传感技术学报
傳感技術學報
전감기술학보
Journal of Transduction Technology
2014年
1期
128-134
,共7页
张勇%孟庆浩%吴玉秀%曾明
張勇%孟慶浩%吳玉秀%曾明
장용%맹경호%오옥수%증명
无线传感网络%最小均方差%序贯估计%气泄漏源定位
無線傳感網絡%最小均方差%序貫估計%氣洩漏源定位
무선전감망락%최소균방차%서관고계%기설루원정위
wireless sensor networks%MMSE%sequential estimation%gas leakage source localization
基于无线传感网络的气体泄漏源定位在环境监测、安全防护和污染控制等多个领域具有重要意义。提出一种基于分布式最小均方差( D-MMSE)序贯估计的气体泄漏源定位算法。其通过构建一个包含节点之间信息增益与网络能量消耗两方面参数的信息融合目标函数,并对目标函数寻优实现路由节点的调度与选择。所选节点在其测量值和前节点估计值并通过与邻居节点信息交互的基础上完成气体泄漏源位置参数估计量及其方差的更新与传递。为了降低网络能耗,邻居节点集的选择半径随估计量方差做动态调整。仿真分析表明所提算法对比单节点序贯估计定位算法在一定的能耗条件下可获得较高的定位精度和速度。
基于無線傳感網絡的氣體洩漏源定位在環境鑑測、安全防護和汙染控製等多箇領域具有重要意義。提齣一種基于分佈式最小均方差( D-MMSE)序貫估計的氣體洩漏源定位算法。其通過構建一箇包含節點之間信息增益與網絡能量消耗兩方麵參數的信息融閤目標函數,併對目標函數尋優實現路由節點的調度與選擇。所選節點在其測量值和前節點估計值併通過與鄰居節點信息交互的基礎上完成氣體洩漏源位置參數估計量及其方差的更新與傳遞。為瞭降低網絡能耗,鄰居節點集的選擇半徑隨估計量方差做動態調整。倣真分析錶明所提算法對比單節點序貫估計定位算法在一定的能耗條件下可穫得較高的定位精度和速度。
기우무선전감망락적기체설루원정위재배경감측、안전방호화오염공제등다개영역구유중요의의。제출일충기우분포식최소균방차( D-MMSE)서관고계적기체설루원정위산법。기통과구건일개포함절점지간신식증익여망락능량소모량방면삼수적신식융합목표함수,병대목표함수심우실현로유절점적조도여선택。소선절점재기측량치화전절점고계치병통과여린거절점신식교호적기출상완성기체설루원위치삼수고계량급기방차적경신여전체。위료강저망락능모,린거절점집적선택반경수고계량방차주동태조정。방진분석표명소제산법대비단절점서관고계정위산법재일정적능모조건하가획득교고적정위정도화속도。
Distributed gas source localization with Wireless Sensor Networks has an important significance in the en-vironmental monitoring,security protection and pollution control and other fields. a gas leakage source localization ( GLSL) algorithm based on distributed minimum mean squared error( D-MMSE) sequential estimation is proposed. In the proposed GLSL algorithm, an information fusion objective function which combines the information utility measure and the communication cost between sensor nodes is constructed,and the sensor-node scheduling scheme is designed by optimizing the information fusion objective function;For each selected sensor node,the estimator and the corresponding mean square error are updated with its own observation and the noise corrupted decision from the previous node and transmitted to the next selected node by collaborating information within its neighborhood,and to decrease the energy consumption,the neighborhood radius is adjusted dynamically based on the mean square error. At last,the analysis and simulation results show that the proposed algorithm could be applied to the GLSL with a realtively high accuracy, less time and relatively energy consumption compared to the single node sequential estimation algorithm.