發(fā)布時間：2018-01-26 05:03

  本文關(guān)鍵詞： ZigBee無線傳感器網(wǎng)絡(luò)技術(shù) Kalman濾波 高斯濾波 虛擬空間劃分 加權(quán)距離 模糊聚類　出處：《南昌大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著時代的發(fā)展,特別是伴隨著移動互聯(lián)網(wǎng)的高速發(fā)展,導(dǎo)航與定位越來越受到人們的關(guān)注,同時與位置有關(guān)的服務(wù)成為了當(dāng)前的一個熱門產(chǎn)業(yè)。定位技術(shù)包含有室內(nèi)外這兩個方面。對于室外獲取地理位置信息,全球衛(wèi)星定位系統(tǒng)(GPS)和網(wǎng)絡(luò)輔助全球衛(wèi)星定位系統(tǒng)(A-GPS)以其高定位精度為人們所熟知,并且在目前來說已經(jīng)是比較成熟的室外定位技術(shù);然而在室內(nèi)環(huán)境下,室內(nèi)定位技術(shù)在目前來講還并不很成熟,所以尋找一種有效的定位技術(shù)方案成為了目前定位服務(wù)領(lǐng)域的一個研究關(guān)鍵。隨著無線傳感器網(wǎng)絡(luò)技術(shù)的出現(xiàn),特別是作為一種新型的短距離無線傳感器網(wǎng)絡(luò)技術(shù)的ZigBee,正作為室內(nèi)定位的一種行之有效的解決方案為越來越多的人去探索和研究�；赯igBee的獨特優(yōu)勢,本文選取的室內(nèi)定位的研究方案是基于ZigBee的無線傳感器網(wǎng)絡(luò)技術(shù)。在闡述了研究的意義和背景的前提下,詳細(xì)介紹了無線定位技術(shù),然后與其他無線定位技術(shù)比較,ZigBee無線傳感器網(wǎng)絡(luò)技術(shù)有其優(yōu)越的條件來作為室內(nèi)定位系統(tǒng)搭建的技術(shù)基礎(chǔ)。然而,室內(nèi)環(huán)境的復(fù)雜性制約了ZigBee室內(nèi)定位精度的提高,本文旨在不額外增加硬件條件的基礎(chǔ)上,使用基于RSSI的指紋數(shù)據(jù)庫室內(nèi)定位方法對ZigBee室內(nèi)定位精度進行優(yōu)化,并且提出了可行性方案,即對信號源的處理和定位算法。通過對室內(nèi)環(huán)境復(fù)雜環(huán)境的研究,本文提出了在對移動節(jié)點接收到的信號源進行濾波處理,包括Kalman濾波和高斯濾波這兩種方式。通過實驗可以得出,在最優(yōu)的情況下,在指紋數(shù)據(jù)庫定位方法中的兩個階段使用Kalman濾波方式對信號源進行處理,使用最鄰近定位算法進行定位計算,最終將定位誤差抑制在1.86m以內(nèi),比未做濾波處理的結(jié)果提高了0.1m,一定程度上提高了定位精度。在基于對常規(guī)定位算法研究的基礎(chǔ)上,本文提出了三種新的室內(nèi)定位算法,分別為虛擬空間劃分的室內(nèi)指紋庫定位算法、一種加權(quán)距離室內(nèi)指紋庫定位算法、模糊聚類室內(nèi)定位算法。在最優(yōu)的情況下,虛擬空間劃分的室內(nèi)指紋庫定位算法可以將定位誤差抑制在1.50m以內(nèi),加權(quán)距離室內(nèi)指紋庫定位算法可以將定位誤差抑制在1.57m以內(nèi),模糊聚類室內(nèi)定位算法可以將定位誤差抑制在1.47m以內(nèi),都在一定程度上使定位精度得到優(yōu)化。
[Abstract]:With the development of the times, especially with the rapid development of mobile Internet, people pay more and more attention to navigation and positioning. At the same time location-related services have become a hot industry. Location technology includes indoor and outdoor aspects of geo-location information for outdoor access. GPS (Global Positioning system) and network-aided GPS (A-GPS) are well known for their high positioning accuracy, and are mature outdoor positioning technologies at present. However, in the indoor environment, indoor positioning technology is not very mature. Therefore, the search for an effective location technology has become a research key in the field of location services. With the emergence of wireless sensor networks (WSN) technology. Especially as a new short-range wireless sensor network technology, ZigBee. Is an effective solution for indoor positioning for more and more people to explore and research. Based on the unique advantages of ZigBee. In this paper, the indoor positioning research scheme is based on ZigBee wireless sensor network technology. On the premise of elaborating the significance and background of the research, the wireless location technology is introduced in detail. Then compared with other wireless positioning technology ZigBee wireless sensor network technology has its advantages to serve as the technical foundation of indoor positioning system. However. The complexity of indoor environment restricts the improvement of indoor positioning accuracy of ZigBee. The indoor positioning accuracy of ZigBee is optimized by using the indoor location method of fingerprint database based on RSSI, and the feasible scheme is put forward. That is the signal source processing and location algorithm. Through the study of the complex indoor environment this paper proposed to filter the signal source received by the mobile node. Including Kalman filtering and Gao Si filtering. Through experiments, we can find that in the best case. In the two stages of fingerprint database location method, the Kalman filter is used to process the signal source, and the nearest neighbor location algorithm is used to locate the signal source. Finally, the localization error is restrained within 1.86m, which is 0.1 m higher than the result without filtering, and the accuracy is improved to some extent. Based on the research of the conventional localization algorithm. In this paper, three new indoor location algorithms are proposed, they are virtual space partition indoor fingerprint database location algorithm, a weighted distance indoor fingerprint database location algorithm. Fuzzy clustering indoor location algorithm. Under the optimal condition, the location error of indoor fingerprint database can be restrained within 1.50m by virtual space partition. The location error can be restrained within 1.57m by the weighted distance indoor fingerprint database localization algorithm, and the location error can be restrained by the fuzzy clustering indoor location algorithm within 1.47m. To a certain extent, the positioning accuracy is optimized.
【學(xué)位授予單位】：南昌大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TN92;TP212.9

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本文編號：1464752