基于无线局域网的定位追踪技术研究
摘要
随着无线网络技术的普及和发展,定位追踪服务受到越来越多的关注,在紧急救助、物理配送、生产管理、旅游导航等领域显示出巨大的活力。实时定位系统(RTLS)国际标准的制定和“物联网”产业的崛起,开拓并推动了定位追踪技术的发展应用。
当前,定位追踪技术主要有视频监控、GPS、RFID等。但是,这些定位技术在应用范围、使用成本和便携性等方面还不能满足普适计算应用的需要,限制了基于位置的服务在用户中的普及。基于无线局域网络和位置指纹的定位技术借助于已有丰富的WLAN资源,能够利用无线路由器实现定位,具有应用范围广,定位系统成本低等优点,成为近年来位置感知领域的一个研究热点。
本文主要就无线局域网定位系统的定位准确度、定位速度、设备能耗和地图管理平台方面等问题开展研究,采用最近邻居权重匹配、区域划分和GIS技术对上述问题提出了相应的解决方案。论文的主要工作和创新点包括：
(1)通过在实际WLAN环境中测得的位置指纹数据,从定位的角度分析了无线信号在室内的传播特性,总结了指纹图数据库制作和实时定位信号强度获取方法。
在基于WLAN和位置指纹的定位技术中,采样点间距、接入点的个数以及环境的干扰是影响定位平均误差的主要因素,但是对于这些参数的选取目前还没有较系统的指导,主要依靠经验来确定。本文分析了各因素与定位误差之间的关系,为设计定位算法、部署定位系统、制作指纹图数据库提供了一定的理论支持。
(2)结合LANDMARC系统中权重参数的思想,对现有RADAR系统的信号空间最近邻居法(NNSS-AVG)进行改进。
由于受室内复杂环境里噪声的干扰,位置指纹数据中常含有不确定性因素,提高定位准确度是当前研究的重点之一。权重改进后的NNSS-AVG方法能够为不同的最近邻居赋予不同的比重,用来描述和区分不同邻居点对定位结果的贡献能力；在选择无线接入点时,本文提出了自适应AP匹配法。
(3)提出了无线WLAN定位的区域划分及判定方法。
定位耗时决定定位系统效率,影响着定位追踪系统的实用性。本文就如何减小定位算法的计算量提出了区域划分的方法。通过区域判定,将位置估计的计算限制在特定区域内,从而大幅较少定位计算量。区域划分及判定方法同时为定位系统向手持设备移植提供了可能性,该方法通过减少计算量可以有效地降低移动设备的能耗。
(4)设计了基于移动台辅助定位技术的主动式WiFi定位标签,并就定位标签的抗干扰、稳定性、能耗等进行了讨论和研究。
(5)开发了以地理信息系统为依托,融合数据库技术的无线定位追踪系统管理平台,提供了基于位置信息的诸多应用功能。这些典型功能包括实时定位及历史路径分析、突发事件在场人员查询、非法越界报警、安全区域防范、救援／拦截最佳路径分析等。
本文研究了无线局域网络环境中基于位置指纹法的定位追踪技术；设计了基于移动台辅助定位技术的主动式WiFi定位标签；开发了定位追踪管理软件平台,并提供了基于位置信息的应用功能。
With the widespread of wireless networks, positioning and tracking services become attractive and show great energy in many applications, such as emergency, logistics distribution, production management and navigation. The international standards of RTLS and the growing up of the Internet of Things have promoted the development and application of positioning and tracking technology.
However, the existing positioning technique cannot fulfill the growing requirements of pervasive computing applications in practical applications, such as low cost and portability, which limits the popularization of location based services (LBS). With the help of the existing resources of WLAN, the positioning technique based on WLAN and location fingerprinting schemes can be implemented by using of wireless routers. Besides, it can work effectively in a wide range with low cost. Thus, positioning technique based on WLAN and location fingerprinting schemes has become a hot research topic in the field of location awareness.in recent years.
