aware routing: A Recursive Data Dissemination Protocol for Wireless Sensor Networks, Technical Report UCLA/CSD-TR-01-0023, University of Southern California, May 2001
[53] Lu C, Blum BM, Abdelzaher TF, Stankovic JA, He T, RAP: A real-time communication architecture for large-scale wireless sensor networks, in: Proceeding of the IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2002), San Jose, CA, September 2002, 55-68.
[54] Niculescu D, Nath B, Trajectory based forwarding and its applications, in: Proceeding of the 9th Annual Int'l Conf. on Mobile Computing and Networking. San Diego: ACM Press, 2003, 260-272.
[55] He T, Stankovic JA, Lu C, Abdelzaher T, SPEED: A stateless protocol for real-time communication in sensor networks, in: Proceeding of the 23rd International Conference on Distributed Computing Systems, 2003, 46 - 55
[56] Sohrabi K, Gao J, Ailawadhi V, Pottie GJ, Protocols for self-organization of a wireless sensor network, IEEE Personal Communications, 2000,7(5l):l6-27
[57] Akkaya K, Younis M, An Energy-aware Qos routing protocol for wireless sensor network , in: Proceeding of ICDCSW’03, 2003:710-719
[58] Savidge L, Huang L, Aghajan H, Goldsmith A, QoS-based geographic routing for event-driven image sensor networks, in: proceeding of the 2nd International Conference on Broadband Networks, 2005, 68-77.
[59] Felemban, E, Lee CG, Ekici E, MMSPEED: Multipath multi-SPEED protocol for QoS guarantee of reliability and timeliness in wireless sensor networks, IEEE Transactions on Mobile Computing, 2006, 5(6): 738 - 754.
[60] Wan CY, Campbell AT, Krishnamurthy L, Pump-slowly, fetch-quickly (PSFQ): a reliable transport protocol for sensor networks, IEEE Journal on Selected Areas in Communications, 2005, 23(4):862-872
[61] Fred Stann, John Heidemann, RMST: Reliable data transport in sensor networks, In Proceedings of the First International Workshop on Sensor Net Protocols and Applications, Anchorage, Alaska, USA, IEEE, 2003, 102-112
[62] Sankarasubramaniam Y, Akan O, Akyildiz I, ESRT: Event-to-Sink reliable transport in wireless sensor networks, IEEE/ACM Trans. On Networking, 2005, 13(5):1003 - 1016
[63] Shane B, Eisenman, Chieh-Yih Wan and Andrew T. Campbell, PSFQ++: critique and suggestions for Source-to-Sink reliable transport, Technical Report CU/EE/TAP-TR-2004-11-002, November 10, 2004:1-6
[64] Karenos, K, Kalogeraki V, Krishnamurthy SV, Cluster-based congestion control for supporting multiple classes of traffic in sensor networks, in: proceeding of The Second IEEE Workshop on Embedded Networked Sensors (EmNetS-II), 2005,107-114
[65] Tan K, Jiang F, Zhang Q, and. Shen X, Congestion control in multi-hop wireless networks, sensor and Ad Hoc communications and networks, IEEE SECON’05. 2th Annual IEEE Communications Society Conference on, 2005, 96-106
[66] Elson J, Girod L, Estrin D. Fine-Grained network time synchronization using reference broadcasts. In: Proc. of the 5th Symp. on Operating Systems Design and Implementation. ACM Press, 2002. 147-163
[67] Ping S, Delay measurement time synchronization for wireless sensor networks, Intel research Berkeley lab, 2003, http: //www.intel_research.net/publications/berkeley/081120031327_137.pdf
[68] Maroti M, Kusy B, Simon G, et al., The flooding time synchronization protocol, Technical Report, Vanderbilt University,2004
[69] He T, Huang CD, Blum BM, Stankovic JA, Abdelzaher T, Range-Free localization schemes in large scale sensor networks. In: Proceeding of the 9th Annual Int'1 Conf. on Mobile Computing and Networking. San Diego: ACM Press, 2003. 81-95
[70] Hightower J, Vakili C, Borriello G, Want R, Design and calibration of the spot on ad-hoc location sensing system, CSE Techniuqe Report, University of Washington, August 2001.
