本文關(guān)鍵詞：基于RSSI的室內(nèi)無源感知模型和定位算法研究　出處：《安徽大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 無線傳感網(wǎng) 無源感知 射頻信號(hào) RSSI 橢圓定位算法

【摘要】：現(xiàn)如今,無線傳感器網(wǎng)絡(luò)作為物聯(lián)網(wǎng)底層感知的重要組成部分得到了越來越多的發(fā)展和應(yīng)用,與此同時(shí),人們對(duì)于感知定位技術(shù)的需求也越來越高;因此,利用無線傳感器網(wǎng)絡(luò)進(jìn)行無源感知定位作為一種新的研究方向得到了廣泛關(guān)注。基于無線傳感器網(wǎng)絡(luò)的無源感知定位方法與傳統(tǒng)的感知定位方法相比有著許多優(yōu)點(diǎn)。常用的通過檢測(cè)光線、超聲波、紅外線等物理屬性的感知定位方法會(huì)受到很多環(huán)境因素的限制,如光線、溫度、盲區(qū)等�；跓o線傳感器網(wǎng)絡(luò)的無源感知方法可以不受上述因素的干擾,它能有效的適應(yīng)各種變化的環(huán)境,并且不需要感知目標(biāo)配合攜帶任何的電子標(biāo)簽和移動(dòng)設(shè)備,是一種新型的無源感知方法。因此它具有更為廣闊的發(fā)展和應(yīng)用前景。在無線傳感器網(wǎng)絡(luò)中使用射頻信號(hào)進(jìn)行無源感知的方法,本質(zhì)上是利用了障礙物遮擋對(duì)無線信號(hào)鏈路的影響,當(dāng)有物體遮擋無線鏈路時(shí),會(huì)使得鏈路信號(hào)接收強(qiáng)度(Received Signal Strength Indication,RSSI)發(fā)生改變,通過分析無線鏈路的這種變化屬性,總結(jié)其變化規(guī)律,可以實(shí)現(xiàn)在實(shí)驗(yàn)區(qū)域內(nèi)進(jìn)行人員感知的目的,并通過利用橢圓模型算法,對(duì)感知區(qū)域內(nèi)存在的人員進(jìn)行定位。因此,本文圍繞室內(nèi)無源感知模型和定位算法開展研究。論文首先分析了室內(nèi)無線信號(hào)的傳播特征和衰落模型,分析找出障礙物對(duì)信號(hào)功率的影響原因,并總結(jié)了橢圓模型定位方法,在此基礎(chǔ)上設(shè)計(jì)了無源感知定位實(shí)驗(yàn)?zāi)Ｐ秃蛯?shí)驗(yàn)方案,這其中包括了對(duì)感知定位流程的規(guī)劃,對(duì)實(shí)驗(yàn)平臺(tái)的設(shè)計(jì),所采用的數(shù)據(jù)收集和處理方法以及感知定位所采用的算法程序。同時(shí),在實(shí)驗(yàn)?zāi)Ｐ偷幕A(chǔ)上研究了橢圓模型定位算法,并根據(jù)實(shí)驗(yàn)結(jié)果分析算法的缺陷,對(duì)定位算法進(jìn)行了改進(jìn),解決了定位中出現(xiàn)的邊緣效應(yīng),提高橢圓模型定位算法的定位精度。在搭建實(shí)驗(yàn)系統(tǒng)的硬件選擇上,實(shí)驗(yàn)中使用了以CC2530芯片作為控制核心的ZigBee無線傳感器網(wǎng)絡(luò)定位節(jié)點(diǎn)硬件模塊;在軟件編程中,實(shí)驗(yàn)中通過IAR Embedded Workbench編譯環(huán)境使用了 TI官方提供的簡(jiǎn)單協(xié)議Basic RF來編寫和修改節(jié)點(diǎn)程序,完成感知節(jié)點(diǎn)的程序設(shè)計(jì);通過使用環(huán)協(xié)機(jī)制實(shí)現(xiàn)了對(duì)于整個(gè)傳感器網(wǎng)絡(luò)節(jié)點(diǎn)的控制和數(shù)據(jù)采集,完成了無源感知定位實(shí)驗(yàn)?zāi)Ｐ偷能浻布脚_(tái)搭建,并對(duì)實(shí)驗(yàn)結(jié)果進(jìn)行分析。
[Abstract]:Nowadays, as an important part of the bottom perception of the Internet of things, wireless sensor networks have been more and more developed and applied. So... Passive sensing localization based on wireless sensor network (WSN) has been paid more attention as a new research direction. Compared with traditional sensor network, passive sensing localization method based on wireless sensor network has many advantages. Point. Commonly used by detecting light. Ultrasonic, infrared and other physical properties of the sensing and positioning methods will be limited by many environmental factors, such as light, temperature. Blind area, etc. The passive sensing method based on wireless sensor network can not be disturbed by the above factors, it can effectively adapt to all kinds of changing environment. And does not need to sense the target to carry any electronic tags and mobile devices. It is a new passive sensing method. Therefore, it has a broader development and application prospects. In wireless sensor networks, radio frequency signals are used for passive sensing. In essence, the influence of obstacle occlusion on wireless signal link is utilized, when there is an object blocking wireless link. The received Signal Strength indication (RSSI) of the link signal is changed. By analyzing the changing attributes of wireless link and summarizing its changing rules, we can realize the purpose of personnel perception in the experimental area, and use the elliptic model algorithm. Therefore, this paper focuses on the indoor passive sensing model and localization algorithm. Firstly, the propagation characteristics and fading model of indoor wireless signal are analyzed. The influence of obstacles on signal power is analyzed and the elliptic model localization method is summarized. Based on this the passive sensing localization experimental model and experimental scheme are designed. This includes the planning of the perceptual localization process, the design of the experimental platform, the data collection and processing methods used and the algorithm program used in the perceptual localization. At the same time. Based on the experimental model, the elliptic model localization algorithm is studied. According to the experimental results, the defect of the algorithm is analyzed, and the localization algorithm is improved to solve the edge effect. Improve the location accuracy of the elliptic model location algorithm in building the hardware of the experimental system selection. In the experiment, the hardware module of positioning node in ZigBee wireless sensor network based on CC2530 chip is used. In software programming. In the experiment, we use the simple protocol Basic RF provided by TI to write and modify the node program through IAR Embedded Workbench compilation environment. Complete the program design of the perceptual node; The control and data acquisition of the whole sensor network node is realized by using the mechanism of environment cooperation, and the hardware and software platform of the passive sensing localization experimental model is built, and the experimental results are analyzed.
【學(xué)位授予單位】：安徽大學(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 熊偉;;面向物聯(lián)網(wǎng)的無線傳感器網(wǎng)絡(luò)綜述[J];電子技術(shù)與軟件工程;2015年14期

