基于無線傳感器網(wǎng)絡(luò)的高速移動節(jié)點(diǎn)定位研究
發(fā)布時(shí)間：2019-04-26 03:55
【摘要】：無線傳感器網(wǎng)絡(luò)(Wireless Sensor Network,WSN)綜合了嵌入式計(jì)算技術(shù)、傳感器技術(shù)、無線通信、微機(jī)電系統(tǒng)等學(xué)科領(lǐng)域,是21世紀(jì)以來迅速發(fā)展起來的一種新型網(wǎng)絡(luò)。WSN在監(jiān)測區(qū)域內(nèi)部署大量傳感器節(jié)點(diǎn),先通過傳感器協(xié)作地實(shí)時(shí)監(jiān)測、感知和采集目標(biāo)信息;然后將采集到的數(shù)據(jù)以無線通信技術(shù)方式傳遞;最后通過傳感器間的多跳、自組織方式傳送到用戶終端。近年來,隨著對無線傳感器的研究以及不斷完善WSN的網(wǎng)絡(luò)協(xié)議,WSN已具有低功耗、低成本、分布式和自組織等優(yōu)點(diǎn),使其被廣泛應(yīng)用于軍事系統(tǒng)、國家安全、環(huán)境監(jiān)測、目標(biāo)跟蹤、智能家居、醫(yī)療保健和空間探索等領(lǐng)域。定位技術(shù)作為WSN中的關(guān)鍵技術(shù)之一,也是目前研究的熱點(diǎn)。目前,WSN節(jié)點(diǎn)定位主要應(yīng)用于靜止?fàn)顟B(tài)下的目標(biāo)定位,而對移動WSN定位研究比較少。如果在靜態(tài)的WSN中部署若干個(gè)具有高速移動能力的節(jié)點(diǎn),那么既增加了WSN定位的應(yīng)用范圍和應(yīng)變能力,也滿足了當(dāng)今時(shí)代人們對位置信息的需求。因此,無論是在普通環(huán)境中的移動節(jié)點(diǎn)定位還是在高速環(huán)境中的節(jié)點(diǎn)定位都具有重要的理論意義和應(yīng)用價(jià)值。本文對目前已有的移動WSN節(jié)點(diǎn)定位算法進(jìn)行深入研究,并分析算法中存在的問題。針對定位區(qū)域的范圍、定位精度和能耗等問題,結(jié)合各類移動定位算法具有的特點(diǎn),提出一種在高速環(huán)境下的移動節(jié)點(diǎn)定位算法,利用不會變化的采樣范圍和航位推算算法具有短時(shí)間內(nèi)定位精度高和獨(dú)立性強(qiáng)的特點(diǎn),進(jìn)而得到精確的定位信息。本論文的主要研究成果如下:(1)針對蒙特卡羅定位算法采樣范圍過大這一現(xiàn)象,將線性部署與基于正三角形的節(jié)點(diǎn)部署結(jié)合,提出一種新的算法模型。利用錨節(jié)點(diǎn)感知范圍可以重疊的特點(diǎn),得到一個(gè)精確的重疊區(qū)域,并用其取代了傳統(tǒng)蒙特卡羅定位算法以速度為半徑確定的采樣范圍。(2)針對蒙特卡羅定位算法中粒子退化問題導(dǎo)致的重采樣以及航位推算算法誤差積累的問題,本文提出來一種改進(jìn)航位推算算法,將重疊區(qū)域內(nèi)采集到的錨節(jié)點(diǎn)信息作為修正定位誤差的參照點(diǎn)。在離散的時(shí)間段內(nèi),利用參照點(diǎn)修正定位誤差,并且利用定位誤差描繪出未知節(jié)點(diǎn)的運(yùn)動軌跡。(3)考慮到線性部署單點(diǎn)失效問題以及高速環(huán)境下移動未知節(jié)點(diǎn)的定位精度,本文引入數(shù)據(jù)回傳技術(shù)與異常數(shù)據(jù)剔除技術(shù),并在算法模型中虛擬地構(gòu)建一個(gè)數(shù)據(jù)處理中心。高速移動未知節(jié)點(diǎn)將采集到的信息直接回傳到數(shù)據(jù)處理中心,解決了線性部署中數(shù)據(jù)單向傳遞問題。經(jīng)過修正因子與閾值對比,剔除大于閾值的誤差值,進(jìn)而得到更精確的定位。(4)對基于WSN的高速移動節(jié)點(diǎn)定位算法所提出的解決方案進(jìn)行仿真,并采用勻速運(yùn)動、勻加速運(yùn)動和勻減速運(yùn)動以三組不同的速度、加速度、參照點(diǎn)數(shù)進(jìn)行比較分析。最后,對比分析了在一維空間與二維空間下算法定位誤差,仿真結(jié)果表明在一維空間下的定位誤差要小于在二維空間中的定位,同樣說明了該算法同樣適用于在一維空間下對高速移動節(jié)點(diǎn)的定位。
[Abstract]:Wireless Sensor Network (WSN) integrated the field of embedded computing technology, sensor technology, wireless communication and micro-electro-mechanical system. It is a new kind of network that has developed rapidly since the 21st century. The WSN deploys a large number of sensor nodes in the monitoring area, monitors, senses and collects the target information in real time through the sensors, and then transmits the acquired data in a wireless communication technology mode; and finally, through the multi-hop among the sensors, the self-organizing mode is transmitted to the user terminal. In recent years, with the research of the wireless sensor and the continuous improvement of the network protocol of the WSN, the WSN has the advantages of low power consumption, low cost, distributed and self-organization and the like, and is widely applied to the military system, the national security, the environment monitoring, the target tracking and the intelligent home, Healthcare and space exploration. As one of the key technologies in the WSN, the location technology is also the hot spot of the research. At present, the location of the WSN node is mainly applied to the target location in the stationary state, and the positioning of the mobile WSN is less. If a number of nodes with high-speed movement capability are deployed in the static WSN, the application range and the adaptability of the WSN positioning are increased, and the requirements of people on the position information in the current era are also met. Therefore, both the positioning of the mobile node in the normal environment or the positioning of the nodes in the high-speed environment have important theoretical and application values. In this paper, the existing mobile WSN node positioning algorithm is deeply studied and the problems existing in the algorithm are analyzed. Aiming at the problems of the range of the positioning region, the positioning accuracy and the energy consumption and the like, the mobile node positioning algorithm in a high-speed environment is proposed in combination with the characteristics of various mobile positioning algorithms, The method has the characteristics of high positioning accuracy and strong independence in a short time by utilizing the sampling