[71] Savvides A, Han C, Strivastava MB, Dynamic fine-grained localization in ad-hoc networks of sensors, in Proc. MobiCom, 2001.
[72] Whitehouse K, The design of calamari: an ad-hoc localization system for sensor networks, Master’s Thesis, University of California at Berkeley, 2002.
[73] Moore D, Leonard J, Rus D, Teller S, Robust distributed network localization with noisy range measurements, in Proc. SenSys, 2004.
[74] B.D. Van Veen and K.M. Buckley, Beamforming: A versatile approach to spatial filtering, IEEE ASSP Mag., 1988, 5(2): 4–24
[75] Stoica P, Moses RL, Introduction to spectral analysis. Englewood Cliffs, NJ: Prentice-Hall, 1997.
[76] Ottersten B, Viberg M, Stoica P, Nehorai A, Exact and large sample ML techniques for parameter estimation and detection in array processing, in Haykin, Litva, and Shepherd, Editors, Radar Array Processing, Springer-Verlag, Berlin, 1993, 99–151.
[77] Priyantha NB, Chakraborty A, Balakrishnan H, The Cricket location-support system, In Mobile Computing and Networking, pp.32–43, 2000.
[78] Patwari N, Hero III AO, Perkins M, et al., Relative location estimation in wireless sensor networks, IEEE Trans. Signal Processing, 2003, 51( 8): 2137–2148
[79] Niculescu D, Nath B, Ad hoc positioning system (APS) using AOA, In: Proceed of IEEE INFOCOM, San Francisco, CA, Mar. 2003.
[80] Biswas P, Ye Y, A distributed method for solving semidefinite programs arising from ad hoc wireless sensor network localization, Dept. of Computer Science, Stanford Univ., Stanford, CA, Tech. Rep., Oct.2003.
[81] Shang Y, Ruml W, Zhang Y, Fromherz MPJ, Localization from mere connectivity, In: Proceed of. The Mobihoc‘03, June 2003, pp. 201–212.
[82] Shang Y, Ruml W, Improved MDS-based localization, in IEEE Proc.Infocom‘04, 2004: 2640–2651.
[83] Bulusu N, Heidemann J, Estrin D, GPS-less low cost outdoor localization for very small devices. IEEE Personal Communication,2000,7(5):28-34
[84] D. Niculescu and B. Nath, Ad hoc positioning system (APS), In: Proceed of the IEEE GlobeCom, San Sntonio, AZ, Nov, 2001
[85] Nagpal R, Organizing a global coordinate system from local information on an amporphous computer. AI Memo 1666, MIT AI Laboratory, August 1999
[86] He T, Huang C, Blum BM, Stankovic JA, Abdelzaher T, Range-free localization schemes for large scale sensor networks. In: Proceed of 9th Annual Int’1 Conf on Mobile Computing and Networking (Mobicom), San Diego, CA., 2003: 81-95
[87] Sichitiu ML, Ramadurai V, Localization of wireless sensor networks with a mobile beacon, Center for Advances Computing Communications, North Carolina State Univ., Tech. Rep.TR-03/06, Jul. 2003.
[88] Sun GL, Guo W, Comparison of distributed localization algorithms for sensor network with a mobile beacon, In: Proceed of IEEE Int. Conf. Networking, Sensing Control (ICNSC), Taipei, Taiwan, R.O.C., Mar. 2004, pp. 536–540.
[89] Galstyan A, Krishnamachari B, Lerman K, et al. Distributed online localization in sensor networks using mobile target, In: Proceed of the international Symposium on information Processing Sensor Networks, Berkeley, CA, 2004:61-70
[90] Priyantha NB, Balakrishnan H, Demaine E, and Teller S, Mobile-assisted localization in wireless sensor networks, In: Proceed of the IEEE Infocom, vol. 1, March 2005, pp. 172– 183.
