本文選題：室內(nèi)定位 + 無線傳感器網(wǎng)絡(luò)��； 參考：《華東師范大學(xué)》2015年碩士論文

【摘要】：隨著移動互聯(lián)網(wǎng)技術(shù)的蓬勃發(fā)展,基于位置的服務(wù)(Location Based Services, LBS)越來越成為人們生活中必不可少的需求。其中定位技術(shù),即位置信息的獲取,是實(shí)現(xiàn)基于位置的服務(wù)的必要前提和關(guān)鍵。衛(wèi)星導(dǎo)航系統(tǒng)已經(jīng)廣泛應(yīng)用于室外的LBS中,但是由于衛(wèi)星信號無法穿透墻壁等障礙物,使用衛(wèi)星導(dǎo)航系統(tǒng)無法實(shí)現(xiàn)室內(nèi)準(zhǔn)確定位,制約了室內(nèi)LBS的發(fā)展�；跓o線傳感器網(wǎng)絡(luò)的室內(nèi)定位技術(shù)正好彌補(bǔ)了GPS室內(nèi)定位的不足,可以為地下停車場等場所提供實(shí)時的位置和導(dǎo)航信息。目前,已有的室內(nèi)無線定位技術(shù)大多需要額外的硬件設(shè)備,定位成本高,不易于推廣�；诮邮招盘枏�(qiáng)度指示(Received Signal Strength Indicator, RSSI)的定位技術(shù)不需要添加額外設(shè)備,其中RSSI可直接在無線通信過程中獲得。因此基于RSSI的定位技術(shù)成為室內(nèi)定位研究的首選方案。本文在對無線傳感器網(wǎng)絡(luò)定位算法深入分析的基礎(chǔ)上,對基于RSSI的定位算法,即基于RSSI測距的定位算法和基于特征指紋的定位算法分別開展了系統(tǒng)地調(diào)查與研究。本文的研究內(nèi)容和主要貢獻(xiàn)歸納如下：(1)在對信號傳播模型研究的基礎(chǔ)上,提出基于RSSI的自適應(yīng)分段曲線擬合室內(nèi)定位算法。通過實(shí)驗(yàn)驗(yàn)證本文提出的改進(jìn)算法擁有更好的定位精度和更好的環(huán)境適應(yīng)性。(2)研究現(xiàn)有基于特征指紋的定位算法。將定位過程劃分為四個階段,分別討論定位各階段原始RSSI預(yù)處理方法、求解近鄰量度、k近鄰選擇和位置坐標(biāo)確定方法對室內(nèi)定位精度的影響,確定適合當(dāng)前室內(nèi)環(huán)境的最優(yōu)定位算法。(3)設(shè)計(jì)基于無線傳感網(wǎng)的定位算法可供選擇的室內(nèi)定位原型系統(tǒng)。實(shí)驗(yàn)結(jié)果表明改進(jìn)后的基于RSSI定位算法和優(yōu)化后的基于特征指紋的定位算法具有更高的定位精度。
[Abstract]:With the rapid development of mobile Internet technology, location Based Services, LBS) has become an indispensable requirement in people's daily life. Location technology, that is, the acquisition of location information, is the necessary prerequisite and key to realize location-based services. Satellite navigation system has been widely used in outdoor LBS, but because satellite signal can not penetrate obstacles such as walls, the use of satellite navigation system can not achieve accurate indoor positioning, which restricts the development of indoor LBS. The indoor location technology based on wireless sensor network can make up for the deficiency of GPS indoor location, and can provide real-time location and navigation information for underground parking and other places. At present, most of the existing indoor wireless positioning technology need additional hardware equipment, positioning cost is high, it is difficult to be popularized. The location technique based on received signal strength indication received Signal Strength Indicator, RSSI) does not need to add additional equipment, where RSSI can be obtained directly during wireless communication. Therefore, positioning technology based on RSSI has become the first choice of indoor positioning research. Based on the deep analysis of wireless sensor network localization algorithm, this paper makes a systematic investigation and research on the location algorithm based on RSSI, that is, the location algorithm based on RSSI ranging and the location algorithm based on characteristic fingerprint. The research contents and main contributions of this paper are summarized as follows: (1) based on the research of signal propagation model, an adaptive segmented curve fitting indoor localization algorithm based on RSSI is proposed. Experimental results show that the improved algorithm has better localization accuracy and better environmental adaptability.) the existing localization algorithms based on feature fingerprint are studied. The positioning process is divided into four stages, and the original RSSI pretreatment method for each stage is discussed respectively, and the influence of nearest neighbor measurement and location coordinate determination method on indoor positioning accuracy is solved. To determine the optimal location algorithm suitable for the current indoor environment, the prototype system of indoor location based on wireless sensor network is designed. The experimental results show that the improved localization algorithm based on RSSI and the optimized algorithm based on feature fingerprint have higher localization accuracy.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TP212.9;TN929.5

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本文編號：1981081