Aiming at the problems and requirements in the accuracy, speed, energy consumption and map management of the existing location technique, this thesis proposed the corresponding solutions using the theory of NNSS weight matching, area zoning and GIS. Main works and innovations are as follows:
(1) With the location fingerprints measured in a practical WLAN, the thesis analyzes some characteristics of radio signal propagation in indoor environments from the viewpoint of location, and makes a conclusion of how to construct a database of location fingerprints and how to measure the signal strength.
The factors, such as the space between sample points, the numbers of the access points and the interference of the circumstance, are of great importance to position estimate based on WLAN and location fingerprints. However, until now, there is not a general strategy on how to determine these factors, they are mostly determined by experience. This thesis investigated the relationship between these factors and the location errors, which may be helpful for the location estimation algorithm and system, and the database of location fingerprints.
(2) Based on the position weighing algorithm of LANDMARC system, the NNSS-AVG method in RADAR system is improved in this thesis.
Due to the interference from noises of complex indoor environments, location fingerprints data are always with great uncertainty, thus how to improve the positioning accuracy is one of the important research focuses. In this thesis, NNSS-AVG algorithm is improved. The nearest neighbors are weighted with different values, which represent the different contribution to the positioning results. Besides, an adaptive method of matching the access points is proposed in this thesis.
(3) An area zoning and decision method for WLAN based positioning technique is proposed.
Efficiency and practicality of the location system are strongly related to the time cost in locating computation process. Thus, a low computational cost method, area zoning and decision method is proposed, which limit the computational region in the certain area. Since the energy consumption of mobile devices can be decreased by the reducing computation, the positioning system can to be transplanted to mobile devices.
(4) Based on mobile station assisted positioning technique, active WiFi positioning tags are designed in this thesis, and the noise immunity, stability and energy consumption of the tag are investigated.
(5) Using GIS and database technique, the platform provides users a series of serives based on location, such as real-time positioning, historical pathway replaying, limited region entering, safe region guarding and optimal path analysis for rescue and intercept.
This thesis studys the positioning technique based on WLAN and position fingerprints, designs the active WiFi positioning tag based on mobile station assisted positioning technique, develops a management platform of positioning and tracking system, and provides users a series of serives based on location.
当前,定位追踪技术主要有视频监控、GPS、RFID等。但是,这些定位技术在应用范围、使用成本和便携性等方面还不能满足普适计算应用的需要,限制了基于位置的服务在用户中的普及。基于无线局域网络和位置指纹的定位技术借助于已有丰富的WLAN资源,能够利用无线路由器实现定位,具有应用范围广,定位系统成本低等优点,成为近年来位置感知领域的一个研究热点。
本文主要就无线局域网定位系统的定位准确度、定位速度、设备能耗和地图管理平台方面等问题开展研究,采用最近邻居权重匹配、区域划分和GIS技术对上述问题提出了相应的解决方案。论文的主要工作和创新点包括：
(1)通过在实际WLAN环境中测得的位置指纹数据,从定位的角度分析了无线信号在室内的传播特性,总结了指纹图数据库制作和实时定位信号强度获取方法。
在基于WLAN和位置指纹的定位技术中,采样点间距、接入点的个数以及环境的干扰是影响定位平均误差的主要因素,但是对于这些参数的选取目前还没有较系统的指导,主要依靠经验来确定。本文分析了各因素与定位误差之间的关系,为设计定位算法、部署定位系统、制作指纹图数据库提供了一定的理论支持。
(2)结合LANDMARC系统中权重参数的思想,对现有RADAR系统的信号空间最近邻居法(NNSS-AVG)进行改进。
由于受室内复杂环境里噪声的干扰,位置指纹数据中常含有不确定性因素,提高定位准确度是当前研究的重点之一。权重改进后的NNSS-AVG方法能够为不同的最近邻居赋予不同的比重,用来描述和区分不同邻居点对定位结果的贡献能力；在选择无线接入点时,本文提出了自适应AP匹配法。
(3)提出了无线WLAN定位的区域划分及判定方法。
定位耗时决定定位系统效率,影响着定位追踪系统的实用性。本文就如何减小定位算法的计算量提出了区域划分的方法。通过区域判定,将位置估计的计算限制在特定区域内,从而大幅较少定位计算量。区域划分及判定方法同时为定位系统向手持设备移植提供了可能性,该方法通过减少计算量可以有效地降低移动设备的能耗。
(4)设计了基于移动台辅助定位技术的主动式WiFi定位标签,并就定位标签的抗干扰、稳定性、能耗等进行了讨论和研究。
(5)开发了以地理信息系统为依托,融合数据库技术的无线定位追踪系统管理平台,提供了基于位置信息的诸多应用功能。这些典型功能包括实时定位及历史路径分析、突发事件在场人员查询、非法越界报警、安全区域防范、救援／拦截最佳路径分析等。
本文研究了无线局域网络环境中基于位置指纹法的定位追踪技术；设计了基于移动台辅助定位技术的主动式WiFi定位标签；开发了定位追踪管理软件平台,并提供了基于位置信息的应用功能。
With the widespread of wireless networks, positioning and tracking services become attractive and show great energy in many applications, such as emergency, logistics distribution, production management and navigation. The international standards of RTLS and the growing up of the Internet of Things have promoted the development and application of positioning and tracking technology.
