本文關(guān)鍵詞： Wi-Fi 定位 位置指紋 傳感器　出處：《武漢理工大學》2014年碩士論文　論文類型：學位論文

【摘要】：隨著智慧城市建設的興起和移動互聯(lián)網(wǎng)的快速發(fā)展，人們對基于位置的服務需求日益增強，這就要求其能夠?qū)崿F(xiàn)準確的定位與跟蹤。目前，定位技術(shù)廣泛應用于各個領(lǐng)域，而基于GPS的室外定位的成功應用也激勵了室內(nèi)定位系統(tǒng)的研究與開發(fā)。然而由于接受信號微弱，GPS系統(tǒng)不能有效運用于建筑物內(nèi)部和密集的都市區(qū)域。目前的室內(nèi)定位系統(tǒng)采用的技術(shù)主要有計算機視覺、紅外線、射頻識別、超寬帶、無線傳感網(wǎng)絡、AGPS等，但這些系統(tǒng)往往需要部署額外的設施，應用時大受限制。基于Wi-Fi的室內(nèi)定位系統(tǒng)能夠充分利用現(xiàn)有的基礎(chǔ)設施，在不需要部署額外設備的情況下，應用于提供室內(nèi)位置服務。而且智能手機也都內(nèi)置了Wi-Fi模塊，，這使得基于Wi-Fi的室內(nèi)定位成為可能。所以使用智能手機利用遍布建筑物內(nèi)的Wi-Fi信號定位成為了一種極具潛力的室內(nèi)定位技術(shù)。 本文在對Wi-Fi室內(nèi)定位技術(shù)進行充分研究的基礎(chǔ)上，針對現(xiàn)有的基于指紋的Wi-Fi定位算法存在的不足之處提出了相應的改進算法，并設計和實現(xiàn)了Wi-Fi室內(nèi)定位系統(tǒng)。首先，本文對Wi-Fi的接收信號強度特性和影響因素進行分析，包括RSSI的概率分布，RSSI與距離的關(guān)系，人體方位的影響和不同設備的影響。其次，從定位系統(tǒng)構(gòu)建及工作流程出發(fā)，依次探討了數(shù)據(jù)采集構(gòu)建位置指紋數(shù)據(jù)庫，實時定位階段的預處理過程，定位參考AP選擇，信號距離，近鄰選取和定位結(jié)果計算等。在定位結(jié)果計算階段，提出最密集近鄰算法，通過比較可知，相比傳統(tǒng)質(zhì)心法能得到更好的定位精度。然后，對卡爾曼濾波器在動態(tài)定位追蹤中的作用進行分析。通過手機傳感器判斷用戶運動狀態(tài)發(fā)生變化，使用不同的卡爾曼參數(shù)，有效改善了動態(tài)定位追蹤的效果。接著，通過研究基于手機傳感器的定位，提出Wi-Fi定位與傳感器定位的融合算法，在無法進行Wi-Fi定位時使用傳感器定位，可以有效彌補Wi-Fi定位的不足。同時在Wi-Fi正常定位過程中，能夠?qū)i-Fi定位波動較大的情況進行較好地校正，有效改善動態(tài)定位追蹤的效果。最后，設計并實現(xiàn)基于Android手機平臺的位置指紋Wi-Fi室內(nèi)定位系統(tǒng)，并對軟件各個模塊進行分析。實驗結(jié)果表明，本文提出的算法能夠更有效地實現(xiàn)高精度的Wi-Fi室內(nèi)定位。
[Abstract]:With the rise of intelligent city construction and the rapid development of mobile Internet, people's demand for location-based services is increasing, which requires them to achieve accurate positioning and tracking. At present, positioning technology is widely used in various fields. The successful application of outdoor positioning based on GPS also encourages the research and development of indoor positioning system. However, because of the weak reception signal, GPS system can not be effectively used in the interior of buildings and in dense urban areas. The main technologies used in the positioning system are computer vision, Infrared, radio frequency identification, ultra-wideband, wireless sensor networks, AGPS, etc., but these systems often need to deploy additional facilities and are severely restricted in their application. Indoor positioning systems based on Wi-Fi can take full advantage of existing infrastructure. It is used to provide indoor location services without the need to deploy additional devices, and smartphones are built into Wi-Fi modules. This makes indoor positioning based on Wi-Fi possible, so using smart phones to use Wi-Fi signals all over the building has become a potential indoor location technology. Based on the research of Wi-Fi indoor location technology, this paper puts forward the corresponding improved algorithm for the existing fingerprint based Wi-Fi localization algorithm, and designs and implements the Wi-Fi indoor positioning system. In this paper, the characteristics and influencing factors of the received signal intensity of Wi-Fi are analyzed, including the relation between the probability distribution of RSSI and distance, the influence of human body orientation and different equipments. Data acquisition and construction of location fingerprint database, preprocessing process of real-time positioning stage, selection of location reference AP, selection of signal distance, selection of nearest neighbor and calculation of location result are discussed in turn. This paper proposes the densest nearest neighbor algorithm, which can get better positioning accuracy than the traditional centroid method. The function of Kalman filter in dynamic location tracking is analyzed. The mobile phone sensor is used to judge the change of user's motion state, and different Kalman parameters are used to effectively improve the effect of dynamic location tracking. By studying the location of mobile phone sensor, the fusion algorithm of Wi-Fi location and sensor location is proposed. When Wi-Fi positioning cannot be carried out, using sensor positioning can effectively compensate for the deficiency of Wi-Fi location. At the same time, in the process of Wi-Fi normal positioning, It can correct the large fluctuation of Wi-Fi location, and improve the effect of dynamic location tracking. Finally, the location fingerprint Wi-Fi indoor positioning system based on Android mobile platform is designed and implemented. The experimental results show that the algorithm proposed in this paper can achieve high precision Wi-Fi indoor positioning more effectively.
【學位授予單位】：武漢理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN92

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本文編號：1503624