無線傳感器網絡加權質心定位算法分析.pdf

重慶大學碩士學位論文 英文摘要 II ABSTRACT As the basis for the implementation of the Internet of Things （ IOT） , the Wireless Sensor Network （ WSN） was confirmed as the critical ination transmission technology by national policy. With the development of society, positioning and navigation services will be more and more needed to people. Such characteristics of microsensor as low power, low cost, multi－ function that makes positioning technology based on WSN has a significant cost advantage and great potential research value. Besides, the positioning accuracy of WSN is not very satisfactory so far that makes the space of research in this field broadly. Weighted Centroid Algorithm （ WCA） was chosen to make the further research on location technology for its being applied to the localization project of laboratory. It combines the advantages of RSSI ranging technology and centroid algorithm as one algorithm. Implementation of this algorithm is simple, without the installation of additional hardware devices. In the process of positioning experiment we found that the initial weight coefficient values seriously affect the positioning perance of WCA algorithm, and on the edge of location area the positioning precision is poor in the case of only a few anchor nodes was laid. In order to truly meet the needs of practical application, two improved algorithms would be proposed to improve the positioning accuracy of WCA. The main research results in this paper are described as follows. ① Through the mathematical derivation and analysis for WCA ula, we realized exactly from the perspective of the derivative how the changing of weighting coefficients of WCA will affect the location results, which is provided a theoretical basis for adjusting parameter for the weighted centroid localization algorithm to make positioning controllable . ② An improved algorithm was proposed by optimizing the initial weighted parameter. A more accurate positioning result will get through Parameter of Weight Self－ Adjusting （ PWSA） according to the principle of negative feedback. Simulation results show that the overall positioning accuracy of this algorithm surpass traditional weighted centroid algorithm. Under the condition that the weight parameter is not less than 1.8, the positioning accuracy of this algorithm has nothing to do with the initial weighted parameter, so there is no need to constantly adjust the weighting coefficient during the process of algorithm application. 重慶大學碩士學位論文 英文摘要 III ③ To further improve the positioning accuracy on the edge of location area, an improved weighted centroid algorithm was put forward based on Virtual Static Anchor Nodes（ VSAN） . In this paper, VSAN have been proposed to participate in the positioning, which are fabricated by the combination of location ination of the known anchor nodes and cosines law. This algorithm inherits the favorable characteristics from WCA like low－ complexity, easy to implement. Without the installation of additional anchor nodes, the positioning accuracy can be improved obviously. Keywords: Wireless sensor network, Localization technology, Weighted centroid algorithm, Weighted parameter, Virtual static anchor nodes 重慶大學碩士學位論文 目 錄 IV 目 錄 中文摘要 ········································································································ I 英文摘要 ······································································································· II 1 緒論 ············································································································ 1 1.1 研究背景 ···································································································· 1 1.1.1 無線傳感器網絡概述 ··············································································· 1 1.1.2 無線傳感器網絡關鍵支撐技術 ··································································· 2 1.1.3 無線傳感器網絡發展和應用 ······································································ 4 1.2 無線傳感器網絡定位技術 ·············································································· 5 1.2.1 現有定位技術介紹 ·················································································· 5 1.2.2 定位研究的必要性和可行性 ······································································ 7 1.2.3 傳感器定 位面臨的問題 ············································································ 8 1.3 研究內容及章節安排 ···················································································· 9 1.3.1 主要研究內容 ························································································ 9 1.3.2 論文章節安排 ························································································ 9 2 無線傳感器網絡定位算法 ······································································ 11 2.1 定位基本概念 ···························································································· 11 2.2 定位算法的分類 ························································································ 11 2.3 典型定位算法介紹 ····················································································· 13 2.3.1 Range－ Based 定位算法 ·········································································· 13 2.3.2 Range－ Free 定位算法 ············································································ 17 2.3.3 定位算法評價 ······················································································ 20 2.4 加權質心定位算法 ····················································································· 21 2.5 本章小結 ·································································································· 23 3 基于權重系數自調整的加權質心定位算法 ·········································· 24 3.1 引言 ········································································································ 24 3.2 權重系數特性分析 ····················································································· 24 3.2.1 算法整體權重系數 n 特性分析 ································································· 25 3.2.2 錨節點權重系數 nj 特性分析 ···································································· 26 3.3 基于權重系數自調整的 PWSA 算法 ······························································· 26 3.3.1 PWSA 算法原理 ···················································································· 26 3.3.2 PWSA 算法流程 ···················································································· 30 重慶大學碩士學位論文 目 錄 V 3.4 PWSA 算法仿真 ························································································· 32 3.4.1 仿真環境設置 ······················································································ 32 3.4.2 仿真方案及結果 ··················································································· 32 3.4.3 仿真結果分析 ······················································································ 34 3.5 PWSA 算法實驗 ························································································· 34 3.5.1 實驗設置 ····························································································· 34 3.5.2 實驗結果 ···························································································· 36 3.6 本章小結 ·································································································· 37 4 基于虛擬靜態錨節點的加權質心定位算法 ········································· 38 4.1 引言 ········································································································ 38 4.2 加權質心算法分析 ····················································································· 38 4.2.1 權重系數特性分析 ················································································ 38 4.2.2 RSSI 測距作用分析 ················································································ 38 4.2.3 錨節點數量較少時定位誤差較大的原因分析 ··············································· 38 4.3 基于虛擬靜態錨節點的 VSAN 算法 ································································ 39 4.3.1 VSAN 算法原理 ···················································································· 39 4.3.2 VSAN 算法流程 ···················································································· 41 4.4 VSAN 算法仿真 ························································································· 42 4.4.1 仿真環境設置 ······················································································ 42 4.4.2 仿真方案及結果 ··················································································· 42 4.4.3 仿真結果分析 ······················································································ 45 4.4.4 VSAN 改進算法仿真 ·············································································· 