However, the existing positioning technique cannot fulfill the growing requirements of pervasive computing applications in practical applications, such as low cost and portability, which limits the popularization of location based services (LBS). With the help of the existing resources of WLAN, the positioning technique based on WLAN and location fingerprinting schemes can be implemented by using of wireless routers. Besides, it can work effectively in a wide range with low cost. Thus, positioning technique based on WLAN and location fingerprinting schemes has become a hot research topic in the field of location awareness.in recent years.
Aiming at the problems and requirements in the accuracy, speed, energy consumption and map management of the existing location technique, this thesis proposed the corresponding solutions using the theory of NNSS weight matching, area zoning and GIS. Main works and innovations are as follows:
(1) With the location fingerprints measured in a practical WLAN, the thesis analyzes some characteristics of radio signal propagation in indoor environments from the viewpoint of location, and makes a conclusion of how to construct a database of location fingerprints and how to measure the signal strength.
The factors, such as the space between sample points, the numbers of the access points and the interference of the circumstance, are of great importance to position estimate based on WLAN and location fingerprints. However, until now, there is not a general strategy on how to determine these factors, they are mostly determined by experience. This thesis investigated the relationship between these factors and the location errors, which may be helpful for the location estimation algorithm and system, and the database of location fingerprints.
(2) Based on the position weighing algorithm of LANDMARC system, the NNSS-AVG method in RADAR system is improved in this thesis.
Due to the interference from noises of complex indoor environments, location fingerprints data are always with great uncertainty, thus how to improve the positioning accuracy is one of the important research focuses. In this thesis, NNSS-AVG algorithm is improved. The nearest neighbors are weighted with different values, which represent the different contribution to the positioning results. Besides, an adaptive method of matching the access points is proposed in this thesis.
(3) An area zoning and decision method for WLAN based positioning technique is proposed.
Efficiency and practicality of the location system are strongly related to the time cost in locating computation process. Thus, a low computational cost method, area zoning and decision method is proposed, which limit the computational region in the certain area. Since the energy consumption of mobile devices can be decreased by the reducing computation, the positioning system can to be transplanted to mobile devices.
(4) Based on mobile station assisted positioning technique, active WiFi positioning tags are designed in this thesis, and the noise immunity, stability and energy consumption of the tag are investigated.
(5) Using GIS and database technique, the platform provides users a series of serives based on location, such as real-time positioning, historical pathway replaying, limited region entering, safe region guarding and optimal path analysis for rescue and intercept.
This thesis studys the positioning technique based on WLAN and position fingerprints, designs the active WiFi positioning tag based on mobile station assisted positioning technique, develops a management platform of positioning and tracking system, and provides users a series of serives based on location.
引文
[1]宁焕生.RFID重大工程与国家物联网[M].机械工业出版社,2010.
[2]IDTECHEX. Real Time Locating Systems 2006-2016 [N/OL].2009. http://www.idtec
hex.com/research/articles/real time locating systems 2006 2016 00000453.asp.