[91] Kuo-Feng Ssu; Chia-Ho Ou; Jiau, HC, Localization with mobile anchor points in wireless sensor networks, IEEE Transactions on Vehicular Technology, 2005,54(3):1187-1197
[92] Hu L and Evans D, Localization for mobile sensor networks, in: ACM Mobicom’04, Philadelphia, Pennsylvania, September,2004
[93] Zhang L, Cheng Q, Wang Y and Zeadally S, A novel high performance distributed sensor positioning system, online technical report, www.ece.eng.wayne.edu/~qcheng/Landscape.pdf
[94] Gupta R, Das SR, Tracking moving targets in a smart sensor network. The VTC Fall 2003 Symposium,Oct,2003
[95] Mechitov K, Sundresh S, Kwon Y, Agha G, Cooperative tracking with binary-detection sensor networks, In: Proceeding 1st Int. Conf. on Embedded Networked Sensor System(SenSys03), Los Angeles,CA, November 5-7,2003
[96] Zhao F, Shin J, Reich J, Information-Driven dynamic sensor collaboration for tracking applications, IEEE Signal Processing Magazine, 2002, 19(2):61-72
[97] Chu M, Haussecker H, Zhao F, Scalable information-driven sensor querying and routing for ad hoc heterogeneous sensor networks. International Journal on High Performance Computing Applications, 2002,16(3):293-313.
[98] Liu J, Cheung P, Guinbas L, et al., A Dual-Space approach to tracking and sensor management in wireless sensor networks, Proc. 1st ACM Int’1 workshop on wireless sensor network and applications, Atlanta, GA. 2003.131-139
[99] Ramanathan P, Location-centric approach for collaborative target detection, classification, and tracking, IEEE CAS Workshop, 2002.
[100] Brook R, Ramanathan P, Sayeed A, distributed target classification and tracking in sensor networks, Proc. of IEEE, 2003, 91(8):1163-1171
[101] Brooks R, Griffin C, Traffic model evaluation of ad hoc target tracking algorithms, International Journal of High Performance Computing Applications, 2002, 16(3): 221-234
[102] Brooks R, Griffin C, and Friedlander DS, Self-Organized distributed sensor network entity tracking, International Journal of High Performance Computing Applications, 2002,16(3): 207-219
[103] Zhang W, Cao G, DCTC: Dynamic convoy tree-based collaboration for target tracking in sensor networks, IEEE Transactions on Wireless Communications, 2004,3(5):1689-1701
[104] Guo D, Wang X, Dynamic sensor collaboration via sequential Monte Carlo, IEEE Journal on Selected Areas in Communication, 2004, 22(6):1037-1047
[105] Sheng X, Hu Y, Distributed particle filter with GMM approximation for multiple target localization and tracking in wireless sensor network, In: Proceeding of the international symposium of information processing in sensor networks,(Los Angeles, CA), 2005. 181-188
[106] Xiao W, Adaptive sensor scheduling for target tracking in wireless sensor network, Advanced Signal Processing Algorithms, Architectures, and Implementations XV. In Proceedings of the SPIE, 2005, Volume 5910, pp.104-112
[107] Lee J, Cho K, Lee S, et al., Distributed and energy-efficient target localization and tracking in wireless sensor networks, Computer Communications, 2006, 29(2006):2494-2505
[108] Megerian S, Koushanfar F, Qu G, Veltri G,. Potkonjak M, Exposure in wireless sensor networks: theory and practical solutions, Journal of Wireless Networks, 2002, 8(5): 443–454
[109] Meguerdichian S, Koushanfar F, Qu G, Potkonjak M, Exposure in wireless Ad Hoc sensor networks, In: proceeding of International Conference on Mobile Computing and Networking (MobiCom ’01), pp. 139–150, Rome, Italy, July 2001.
[110] Clouqueur T, Phipatanasuphorn V, Ramanathan P, Saluja KK, Sensor deployment strategy for target detection, The First ACM International Workshop on Wireless Sensor Networks and Applications (WSNA’02), Sep. 2002.
[111] Chakrabarty K, Iyengar SS, Qi H, Cho EC, Grid coverage for surveillance and target location in distributed sensor networks, IEEE Transactions on Computers.2002,51(12):1448-1453.
[112] Jung, B, Sukhatme GS, Tracking Targets using Multiple Robots: The effect of environment occlusion, Autonomous Robots, 2002,13(3):191-205
[113] Bejar R, Krishnamachari B, Gomes C, Selman B, Distributed constraint satisfaction in a wireless sensor tracking system, Workshop on Distributed Constraint Reasoning, International Joint Conference on Artificial Intelligence, Seattle, Washington, August 2001.
