【摘要】：礦井下對(duì)人員的定位在礦井的安全生產(chǎn)中是極其核心的一部分。無(wú)線傳感器網(wǎng)絡(luò)技術(shù)近些年來(lái)作為一類新興的對(duì)信息感知、處理和交互技術(shù),將會(huì)為井下安監(jiān)系統(tǒng)帶來(lái)飛速的發(fā)展和進(jìn)步。井下安監(jiān)系統(tǒng)最核心的問(wèn)題是井下節(jié)點(diǎn)的定位問(wèn)題,沒(méi)有定位技術(shù)井下安全系統(tǒng)的信息采集就失去了其根本的價(jià)值。節(jié)點(diǎn)定位技術(shù)在無(wú)線傳感器網(wǎng)絡(luò)中占據(jù)著最基礎(chǔ),最核心的部分。在礦井下的特殊環(huán)境中,傳統(tǒng)的GPS定位方法因?yàn)樾枰邮招l(wèi)星信號(hào)而無(wú)法滿足在井下環(huán)境中的定位監(jiān)測(cè)。目前,井下的定位系統(tǒng)主要采用射頻識(shí)別的方式,即在人靠近射頻節(jié)點(diǎn)時(shí)才能被檢測(cè)到,進(jìn)而得到定位信息,但是射頻識(shí)別的定位方式只是一種被動(dòng)的監(jiān)測(cè)方式,無(wú)法實(shí)現(xiàn)對(duì)井下人員的實(shí)時(shí)定位反饋,針對(duì)現(xiàn)在井下安監(jiān)系統(tǒng)不能實(shí)時(shí)定位、定位精度差、性能不穩(wěn)定的問(wèn)題,結(jié)合無(wú)線傳感器網(wǎng)絡(luò)知識(shí)和井下環(huán)境中無(wú)線傳感器網(wǎng)絡(luò)的定位現(xiàn)狀,提出了兩種新型井下無(wú)線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位方法,并且對(duì)兩種方法進(jìn)行仿真驗(yàn)證。本文在基于RSSI的多邊定位算法的基礎(chǔ)上,利用錨節(jié)點(diǎn)之間的相互關(guān)系獲取比例差分系數(shù),將這個(gè)系數(shù)應(yīng)用在通過(guò)RSSI方法測(cè)量得到的節(jié)點(diǎn)之間的距離上。RSSI測(cè)量方法在不同環(huán)境下的測(cè)量需要不同的傳播模型,且RSSI測(cè)距方法由于自身的限制條件,即RSSI對(duì)距離近的目標(biāo)測(cè)距精度要遠(yuǎn)遠(yuǎn)好于距離遠(yuǎn)的目標(biāo)。目標(biāo)未知節(jié)點(diǎn)首先讀取在通信范圍內(nèi)的信標(biāo)節(jié)點(diǎn)廣播的信息,得到RSSI強(qiáng)度值,通過(guò)卡爾曼濾波的方法對(duì)RSSI信號(hào)除去信號(hào)中的噪聲,除去噪聲的接收信號(hào)強(qiáng)度值可以獲得更加精確的距離值,繼而利用最靠近目標(biāo)節(jié)點(diǎn)的錨節(jié)點(diǎn)和其余錨節(jié)點(diǎn)構(gòu)建差分模型,獲取系統(tǒng)差分誤差,在對(duì)目標(biāo)節(jié)點(diǎn)測(cè)距時(shí)去掉系統(tǒng)差分誤差,得到更加精確的距離值;然后利用比例差分的方法繼續(xù)修正RSSI測(cè)距,經(jīng)過(guò)仿真實(shí)驗(yàn),得到定位效果明顯好于傳統(tǒng)RSSI定位算法精度。針對(duì)原始的加權(quán)質(zhì)心定位不夠精確,使用了改進(jìn)的加權(quán)質(zhì)心的方法對(duì)井下巷道內(nèi)的節(jié)點(diǎn)進(jìn)行定位。分析了在巷道環(huán)境下節(jié)點(diǎn)分布時(shí)存在的問(wèn)題,提出解決方案。在此基礎(chǔ)上,進(jìn)一步采取比例差分的方法對(duì)獲取到的距離修正,進(jìn)一步優(yōu)化加權(quán)系數(shù),使節(jié)點(diǎn)的定位精度更加逼近真實(shí)效果。
[Abstract]:The positioning of personnel under the mine is an extremely important part of the safety production of the mine. Wireless sensor network (WSN) technology, as a new technology of information perception, processing and interaction, will bring rapid development and progress for underground safety monitoring system in recent years. The core problem of downhole safety monitoring system is the location of underground nodes. Without positioning technology, the information collection of downhole safety system will lose its fundamental value. Node location technology occupies the most basic and core part in wireless sensor networks. In the special environment under the mine, the traditional GPS positioning method can not meet the need to receive satellite signals and can not meet the location monitoring in the underground environment. At present, the downhole positioning system mainly adopts the method of radio frequency identification, that is, it can only be detected when people are near the radio frequency node, and then the location information can be obtained. However, the location mode of radio frequency identification is only a passive monitoring method. Can not realize the real-time positioning feedback to the downhole personnel, aiming at the problem that the downhole safety monitoring system can not locate in real time, the positioning accuracy is poor, the performance is unstable, Combined with the knowledge of wireless sensor network and the status quo of wireless sensor network location in underground environment, two new underground wireless sensor network node localization methods are proposed, and the two methods are simulated and verified. In this paper, based on the multilateral localization algorithm based on RSSI, the proportional difference coefficient is obtained by using the relationship between anchor nodes. This coefficient is applied to the distance between nodes measured by RSSI method. The measurement of RSSI in different environments requires different propagation models, and the RSSI ranging method is limited by its own conditions. That is, the ranging accuracy of RSSI is much better than that of long range target. The target unknown node first reads the information broadcast by the beacon node in the communication range, obtains the RSSI intensity value, and removes the noise from the RSSI signal by Kalman filter. The received signal intensity value without noise can obtain more accurate distance value, and then use the anchor node closest to the target node and the other anchor nodes to construct a differential model to obtain the differential error of the system. The system difference error is removed and the range value is more accurate. Then the method of proportional difference is used to continue to modify the RSSI ranging. The simulation results show that the accuracy of the localization algorithm is better than that of the traditional RSSI localization algorithm. Because the original weighted centroid location is not accurate, the improved weighted centroid method is used to locate the nodes in the underground roadway. The problems of node distribution in roadway environment are analyzed, and the solutions are put forward. On this basis, the method of proportional difference is adopted to correct the distance obtained, and the weighting coefficient is further optimized, so that the positioning accuracy of the node is closer to the real effect.
【學(xué)位授予單位】：江西理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN929.5;TP212.9