[3]温家宝.政府工作报告——2010年3月5日在第十一届全国人民代表大会第三次[M].人民出版社,2010.
[4]中国统计年鉴-2009[N/OL].中华人民共和国国家统计局,2009. http://www.stats.gov.c n/tjsj/ndsj/2009/indexch.htm.
[5]高培勇.中国财政政策报告2010/2011：“十二五”时期的中国财税改革[M].中国财政经济出版社.2010.
[6]中华人民共和国2009年国民经济和社会发展统计公报[N/OL].中华人民共和国国家统计局,2010. http://www.stats.gov.cn/tjgb/ndtjgb/qgndtjgb/t20100225_402622945.htm.
[7]慧聪安防网.中国2009年重特大越狱事件盘点[N/OL].2009.http://info.secu.hc360.co m/2009/12/112028202380.shtml.
[8]张彦,宁焕生.RFID与物联网：射频中间件解析与服务[M].电子工业出版社,2008.
[9]University of Helsinki. Ekahau [N/OL]. http://www.ekahau.com/.
[10]ENGE P, MISRA P. Special issue on Global Positioning System [J]. P Ieee,1999,8 7(1):3-15.
[11]刘佳.基于RFID技术的监狱管控系统设计与实现[D].长沙：国防科学技术大学,2008.
[12]曾毅,崔波,汪洋海.伽利略导航试验卫星电子系统设计概述[J].航天器工程,2009,(01)：89-94.
[13]潘巍,常江,张北江. “北斗一号”定位系统介绍及其应用分析[J].数字通信世界,2009,(09)：25-28.
[14]北美E911系统建设和发展初探[N/OL].ZTE中兴,2010. http://www.zte.com.cn/cndat a/magazine/zte_technologies/2010/6_10/magazine/201006/t20100618_186581.html.
[15]ZAGAMI J M, PARL S A, BUSSGANG J J, et al. Providing universal location ser vices using a wireless E911 location network [J]. Ieee Commun Mag,1998,36(4):66-7 1.
[16]SUN G L, GUO W. Robust mobile geo-location algorithm based on LS-SVM [J]. Ie ee T Veh Technol,2005,54(3):1037-1041.
[17]游战清,刘克胜,吴翔等.无线射频识别(RFID)与条码技术[M].机械工业出版社.2007.
[18]NI L, LIU Y, LAU Y, et al. LANDMARC:indoor location sensing using active RFI D [J]. Wireless Networks,2004,10(6):701-710.
[19]刘乃安.无线局域网(WLAN)-原理、技术与应用[M].西安；西安电子科技大学出版社.2004.
[20]无线城市提上两会议程有望提升城市国际竞争力[N/OL].中国信息经济学会,2010.http://www.cies.org.cn/web/news/show.asp?id=123.
[21]BAHL P, PADMANABHAN V. RADAR:An in-building RF-based user location and tracking system, F,2002 [C]. Ieee.
[22]XIANG Z, SONG S, CHEN J, et al. A wireless LAN-based indoor positioning tech nology [J]. IBM Journal of Research and Development,2010,48(5.6):617-626.
[23]YOUSSEF M, AGRAWALA A. Handling samples correlation in the horus system, F, 2004 [C]. IEEE.
[24]YOUSSEF M, AGRAWALA A. Continuous space estimation for WLAN location det ermination systems, F,2005 [C]. IEEE.
[25]董梅,杨曾,张健,et al.基于信号强度的无线局域网定位技术[J].计算机应用,2004,(12)：49-52.
[26]张明华.基于WLAN的室内定位技术研究[D].上海：上海交通大学,2009.
[27]CHEN Y Q, YANG Q, YIN J, et al. Power-efficient access-point selection for indoo r location estimation [J]. Ieee T Knowl Data En,2006,18(7):877-888.
[28]YIN J, YANG Q, NI L. Adaptive temporal radio maps for indoor location estimatio n [J]. Third IEEE International Conference on Pervasive Computing and Communication s, Proceedings,2005,85-94.