[114] Li D, Wong K, Hu Y, Sayeed A, Detection, classification, tracking of targets in micro-sensor networks, IEEE Signal Processing Magazine, 2002,19(2):17–29
[115] Fang Q, Zhao F, Guibas L, Counting targets: building and managing aggregates in wireless sensor networks, Palo Alto Research Center Technical Report, pp.2002–10298, June 2002.
[116] 邓小龙,基于粒子滤波的目标跟踪与系统辨识方法的研究, [博士学位论文],上海交通大学,2005
[117] 李安平,复杂环境下的视频目标跟踪算法研究, [博士学位论文],上海交通大学,2006
[118] 张尧庭,贝叶斯统计推断, 科学出版社,1991
[119] Kalman R.E., A new approach to linear filtering and prediction and prediction problems, Trans. ASME, Journal of basic Engineering, 1960,82D(1):35-45
[120] Jazwinski AH, Stochastic processes and filtering theory, New York, Academic Press,1970.
[121] Wan EA, Van Der Merwe R, The unscented Kalman filter for nonlinear estimation, In: proceeding of the Symposium on Adaptive Systems for Signal Processing, Communication and control, 2000, pp:153 - 158.
[122] Julier SJ, The scaled unscented transformation, In: Proceeding of America Control Conference, Anchorage Alaska:IEEE,2002,6:4555-4559
[123] Kitagawa G, Non-Gaussian state-space modeling of non-stationary time series, Journal of computation and graphical statistics, 1987,82(400):1032-1063
[124] Alspach DL, Sorerison HW, Nonlinear Bayesian estimation using Gaussian sum approximation. IEEE Trans. Automatic Control, 1972,17(4):439-448
[125] Rabiner LR, A tutorial on hidden markov models and selected applications in speech recognition, Proceeding of the IEEE, 1989,77(2):257-285
[126] 胡拱涛, 主/被动目标跟踪研究, [博士学位论文] 上海交通大学,2005
[127] Gordon NJ, Salmond DJ, Smith AF, Novel approach to nonlinear/non Gaussian Bayesian state estimation , IEE Proceedings-F (0143-7070), 1993, 140(2):107-113.
[128] Liu JS, Chen R, Sequential Monte Carlo methods for dynamic system, Journal of the American Statistical Association, 1998, 93(443) : 1032-1044
[129] Kitagawa G, Monte carlo filter and smoother for Non-Gaussian nonlinear state space models, Journal of computation and graphical statistics, 1996, 5(1):1-25
[130] Doucet A, On sequential simulation-based methods for Bayesian filtering, Technical Report CUED-F-ENG-TR310,Dept. of. Engineering, University of Cambridge,1998
[131] Crisan D, Doucet A, A survey of convergence results on particle filtering methods for practitioners, IEEE Trans. Signal Processing, 2002, 5(3):738-746
[132] Arulampalam MS, Maskell S, Gordon N, and Clapp T, A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE Trans. on signal Processing, 2002,50(2):174-188
[133] Carlin BP, Polson NG, Stoffer DS, A Monte Carlo approach to non-normal and nonlinear state-space modeling, Journal of the American Statistical Assoc., 1992,87(418):493-500
[134] Andrieu C, Djuric P, Doucet A, Model selection by MCMC computation, Signal processing, 2001, 81(1):19-37,
[135] Gilks W, Berzuini C, Following a moving target-Monte Carlo inference for Bayesian dynamic models, Journal of royal Statistic society B, 2004, 63(1):127-146,
[136] Andrieu C, de Freitas N, Doucet A, et al., An introduction to MCMC for machine learning. Machine Learning (0885-6125), 2003, 50(1/2):5-43
[137] Chen R, Liu JS, Predictive updating methods with application to Bayesian classification, Journal of the Royal Statistical Society B, 1996, 58:397-415
[138] Tanizaki H, Mariano RS, Prediction filtering and smoothing in non-linear and non-normal cases using monte carlo integration, Journal of applied econometrics, 1994, 9(2):163-179
[139] Tanizaki H, Mariano RS, Nonlinear and Non-Gaussian state space modeling with monte carlo simulations. Journal of Econometrics, 1998,83(1&2):263-290
[140] de Freitas JFG, Niranjan M, Gee AH and Doucet A, Sequential monte carlo methods to train neural network models, Neural Computation, 2000,12(4):955-993,
[141] van der Merwe R, de Freitas N, Doucet A and Wan E, The unscented particle filter, Technical Report CUED/F-INFENG-TR380, Cambridge University Engineering Department, 2000
[142] Garrick Ing, Distributed particle filters for object tracking in sensor networks, , McGill University, 2005,1-102
[143] Zhao F, Guibas L, Wireless Sensor Networks: An information processing approach, Boston: Elsevier-Morgan Kaufmann Publishers, 2004
[144] Mao G, Fidan B, Brian DO Anderson, Wireless sensor network localization techniques, Computer Networks,2007, 51(10):2529-2553
[145] Capkun S, Hamdi M, Hubaux J-P., GPS-Free positioning in mobile ad-hoc networks, Cluster Computing,2002,5(2):157-167
[146] Doherty L, Pister KSJ, Ghaoui LE, Convex position estimation in wireless sensor networks, In: Proceeding of the IEEE INFOCOM 2001,Vo1.3, Anchorage: IEEE Computer and Communications Societies,2001. 1655-1663.