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 姚維強(qiáng);張金藝;鮑深;梁濱;;iBeacon網(wǎng)絡(luò)下的區(qū)域化雙層定位體系[J];應(yīng)用科學(xué)學(xué)報(bào);2017年01期

2 王千;金光;鈕俊;;一種基于RSSI的混合定位算法[J];傳感技術(shù)學(xué)報(bào);2015年12期

3 于泉;徐保國(guó);;一種基于RSSI的三角形質(zhì)心改進(jìn)算法[J];電子設(shè)計(jì)工程;2015年03期

4 胡偉;朱西平;文紅;曾曉麗;;基于四面體質(zhì)心迭代的三維APIT定位算法研究[J];傳感技術(shù)學(xué)報(bào);2013年10期

5 李慧浩;許寶杰;左云波;吳國(guó)新;;基于小波變換和EMD方法提取趨勢(shì)項(xiàng)對(duì)比研究[J];儀器儀表與分析監(jiān)測(cè);2013年03期

6 謝波;江一夫;嚴(yán)恭敏;任宏科;;個(gè)人導(dǎo)航融合建筑平面信息的粒子濾波方法[J];中國(guó)慣性技術(shù)學(xué)報(bào);2013年01期

7 肖麗萍;劉曉紅;;一種基于跳數(shù)修正的DV-Hop定位算法[J];傳感技術(shù)學(xué)報(bào);2012年12期

8 劉凱;余君君;譚立雄;;跳數(shù)加權(quán)DV-Hop定位算法[J];傳感技術(shù)學(xué)報(bào);2012年11期

9 王長(zhǎng)征;湯文亮;徐燕;;無(wú)線傳感器網(wǎng)絡(luò)中四面體三維質(zhì)心定位算法[J];傳感器與微系統(tǒng);2012年08期

10 吳俊;張榆鋒;;經(jīng)驗(yàn)?zāi)B(tài)分解和小波分解濾波特性的比較研究[J];云南大學(xué)學(xué)報(bào)(自然科學(xué)版);2012年03期

相關(guān)碩士學(xué)位論文 前1條

1 劉捚;基于卡爾曼濾波的WSNs定位系統(tǒng)研究與設(shè)計(jì)[D];華中師范大學(xué);2014年

，

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