[29]ROBINSON N, PSAROMILIGKOS I. Received signal strength based location estima tion of a wireless LAN client [J]. Ieee Wcnc,2005,2350-2354.
[30]KOTANEN A, HANNIKAINEN M, LEPPAKOSKI H, et al. Positioning with IEEE 802.11b wireless LAN [J]. Pimrc 2003:14th Ieee 2003 International Symposium on Pers onal, Indoor and Mobile Radio Communications Proceedings, Vols 1-3 2003,2003,2218-2222.
[31]COTRONEO D, RUSSO S, CORNEVILLI F, et al. Implementing positioning service s over an ubiquitous infrastructure [J]. Second Ieee Workshop on Software Technologies for Future Embedded and Ubiquitous Systems, Proceedings,2004,14-18.
[32]LEE D, CHEN Q. A model-based wifi localization method, F,2007 [C]. ICST (Insti tute for Computer Sciences, Social-Informatics and Telecommunications Engineering).
[33]KOBBEN B, VAN BUNNINGEN A, MUTHUKRISHNAN K. Wireless Campus LBS: Building Campus-Wide Location Based Services Based on WiFi Technology [J]. Lec N ot Geo Carto,2006,399-408.
[34]GARTNER. Gartner's 2006 Emerging Technologies Hype Cycle Highlights Key Tech nology Themes [N/OL].2006. http://www.gartner.com/it/page.jsp?id=495475.
[35]刘庆.基于主动式RFID的监狱管理系统设计与研究[D].济南：山东大学,2009.
[36]ZHAO F, YA W B, LOGOTHETIS C C, et al. Comparison of super-resolution algor ithms for TOA estimation in indoor IEEE 802.11 wireless LANs [J]. I C Wirel Comm Netw,2006,1365-1368.
[37]SAYRAFIAN-POUR K, KASPAR D. Indoor positioning using spatial power spectru m, F,2006 [C]. IEEE.
[38]NICULESCU D, NATH B. VOR base stations for indoor 802.11 positioning, F,200 4 [C]. ACM.
[39]ORR R, ABOWD G. The smart floor:A mechanism for natural user identification a nd tracking, F,2000 [C]. ACM.
[40]CASTRO P, CHIU P, KREMENEK T, et al. A probabilistic room location service fo r wireless networked environments, F,2001 [C]. Springer.
[41]GWON Y, JAIN R, KAWAHARA T. Robust indoor location estimation of stationary and mobile users [J]. Ieee Infocom Ser,2004,1032-1043.
[42]PAHLAVAN K, KRISHNAMURTHY P. Principles of wireless networks [M]. Prentice Hall PTR New Jersey,2001.
[43]何皎.基于无线局域网的精确室内定位系统软件平台开发[D].武汉：华中师范大学2009.
[44]李剑,赵东风,余江,et al.宽带无线系统楼内传播特性[J].云南大学学报(自然科学版),2002,(03)：186-191.
[45]KAEMARUNGSI K, KRISHNAMURTHY P. Properties of indoor received signal stre ngth for WLAN location fingerprinting, F,2004 [C]. IEEE.
[46]LADD A M, BEKRIS K E, RUDYS A, et al. Robotics-based location sensing using wireless Ethernet [J]. Wireless Networks,2005,11(1-2):189-204.
[47]KUSHKI A, PLATANIOTIS K N, VENETSANOPOULOS A N. Kernel-based positio ning in Wireless Local Area Networks [J]. Ieee T Mobile Comput,2007,6(6):689-705.
[48]YOUSSEF M A, AGRAWALA A, SHANKAR A U. WLAN location determination via clustering and probability distributions [J]. Proceedings of the First Ieee International Conference on Pervasive Computing and Communications (Percom 2003),2003,143-15 0.
[49]PRASITHSANGAREE P, KRISHNAMURTHY P, CHRYSANTHIS P K. On indoor p osition location with wireless LANS [J].13th Ieee International Symposium on Personal, Indoor and Mobile Radio Communications, Vol 1-5, Proceedings,2002,720-724.