[147] Meguerdichian S, Koushanfar F, Potkonjak M, Srivastava MB, Coverage problems in wireless ad-hoc sensor networks, In: Proceeding of the IEEE INFOCOM 2001. Vol.3, Anchorage: IEEE Computer and Communications Societies, 2001, 1380-1387.
[148] Bulusu N, Heidemann J, Estrin D, Adaptive beacon placement, In: Proceedings of 21st IEEE International Conference on Distributed Computing Systems, IEEE Computer Society, Los Angeles, CA, United States ,2001, 489-498.
[149] Hightower J, Boriello G., Location systems for ubiquitous computing, Computer, 2001, 34(8):57-66
[150] Sun G, Chen J,Guo W; Liu, KJR,Signal processing techniques in network-aided positioning: a survey of state-of-the-art positioning designs, IEEE Signal Processing Magazine, 2005,22(4): 12–23.
[151] Sayed AH, Tarighat A, Khajehnouri N, Network-based wireless location: challenges faced in developing techniques for accurate wireless location information, IEEE Signal Processing Magazine, 2005,22(4): 24–40.
[152] Gustafsson F,Gunnarsson F,Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements, IEEE Signal Processing Magazine,2005,22(4): 41–53.
[153] Camp T, Boleng J, Davies V, A survey of mobility models for Ad Hoc networks research, wireless communications and mobile computing, Special issue on Mobile Ad Hoc Networking Research, Trends and Applications, 2002,2(5):483-502
[154] Li D, Hu Y, Energy-based collaborative source localization using acoustic microsensor array, EURASIP Journal on Applied Signal Processing 2003:4,321–337
[155] 王福豹,史龙,任丰原, 无线传感器网络中的自身定位系统和算法, 软件学报,2005, 16(5):857-868
[156] Zhang Y, Ackerson L, Duff D et al, STAM: A System of tracking and mapping in real environments, IEEE Wireless Magazine, 2004, 11(6):87-96
[157] Michalis P Michaelides, Christos G Panayiotou. Plume source position estimation using sensor networks, in: proceedings of the 13th Mediterranean conference on control an automation, Limassol Cyprus 2005:731-736
[158] Michalis P Michaelides, Christos G Panayiotou, Event source position estimation using sensor networks, Control and Automation, MED '06.14th Mediterranean Conference on June 2006:1- 6
[159] Glenn T. Nofsinger, Tracking based plume detection, DARTMOUTH COLLEGE,2006
[160] Farrell J., Pang S, Li W, Plume mapping via hidden markov methods, IEEE Transactions on Systems, Man and Cybernetics-PART B: Cybernetics, 2003, 33(6):850-863
[161] Zarzhitsky D, Spears DF, Spears WM, Distributed robotics approach to chemical plume tracing , Edmonton, Alberta: In: Proceeding of the IEEE/RSJ International Conference on Intelligent Robots and Systems.(IROS’05), 2005:4034-4039
[162] Ishida H, Nakayama G, Nakamoto T, Moriizumi T, Controlling a gas/odor plume-tracking robot based on transient responses of gas sensors, IEEE Sensors Journal, 2005, 5(3):537-545
[163] Adam T. Hayes, Alcherio Martinoli, Distributed odor source localization, IEEE Sensors Journal, 2002, 2(3): 260-271
[164] Kulesz J, Development of a common data highway for comprehensive incident management, Tech. Rep., 2003
[165] Brennan S, Mielke A, Torney D and Maccabe A, Radiation detection with distributed sensor networks, IEEE Computer Magazine, 2004, 37(8): 57–59
[166] Braun JJ, Glina Y, Stein D and Fox E, Multi-sensor information fusion for biological sensor networks and cbrn detection, In: Proceeding of Conf. Science and Technology for Chem-Bio Information Systems, Williamsburg, VA, October 2004.
