摘 要
近年來，各種自然災害與人為災害頻繁發(fā)作，而復雜的災害現場對救援提出了更高要求。建立消防現場監(jiān)控系統(tǒng)可為消防現場指揮調度和救援提供依據,而對監(jiān)控節(jié)點和消防員的定位則是建立消防現場監(jiān)控系統(tǒng)的一個關鍵問題。隨著無線傳感器網絡（WSN）在眾多場合的成功應用，將便攜式WSN節(jié)點快速部署在消防現場使現場情況的監(jiān)測和對消防員的定位成為可能。而在運用WSN實現定位的過程中，必須結合具體應用特點解決相關關鍵問題。
從消防現場環(huán)境復雜的特點出發(fā)，結合無線通信的傳播特性，構建基于超寬帶技術的消防現場WSN，改進了基于接收信號強度（RSSI）的加權質心定位算法，并對定位結果進行優(yōu)化。主要研究內容如下：
（1）針對室內和野外兩種應用場合，分別建立兩種超寬帶信道衰減模型，分析測距誤差情況；并針對室內測距誤差大的特點，提出采用信標節(jié)點相互定位的方法校正測距誤差，研究結果表明，該方法可有效保證測距精度。
（2）針對加權質心定位算法簡單易行，但定位精度低的問題，在有效提高測距精度的前提下，改進了基于RSSI的加權質心定位算法，并分別采用粒子群算法和量子粒子群算法對定位結果進行優(yōu)化。研究結果表明，采用粒子群算法和量子粒子群算法優(yōu)化后的加權質心定位算法定位精度較高，并且不易受環(huán)境因素的影響，可以有效提高定位精度和穩(wěn)定度。
（3）針對信標節(jié)點需求過多造成的高成本問題，采用遞增式定位過程，在信標節(jié)點數量不足時，將已定位的未知節(jié)點轉化為次級信標節(jié)點參與定位，有效地減少定位中信標節(jié)點的數量，降低成本。仿真結果表明：在粒子群優(yōu)化或量子粒子群優(yōu)化的加權質心定位算法的基礎上，在同等定位率的情況下，定位過程采用遞增式，可有效減少信標節(jié)點數。


關鍵詞 消防現場；超寬帶；無線傳感器網絡；定位；優(yōu)化算法


Abstract
In recent years, various natural and man-made disasters occurred frequently; complex disaster field put forward a higher requirement for rescue. Establish the fire monitoring system provides a basis for fire fighting field command scheduling and rescue, and localization for monitor node and fireman is the key issue to establish the fire monitoring system.
With the rapid development of wireless sensor network (WSN) successfully applied on numerous occasions, the fire monitoring and the localization have become possible because of the portable WSN node rapidly deploying in fire site. However, in the use of WSN to achieve the fireman positioning process must be combined with specific application characteristics to solve relate problems.
In the light of characteristics of the complex fire scene environment and wireless communication propagation characteristics, established the fire site WSN based on UWB technology, improved the weighted cancroids localization algorithm based on the received signal strength (RSSI), and optimized the positioning results. The main research contents are as follows:
(1)According to the different environment of fire happened, considering the fire scene include the indoor and outdoor environment, modeling the fire scene ultra-wideband communication channel model respectively, analyzed the ranging error of UWB channel loss model under various environments. In view of the problem of big ranging and localization error under industrial environment, beacon node mutual positioning and ranging error correction method was proposed, research results shows that this method effectively ensure the distance measurement accuracy.
(2)In view of the problem of weighted cancroids localization algorithm is simple and easy to realize, but have lower accuracy; in the premise of improving the ranging accuracy efficiently, improved the weighted cancroids localization algorithm based on RSSI ranging, the particle swarm algorithm and quantum-behaved particle swarm optimization positioning were applied to optimize the positioning results, research results shows that this method has higher accuracy, And are not easily affected by environmental factors, could improve the localization accuracy and stability.
(3)Incremental positioning process was proposed to overcome the problem of high cost caused by the demanding of more beacon nodes. When there was not enough beacon nodes to localization, the nodes of which were unknown nodes turned into secondary beacon node participated in localization, decreased the beacon nodes number efficiently, and reduced the cost. Simulation results shows that at the basis of the particle swarm and quantum-behaved particle swarm optimization weighted cancroids localization algorithm， at the condition of the same localization rate, incremental method was applied during the positioning could reduce the beacon nodes efficiently.


Key Words The fire scene; ultra-wideband; wireless sensor networks; positioning; optimization algorithm


目 錄
摘 要 I
ABSTRACT III
第1章 緒論 1
1.1背景及意義 1
1.2 國內外定位技術研究現狀 2
1.3 論文研究思路及內容安排 4
第2章 面向消防現場的WSN定位系統(tǒng)整體設計 6
2.1 引言 6
2.2 消防現場的特點 6
2.3 無線傳感器網絡的結構和特點 7
2.4 面向消防現場的WSN定位系統(tǒng)整體設計 8
2.5 面向消防現場定位系統(tǒng)關鍵技術 10
2.5.1 超寬帶技術 10
2.5.2 測距技術 13
2.5.3 定位技術 16
2.6 小結 20
第3章 基于RSSI的加權質心定位算法及..