[50]ROOS T, MYLLYM KI P, TIRRI H, et al. A probabilistic approach to WLAN user location estimation [J]. International Journal of Wireless Information Networks,2002,9 (3):155-164.
[51]徐凤燕,李樑宾,王宗欣.一种新的基于区域划分的距离-损耗模型室内WLAN定位系统[J].电子与信息学报,2008,(06)：1405-1408.
[52]杨章林.基于RSSI的WLAN定位系统研究与实现[D].大连：大连理工大学,2009.
[53]王永虹,徐炜,郝立平.STM32系列ARM Cortex-M3微控制器原理与实践[M].北京；北京航空航天大学出版社.2008.
[54]LANTRONIX. MatchPort(?) b/g嵌入式无线设备服务器[N/OL]. http://www.lantronix.c n/device-networking/embedded-device-servers/matchport.html.
[55]马宁,陈莉.射频电路板抗干扰设计[J].现代雷达,2005,(09)：75-77.
[56]邬伦,张晶,赵伟.地理信息系统[M].北京；电子工业出版社.2002.
[57]向丰.GIS及矢量化技术在城市交通规划中的研究与应用[D].杭州：浙江大学,2010.
[58]张正栋,胡华科,钟广锐.SuperMap GIS应用与开发教程[M].武汉；武汉大学出版社.2006.
[59]刘启滨.组件技术及其分析比较[N/OL].2004. http://blog.csdn.net/javaid/archive/2004/ 11/30/198721.aspx.
[60]知名GIS软件平台的比较[N/OL].2009. http://www.docin.com/p-11597596.html.
[61]肖乐斌,钟耳顺,刘纪远,et al.面向对象整体GIS数据模型的设计与实现[J].地理研究,2002,(01)：34-44.
[62]刘守根.数据库管理系统的现状和发展方向初探[J].内江科技,2006,27(2)：
[63]姜桂洪.SQL Server 2005数据库应用与开发[M].北京；清华大学出版社.2010.
[2]IDTECHEX. Real Time Locating Systems 2006-2016 [N/OL].2009. http://www.idtec
hex.com/research/articles/real time locating systems 2006 2016 00000453.asp.
[3]温家宝.政府工作报告——2010年3月5日在第十一届全国人民代表大会第三次[M].人民出版社,2010.
[4]中国统计年鉴-2009[N/OL].中华人民共和国国家统计局,2009. http://www.stats.gov.c n/tjsj/ndsj/2009/indexch.htm.
[5]高培勇.中国财政政策报告2010/2011：“十二五”时期的中国财税改革[M].中国财政经济出版社.2010.
[6]中华人民共和国2009年国民经济和社会发展统计公报[N/OL].中华人民共和国国家统计局,2010. http://www.stats.gov.cn/tjgb/ndtjgb/qgndtjgb/t20100225_402622945.htm.
[7]慧聪安防网.中国2009年重特大越狱事件盘点[N/OL].2009.http://info.secu.hc360.co m/2009/12/112028202380.shtml.
[8]张彦,宁焕生.RFID与物联网：射频中间件解析与服务[M].电子工业出版社,2008.
[9]University of Helsinki. Ekahau [N/OL]. http://www.ekahau.com/.
[10]ENGE P, MISRA P. Special issue on Global Positioning System [J]. P Ieee,1999,8 7(1):3-15.
[11]刘佳.基于RFID技术的监狱管控系统设计与实现[D].长沙：国防科学技术大学,2008.
[12]曾毅,崔波,汪洋海.伽利略导航试验卫星电子系统设计概述[J].航天器工程,2009,(01)：89-94.
[13]潘巍,常江,张北江. “北斗一号”定位系统介绍及其应用分析[J].数字通信世界,2009,(09)：25-28.
[14]北美E911系统建设和发展初探[N/OL].ZTE中兴,2010. http://www.zte.com.cn/cndat a/magazine/zte_technologies/2010/6_10/magazine/201006/t20100618_186581.html.