2 張文濤;李賀武;;基于信號(hào)傳播特征的室內(nèi)定位和追蹤技術(shù)研究[J];小型微型計(jì)算機(jī)系統(tǒng);2014年07期

3 周逢道;郭新;唐紅忠;王金玉;;海洋探測(cè)設(shè)備的超聲波定位系統(tǒng)設(shè)計(jì)[J];實(shí)驗(yàn)室研究與探索;2013年11期

4 李華嵩;姜先威;;基于BasicRF的Zigbee無線透?jìng)髂K設(shè)計(jì)[J];通信技術(shù);2013年11期

5 楊小軍;;多跳無線傳感器網(wǎng)絡(luò)下信道感知的目標(biāo)定位方法[J];自動(dòng)化學(xué)報(bào);2013年07期

6 龔文超;吳猛猛;劉雙雙;;基于CC2530的無線監(jiān)控系統(tǒng)設(shè)計(jì)與實(shí)現(xiàn)[J];電子測(cè)量技術(shù);2012年06期

7 嚴(yán)萍;張興敢;柏業(yè)超;杜仲林;;基于物聯(lián)網(wǎng)技術(shù)的智能家居系統(tǒng)[J];南京大學(xué)學(xué)報(bào)(自然科學(xué)版);2012年01期

8 宋立橋;朱凌云;;基于ZigBee的搶險(xiǎn)救災(zāi)無線傳感器網(wǎng)絡(luò)[J];電子測(cè)量技術(shù);2011年09期

9 李新;;基于CC2530的Zigbee網(wǎng)絡(luò)節(jié)點(diǎn)設(shè)計(jì)[J];可編程控制器與工廠自動(dòng)化;2011年03期

10 張華;王萬良;;改進(jìn)質(zhì)心算法的節(jié)點(diǎn)自定位研究[J];現(xiàn)代電子技術(shù);2009年16期

，

本文編號(hào)：1367922