range and the dead reckoning algorithm which do not change, and further obtains accurate positioning information. The main research results of this paper are as follows: (1) For the phenomenon that the sampling range of the Monte-Carlo positioning algorithm is too large, the linear deployment is combined with the node deployment based on the regular triangle, and a new algorithm model is proposed. A precise overlap region is obtained by using the characteristic of the sensing range of the anchor node, and the sampling range determined by the speed as the radius is replaced by the traditional Monte Carlo positioning algorithm. (2) In order to solve the problem of the re-sampling and the error accumulation of the dead reckoning algorithm caused by the problem of particle degradation in the Monte-Carlo location algorithm, this paper proposes an improved dead reckoning algorithm, which uses the anchor node information collected in the overlapping area as the reference point for correcting the positioning error. In the discrete time period, the positioning error is corrected by the reference point, and the motion trail of the unknown node is depicted by using the positioning error. (3) Considering the single point failure of the linear deployment and the positioning accuracy of the moving unknown node in the high-speed environment, this paper introduces the data return technique and the abnormal data rejection technique, and constructs a data processing center in the algorithm model. The high-speed moving unknown node transfers the collected information directly to the data processing center, and solves the problem of one-way transfer of data in the linear deployment. After the correction factor is compared with the threshold value, the error value larger than the threshold is eliminated, and the more accurate positioning is obtained. (4) The solution of the high-speed moving node positioning algorithm based on the WSN is simulated, and the uniform speed motion, the uniform acceleration motion and the uniform deceleration motion are compared and analyzed in three groups of different speed, acceleration and reference points. Finally, the positioning error of the algorithm in one-dimensional space and two-dimensional space is compared and analyzed, and the simulation results show that the positioning error in one-dimensional space is less than that in the two-dimensional space, and the same applies to the positioning of the high-speed moving node under the one-dimensional space.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN929.5;TP212.9
[Abstract]:Wireless Sensor Network (WSN) integrated the field of embedded computing technology, sensor technology, wireless communication and micro-electro-mechanical system. It is a new kind of network that has developed rapidly since the 21st century. The WSN deploys a large number of sensor nodes in the monitoring area, monitors, senses and collects the target information in real time through the sensors, and then transmits the acquired data in a wireless communication technology mode; and finally, through the multi-hop among the sensors, the self-organizing mode is transmitted to the user terminal. In recent years, with the research of the wireless sensor and the continuous improvement of the network protocol of the WSN, the WSN has the advantages of low power consumption, low cost, distributed and self-organization and the like, and is widely applied to the military system, the national security, the environment monitoring, the target tracking and the intelligent home, Healthcare and space exploration. As one of the key technologies in the WSN, the location technology is also the hot spot of the research. At present, the location of the WSN node is mainly applied to the target location in the stationary state, and the positioning of the mobile WSN is less. If a number of nodes with high-speed movement capability are deployed in the static WSN, the application range and the adaptability of the WSN positioning are increased, and the requirements of people on the position information in the current era are also met. Therefore, both the positioning of the mobile node in the normal environment or the positioning of the nodes in the high-speed environment