[15]ZAGAMI J M, PARL S A, BUSSGANG J J, et al. Providing universal location ser vices using a wireless E911 location network [J]. Ieee Commun Mag,1998,36(4):66-7 1.
[16]SUN G L, GUO W. Robust mobile geo-location algorithm based on LS-SVM [J]. Ie ee T Veh Technol,2005,54(3):1037-1041.
[17]游战清,刘克胜,吴翔等.无线射频识别(RFID)与条码技术[M].机械工业出版社.2007.
[18]NI L, LIU Y, LAU Y, et al. LANDMARC:indoor location sensing using active RFI D [J]. Wireless Networks,2004,10(6):701-710.
[19]刘乃安.无线局域网(WLAN)-原理、技术与应用[M].西安；西安电子科技大学出版社.2004.
[20]无线城市提上两会议程有望提升城市国际竞争力[N/OL].中国信息经济学会,2010.http://www.cies.org.cn/web/news/show.asp?id=123.
[21]BAHL P, PADMANABHAN V. RADAR:An in-building RF-based user location and tracking system, F,2002 [C]. Ieee.
[22]XIANG Z, SONG S, CHEN J, et al. A wireless LAN-based indoor positioning tech nology [J]. IBM Journal of Research and Development,2010,48(5.6):617-626.
[23]YOUSSEF M, AGRAWALA A. Handling samples correlation in the horus system, F, 2004 [C]. IEEE.
[24]YOUSSEF M, AGRAWALA A. Continuous space estimation for WLAN location det ermination systems, F,2005 [C]. IEEE.
[25]董梅,杨曾,张健,et al.基于信号强度的无线局域网定位技术[J].计算机应用,2004,(12)：49-52.
[26]张明华.基于WLAN的室内定位技术研究[D].上海：上海交通大学,2009.
[27]CHEN Y Q, YANG Q, YIN J, et al. Power-efficient access-point selection for indoo r location estimation [J]. Ieee T Knowl Data En,2006,18(7):877-888.
[28]YIN J, YANG Q, NI L. Adaptive temporal radio maps for indoor location estimatio n [J]. Third IEEE International Conference on Pervasive Computing and Communication s, Proceedings,2005,85-94.
[29]ROBINSON N, PSAROMILIGKOS I. Received signal strength based location estima tion of a wireless LAN client [J]. Ieee Wcnc,2005,2350-2354.
[30]KOTANEN A, HANNIKAINEN M, LEPPAKOSKI H, et al. Positioning with IEEE 802.11b wireless LAN [J]. Pimrc 2003:14th Ieee 2003 International Symposium on Pers onal, Indoor and Mobile Radio Communications Proceedings, Vols 1-3 2003,2003,2218-2222.
[31]COTRONEO D, RUSSO S, CORNEVILLI F, et al. Implementing positioning service s over an ubiquitous infrastructure [J]. Second Ieee Workshop on Software Technologies for Future Embedded and Ubiquitous Systems, Proceedings,2004,14-18.
[32]LEE D, CHEN Q. A model-based wifi localization method, F,2007 [C]. ICST (Insti tute for Computer Sciences, Social-Informatics and Telecommunications Engineering).
[33]KOBBEN B, VAN BUNNINGEN A, MUTHUKRISHNAN K. Wireless Campus LBS: Building Campus-Wide Location Based Services Based on WiFi Technology [J]. Lec N ot Geo Carto,2006,399-408.
[34]GARTNER. Gartner's 2006 Emerging Technologies Hype Cycle Highlights Key Tech nology Themes [N/OL].2006. http://www.gartner.com/it/page.jsp?id=495475.
[35]刘庆.基于主动式RFID的监狱管理系统设计与研究[D].济南：山东大学,2009.
[36]ZHAO F, YA W B, LOGOTHETIS C C, et al. Comparison of super-resolution algor ithms for TOA estimation in indoor IEEE 802.11 wireless LANs [J]. I C Wirel Comm Netw,2006,1365-1368.
[37]SAYRAFIAN-POUR K, KASPAR D. Indoor positioning using spatial power spectru m, F,2006 [C]. IEEE.