[167] Braun JJ, Glina Y, Su JK, Urban biodefense oriented aerosol anomaly detection using sensor data fusion, In: Proceeding of 1st Joint Conf. Battle Management for Nuclear, Chemical, Biological and Radiological Defense, November 2002.
[168] Braun JJ, Glina Y, Su JK, Dasey TJ, Computational intelligence in biological sensing, in: Proceedings of SPIE, 5416, 2004
[169] Sheng X, Hu Y, Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks, IEEE Transactions on Signal Processing, 2005, 53(1): 44-53.
[170] 周宏仁,敬忠良,王培德, 机动目标跟踪, 国防工业出版社, 1991,1-366
[171] 陈利斌, 机动目标跟踪理论和算法研究, [博士学位论文],西北工业大学,2003,1-98
[172] Li XR, Jilkov VP, A survey of maneuvering target tracking: dynamic models, in: Proceeding of SPIE Conference on Signal and Data Processing of Small Targets, April, 2000, Vol. 4048, pp. 212-235
[173] Aidala VJ, Kalman filter behavior in bearing-only tracking applications. IEEE Trans. On Aerospace and Electronic systems (0018-9251), 1979, 15(1):29-39
[174] Aidala VJ, Hammel S, Utilization of modified polar coordinates for bearing-only tracking, IEEE Trans. On automatic Control(0018-9286),1983,28(3):283-294
[175] Aidala VJ, Nardone S, Biased estimation properties of the pseudo-linear tracking filter, IEEE Trans. On Aerospace and Electronic systems (0018-9251), 1982, 18(4):432-441
[176] van der Merwe R, Wan E, Sigma-point Kalman Filters for probabilistic inference in dynamic state-space models , PhD thesis, OGI School of Science & Engineering at Oregon Health & Science University Portland, OR, April 2004.
[177] Lee J, Cho K, Lee S, et al., Distributed and energy-efficient target localization and tracking in wireless sensor networks, Computer Communications, 2006, 29(2006):2494-2505
[178] Xu Y, Winter J, Lee W, Prediction-based strategies for energy saving in object tracking sensor networks, In: Proceeding of the 2004 IEEE International Conference on Mobile Data Management (MDM’04), 2004, 346-357
[179] Dunkels A, Voigt J, Alonso T, Ritter H. and Schiller J, Connecting wireless sensornets with TCP/IP networks, In Conference on Wired/Wireless Internet Communications, 2004, LNCS 2957,pp 143–152, 2004
[180] Dunkels A, Full TCP/IP for 8-bit architectures, In: Proceedings of the First International Conference on Mobile Systems, Applications, and Services (MOBISYS ‘03), May 2003
[181] 吕捷, GPRS 技术, 北京邮电大学出版社,2001
[182] 赵锋,王艳玮,范建华等,GPRS 终端拨号上网连接认证注册全过程研究, 计算机工程与应用,2004,40(23):158-160
[183] Perkins D, Requirements for an internet standard Point-to-Point protocol, RFC1547, Carnegie Mellon University, 1993.
[184] Richard Stevens W, TCP/IP 详解, 机械工业出版社,1999
[185] Chipcon AS, Single chip very low RF transceiver with 8051 compatible microcontroller, http://www.chipcon.com/files/CC1010_Data_Sheet_1_3.pdf
[186] 邓 小 龙 , 谢 剑 英 , 基 于 粒 子 滤 波 的 仅 有 角 测 量 的 被 动 跟 踪 , 上 海 交 通 大 学 学报,2005,39(6):993-996