have important theoretical and application values. In this paper, the existing mobile WSN node positioning algorithm is deeply studied and the problems existing in the algorithm are analyzed. Aiming at the problems of the range of the positioning region, the positioning accuracy and the energy consumption and the like, the mobile node positioning algorithm in a high-speed environment is proposed in combination with the characteristics of various mobile positioning algorithms, The method has the characteristics of high positioning accuracy and strong independence in a short time by utilizing the sampling range and the dead reckoning algorithm which do not change, and further obtains accurate positioning information. The main research results of this paper are as follows: (1) For the phenomenon that the sampling range of the Monte-Carlo positioning algorithm is too large, the linear deployment is combined with the node deployment based on the regular triangle, and a new algorithm model is proposed. A precise overlap region is obtained by using the characteristic of the sensing range of the anchor node, and the sampling range determined by the speed as the radius is replaced by the traditional Monte Carlo positioning algorithm. (2) In order to solve the problem of the re-sampling and the error accumulation of the dead reckoning algorithm caused by the problem of particle degradation in the Monte-Carlo location algorithm, this paper proposes an improved dead reckoning algorithm, which uses the anchor node information collected in the overlapping area as the reference point for correcting the positioning error. In the discrete time period, the positioning error is corrected by the reference point, and the motion trail of the unknown node is depicted by using the positioning error. (3) Considering the single point failure of the linear deployment and the positioning accuracy of the moving unknown node in the high-speed environment, this paper introduces the data return technique and the abnormal data rejection technique, and constructs a data processing center in the algorithm model. The high-speed moving unknown node transfers the collected information directly to the data processing center, and solves the problem of one-way transfer of data in the linear deployment. After the correction factor is compared with the threshold value, the error value larger than the threshold is eliminated, and the more accurate positioning is obtained. (4) The solution of the high-speed moving node positioning algorithm based on the WSN is simulated, and the uniform speed motion, the uniform acceleration motion and the uniform deceleration motion are compared and analyzed in three groups of different speed, acceleration and reference points. Finally, the positioning error of the algorithm in one-dimensional space and two-dimensional space is compared and analyzed, and the simulation results show that the positioning error in one-dimensional space is less than that in the two-dimensional space, and the same applies to the positioning of the high-speed moving node under the one-dimensional space.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN929.5;TP212.9
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 田浩杉;李翠然;謝健驪;梁櫻馨;;基于時(shí)序蒙特卡洛的WSN節(jié)點(diǎn)定位算法[J];傳感技術(shù)學(xué)報(bào);2016年11期
2 金仁成;朱明;車志平;李應(yīng)琛;;WSN中正三角形剖分的異構(gòu)節(jié)點(diǎn)靜態(tài)部署算法[J];單片機(jī)與嵌入式系統(tǒng)應(yīng)用;2016年02期
3 許擁晶;;探知無線傳感器網(wǎng)絡(luò)[J];上海信息化;2015年08期
4 馬慶功;劉冉冉;;基于DV-Distance的無線傳感器網(wǎng)絡(luò)定位算法研究[J];吉林師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2014年01期
5 游曉鵬;鮑金鳳;邱奉美;李懷忠;;RSSI輔助的蒙特卡羅盒定位算法[J];計(jì)算機(jī)技術(shù)與發(fā)展;2013年12期
6 薛興亮;孫榮凱;高玉章;;基于布爾感知模型的邊界線多重覆蓋算法[J];海軍航空工程學(xué)院學(xué)報(bào);2013年05期
7 丁秀鋒;才巖峰;;IPRAN承載基站數(shù)據(jù)回傳方案技術(shù)研究[J];數(shù)據(jù)通信;2013年01期
8 劉明均;;物聯(lián)網(wǎng)中無線傳感器網(wǎng)絡(luò)的安全技術(shù)[J];物聯(lián)網(wǎng)技術(shù);2012年12期
9 吳大中;張蒙蒙;;基于移動節(jié)點(diǎn)的無線傳感器網(wǎng)絡(luò)定位算法[J];物聯(lián)網(wǎng)技術(shù);2012年05期
10 秦小虎;辛云宏;夏海峰;吳俊林;;無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位技術(shù)[J];計(jì)算機(jī)系統(tǒng)應(yīng)用;2011年09期
相關(guān)碩士學(xué)位論文 前2條
1 蔡鑌;無線傳感器網(wǎng)絡(luò)拓?fù)淇刂扑惴ㄑ芯縖D];西南交通大學(xué);2009年
2 羅詠R，
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