[38]NICULESCU D, NATH B. VOR base stations for indoor 802.11 positioning, F,200 4 [C]. ACM.
[39]ORR R, ABOWD G. The smart floor:A mechanism for natural user identification a nd tracking, F,2000 [C]. ACM.
[40]CASTRO P, CHIU P, KREMENEK T, et al. A probabilistic room location service fo r wireless networked environments, F,2001 [C]. Springer.
[41]GWON Y, JAIN R, KAWAHARA T. Robust indoor location estimation of stationary and mobile users [J]. Ieee Infocom Ser,2004,1032-1043.
[42]PAHLAVAN K, KRISHNAMURTHY P. Principles of wireless networks [M]. Prentice Hall PTR New Jersey,2001.
[43]何皎.基于无线局域网的精确室内定位系统软件平台开发[D].武汉：华中师范大学2009.
[44]李剑,赵东风,余江,et al.宽带无线系统楼内传播特性[J].云南大学学报(自然科学版),2002,(03)：186-191.
[45]KAEMARUNGSI K, KRISHNAMURTHY P. Properties of indoor received signal stre ngth for WLAN location fingerprinting, F,2004 [C]. IEEE.
[46]LADD A M, BEKRIS K E, RUDYS A, et al. Robotics-based location sensing using wireless Ethernet [J]. Wireless Networks,2005,11(1-2):189-204.
[47]KUSHKI A, PLATANIOTIS K N, VENETSANOPOULOS A N. Kernel-based positio ning in Wireless Local Area Networks [J]. Ieee T Mobile Comput,2007,6(6):689-705.
[48]YOUSSEF M A, AGRAWALA A, SHANKAR A U. WLAN location determination via clustering and probability distributions [J]. Proceedings of the First Ieee International Conference on Pervasive Computing and Communications (Percom 2003),2003,143-15 0.
[49]PRASITHSANGAREE P, KRISHNAMURTHY P, CHRYSANTHIS P K. On indoor p osition location with wireless LANS [J].13th Ieee International Symposium on Personal, Indoor and Mobile Radio Communications, Vol 1-5, Proceedings,2002,720-724.
[50]ROOS T, MYLLYM KI P, TIRRI H, et al. A probabilistic approach to WLAN user location estimation [J]. International Journal of Wireless Information Networks,2002,9 (3):155-164.
[51]徐凤燕,李樑宾,王宗欣.一种新的基于区域划分的距离-损耗模型室内WLAN定位系统[J].电子与信息学报,2008,(06)：1405-1408.
[52]杨章林.基于RSSI的WLAN定位系统研究与实现[D].大连：大连理工大学,2009.
[53]王永虹,徐炜,郝立平.STM32系列ARM Cortex-M3微控制器原理与实践[M].北京；北京航空航天大学出版社.2008.
[54]LANTRONIX. MatchPort(?) b/g嵌入式无线设备服务器[N/OL]. http://www.lantronix.c n/device-networking/embedded-device-servers/matchport.html.
[55]马宁,陈莉.射频电路板抗干扰设计[J].现代雷达,2005,(09)：75-77.
[56]邬伦,张晶,赵伟.地理信息系统[M].北京；电子工业出版社.2002.
[57]向丰.GIS及矢量化技术在城市交通规划中的研究与应用[D].杭州：浙江大学,2010.
[58]张正栋,胡华科,钟广锐.SuperMap GIS应用与开发教程[M].武汉；武汉大学出版社.2006.
[59]刘启滨.组件技术及其分析比较[N/OL].2004. http://blog.csdn.net/javaid/archive/2004/ 11/30/198721.aspx.
[60]知名GIS软件平台的比较[N/OL].2009. http://www.docin.com/p-11597596.html.
[61]肖乐斌,钟耳顺,刘纪远,et al.面向对象整体GIS数据模型的设计与实现[J].地理研究,2002,(01)：34-44.
[62]刘守根.数据库管理系统的现状和发展方向初探[J].内江科技,2006,27(2)：
[63]姜桂洪.SQL Server 2005数据库应用与开发[M].北京；清华大学出版社.2010.