發(fā)布時間：2018-01-16 08:18

  本文關(guān)鍵詞：基于RSSI的WSN定位算法及測距影響因素的研究　出處：《吉林大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 無線傳感器網(wǎng)絡(luò) RSSI測距 常態(tài)分布 距離修正 加權(quán)質(zhì)心

【摘要】：隨著物聯(lián)網(wǎng)概念的普及和研究的深入，作為其核心技術(shù)之一的無線傳感器網(wǎng)絡(luò)技術(shù)更加引起各國研究人員的關(guān)注熱情，在軍事、醫(yī)療、建筑和交通等領(lǐng)域的應(yīng)用層出不窮，這些應(yīng)用的共同特點是都需要獲取事件發(fā)生的位置信息，這就涉及到無線傳感器網(wǎng)絡(luò)定位技術(shù)。一般來說，WSN的定位可以分為兩種類型：基于距離的和與距離無關(guān)的。與距離無關(guān)的定位方法不需要測距，這降低了硬件成本，但它的定位精度比基于距離的定位方法要差一些�；赗SSI測距的定位方法的優(yōu)勢在于其便捷和低成本的特性，如果能采取一定的措施來降低測距和定位算法帶來的誤差，這種定位方法將具有更加廣闊的商業(yè)應(yīng)用前景。 本文的具體研究內(nèi)容和創(chuàng)新工作如下： 1.系統(tǒng)論述了WSN的概念、體系結(jié)構(gòu)、特點和在不同領(lǐng)域中的比較有特點的應(yīng)用。指出無線傳感器網(wǎng)絡(luò)定位技術(shù)的研究意義，詳細闡述了WSN發(fā)展過程中誕生的種種定位系統(tǒng)和定位算法，總結(jié)國內(nèi)外最新的研究現(xiàn)狀。 2.研究了無線電傳播的幾類數(shù)學(xué)模型，做實驗收集數(shù)據(jù)擬合出RSSI測距模型。探究了影響RSSI測距的兩個因素：天線的方向和人移動的速度。通過做實驗收集數(shù)據(jù)，統(tǒng)計出RSSI的平均值和方差，利用上述信息和RSSI的波動范圍來確定不同程度的因素對RSSI值的影響程度。 3.從分析基于RSSI的加權(quán)質(zhì)心定位算法入手，針對可能引起定位誤差的環(huán)節(jié)，提出了三處改進：對大量的RSSI值進行常態(tài)分布處理，劃定高概率發(fā)生區(qū)域之后再求均值；對RSSI測距模型得出的距離引入差分修正模型，用參考節(jié)點的測距誤差因子來修正未知節(jié)點的測距；對三邊定位法定位出來的多個未知節(jié)點的近似坐標，綜合考慮三邊定位時影響定位精度的因素，最后選擇三種權(quán)值因子進行加權(quán)：距離權(quán)值、角度權(quán)值、面積和邊長權(quán)值，再對計算出來的三個坐標進行融合，，求得未知節(jié)點的最終估計位置。 4.通過Matlab平臺對改進算法進行了仿真，對比基于RSSI的加權(quán)質(zhì)心定位算法和基于RSSI的差分修正質(zhì)心定位算法在定位誤差方面的表現(xiàn)，并分別在不同的信標節(jié)點個數(shù)的情況下進行了比較。另外還對比了改進算法在最后一步坐標融合時采用不同權(quán)值系數(shù)組合的定位誤差，確定了較優(yōu)的組合方案。最終通過仿真實驗驗證了改進算法在減小定位誤差上的優(yōu)勢。
[Abstract]:With the popularity of the concept of the Internet of things and the depth of research, as one of its core technologies, wireless sensor network technology has attracted more and more attention of researchers from all over the world, in the military, medical care. There are many applications in the field of architecture and transportation. The common feature of these applications is that they need to obtain the location information of events, which involves the location technology of wireless sensor networks. The location of WSN can be divided into two types: distance-based and range-independent. Range-independent localization methods do not require ranging, which reduces the cost of hardware. However, the positioning accuracy is lower than that based on distance. The advantage of the location method based on RSSI is its convenience and low cost. If some measures can be taken to reduce the errors caused by ranging and localization algorithms, this method will have a wider commercial application prospect. The specific research contents and innovative work of this paper are as follows: 1. The concept, architecture, characteristics and application of WSN in different fields are discussed systematically. The research significance of wireless sensor network localization technology is pointed out. In this paper, various localization systems and localization algorithms born during the development of WSN are described in detail, and the latest research status at home and abroad is summarized. 2. Several mathematical models of radio propagation are studied. The experimental data were collected to fit the RSSI ranging model. Two factors affecting the RSSI ranging were explored: the direction of the antenna and the speed of human movement. The average value and variance of RSSI are calculated, and the influence of different factors on RSSI value is determined by using the above information and the fluctuation range of RSSI. 3. Based on the analysis of weighted centroid localization algorithm based on RSSI, three improvements are put forward: dealing with the normal distribution of a large number of RSSI values. The mean value is obtained after the high probability area is delineated; A differential correction model is introduced to the distance obtained from the RSSI ranging model, and the ranging error factor of the reference node is used to correct the distance measurement of the unknown node. For the approximate coordinates of many unknown nodes located by the trilateral localization method, the factors that affect the positioning accuracy are considered synthetically. Finally, three weight factors are selected for weighting: distance weight value, angle weight value. The area and the weight of the side length are fused to the calculated three coordinates and the final estimated position of the unknown node is obtained. 4. The improved algorithm is simulated on Matlab platform, and the performance of weighted centroid location algorithm based on RSSI and differential modified centroid location algorithm based on RSSI is compared. In addition, the location errors of the improved algorithm in the last step coordinate fusion using different weight coefficients combination are compared respectively in the case of different number of beacon nodes. Finally, the advantages of the improved algorithm in reducing the location error are verified by simulation experiments.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN929.5;TP212.9

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