46 4.4.5 VSAN－ PWSA 算法仿真 ········································································· 48 4.5 VSAN 算法實驗 ························································································· 49 4.5.1 實驗設置 ····························································································· 49 4.5.2 實驗結果 ····························································································· 49 4.6 本章小結 ·································································································· 50 5 總結與展望 ······························································································ 51 5.1 工作總結 ·································································································· 51 5.2 研究展望 ·································································································· 52 致 謝 ······································································································ 54 參考文獻 ······································································································ 55 附 錄 ······································································································ 59 A.作者在攻讀碩士學位期間發表的論文 ································································ 59 重慶大學碩士學位論文 目 錄 VI B.作者在攻讀碩士學位期間參與的項目 ································································ 59 C.作者在攻讀碩士學 位期間獲得的榮譽 ································································ 59 重慶大學碩士學位論文 1 緒論 1 1 緒論 1.1 研究背景 1.1.1 無線傳感器網絡概述 無線傳感器網絡 （ Wireless Sensor Network，簡稱 WSN） 由部署在監測區域內大量廉價低功耗的微型傳感器節點組成，節點之間通過無線通信組成一個多跳自組織網絡，其目的是協作地感知、采集和處理網絡覆蓋區域中的特定信息 [1]。 WSN 技術是 21 世紀頗具發展空間的研究領域。尤其是最近十年，隨著物聯網技 術的推廣， WSN 必將更多的融入人們的日常生活。作為集通信、傳感與普適計算三大技術結合的產物， WSN 已成為實現物聯網覆蓋的重要技術支撐 [3]。 2012年國家工信部制定的《物聯網 “ 十二五 ” 發展規劃》中，無線傳感器網絡被列為需要重點研究的信息傳輸技術，受到了格外的關注和重視。 I n t e r n e t 網 絡G P R S 網 絡數 據 服 務 器 監 控 中 心大 屏 幕 顯 示防 火 墻vvS i n kS i n kS i n k監 測 區 域 1監 測 區 域 2S i n k傳 感 器 節 點圖 1.1 無線傳感器網絡體系結構 Fig.1.1 Framework of WSNs 典型的 WSN 結構由 Sensor Node、 Sink Node、外部 Internet 網絡及 Terminal Client等組成，如圖 1.1所示。負責采集和傳輸有效信息的是傳感器節點 Sensor Node；匯聚節點 Sink Node 接收、簡單處理并轉發 Sensor Node 傳輸的數據至網關，后者通過外部網絡 （ INTERNET/GPRS 等方式 ） 將最終的有效信息發送給 Terminal Client。Terminal Client也可以通過外部網絡經由匯聚節點向傳感器節點發送新的指令變更服務內容。 WSN 具有區別于一般無線網絡的特點 ： 網絡中傳感器數量規模大、單個傳感器節點存儲和計算能力有限、以應用和數據為中心的自組織拓撲結構 [4]。目前 WSN技術的應用也存在 諸多挑戰 ： 如傳感器節點存儲空間小、計算能力不足；隨機布重慶大學碩士學位論文 1 緒論 2 撒的傳感器自身位置信息不易獲取；無線網絡信息傳輸的安全性等問題有待解決 [6]。 1.1.2 無線傳感器網絡關鍵支撐技術 無線傳感器網絡關鍵支撐技術網絡關鍵技術服務支撐技術應用支持技術路由協議M A C 協議物理層通信標準時間 同步拓撲控制節點定位信息整合網絡安全網絡 管理操作 系統系統開 發資源 管理任務管理數據管理網絡維護節點 管理硬件開發軟件開 發圖 1.2 無線傳感器網絡關鍵支撐技術 Fig.1.2 Key technologies in WSNs 如圖 1.2 所示， WSN 關鍵支撐技術涉及很多相關技術，根據服務層次不同可分類為 ： 網絡關鍵技術、服務支撐技術和應用支持技術。作為 WSN 的核心支持技術，服務支撐技術又包括 時間同步 、拓撲 管理 、節點定位、數據融合、網絡安全等技術。 ① 時間同步 [9]： 作為一種分 布式系統， WSN 具有時空分散性的特點 。 整個 網絡 中各個節點之間 很難實現完全的時間同步 。即使在初始化 階段各個節點之間 達到 了 時 間 同步， 網絡運行過程中也可能 會出現 個別性 偏差，這是因為 網絡中 各個節點 的晶體振蕩器頻率不 可能 完全一致 。 除此之外 各個節點所處 環境中的溫濕度重慶大學碩士學位論文 1 緒論 3 的 差異性 、 空間中其它射頻信號 的 影響 ， 都有可能 使 網絡 時鐘失去統一性。 網絡中實現 各個節點之間時間同步或者相對同步 對很多技術的應用起著 至關重要的 影響 ， 例 如基于時序 原理 的數據融合 [10]、基于時分復用的低功耗 MAC 協議 [11]、基于到達時間或時間差的 物理 測距 [12]及網絡信息安全加密 [13]等方面。 ② 拓撲 管理 ： 為使無線傳感器網絡的 生命 周期 更長、網絡中數據處理的 速度更快、傳輸的更遠，需要 適當 的 控制 機制對 分散 的節點進行管理。 WSN 節點數量多、自主組網、節點計算和存儲能力不足等特點決定 了其網絡 拓撲管理策略必須更加合理和高效。網絡中節點數目和位置的不固定、所需完成的任務功能的變更要求對節點 的 控制 應具備 良好 的自適應性，從而實現網絡的優化控制。 研究 面臨的挑戰是 ： 在不 降低 網絡連通性和通信覆蓋率的條件下， 如何增大信息的處理速度和信息的傳輸效率，延長網絡的生命周期 [14]。目前主要的解決途徑是通過 管理節點發射功率、調控 組網方式 等策略改善 網絡 結構。 ③ 節點定位 ： 顧名思義節點定位就是 利用 特定的計算方法確定網絡中某個節點地理位置的過程 [15]。只有 確定了檢測數據的具體來源位置 ， WSN 中的很多監測信息 才具有真正的實用價值。 傳感器節點由于其低成本、 體積 小 和低功耗 等 特性，使得基于 WSN 大規模節點的定位技術具有獨特的價格優勢。隨著國家城市綜合體和智慧城市的規劃設計，基于位置感知的服務 LBS（ Location Based Services） 將會越來越多。人們迫切的需求獲取更加方便、覆蓋范圍更廣、精度更高的定位和導航服務。特別是在 一些復雜的特殊的地理環境中，對于目標的精準定位顯得尤為重要，如監獄、倉庫、礦井、大型場館等 室內 環境。隨著物聯網技術的逐步發展，低成本、低功耗、多功能的微型傳感器將在未來遍布我們的四周，這為利用無線傳感器網絡技術進行定位提供了極為便利的條件。定位的準確性是衡量節點定位的最主要標準。準確性要求越高， 技術 難度越大，對成本的要求也隨之增加。設計定位系統時需要考慮的因素很多，包括傳感器節點的選擇以及定位算法的設計。此外環境因素對定位精度的影響不可忽略，因此在實際應用中，必須適應不同的應用要求和不同的定位環境來設計 不同 的 定位算法 。 ④ 數據融合 ： 無線傳感器網絡 往往要覆蓋較大的監測區域 ，采集到的大量數據通常存在較大的冗余， 對這些數據無條件的處理和傳輸將 造成 網絡 存儲空間和通信開銷的巨大浪費， 繼而 大大縮短了整個網絡的生命周期 [16]。這就需要 一種 優化 的 數據處理 策略 ，能夠以最終目標信息為 核心淘汰冗余數據 ，同時使資源利用率達到 最大 。解決 上述 問題的途徑就是對冗余的信息進行高效的數據融合。傳感器模塊依據其運算能力、與目標數據是否相關、存儲空間余量和剩余能量多少等制約條件， 在采集信息的過程中 過濾重復數據，減少傳輸次數；更進一步綜合多組信息， 最終 提煉出 表征目標的 核心 數據，使得感知更為 準 確、能耗更為 合理 、重慶大學碩士學位論文 1 緒論 4 網絡生命周期更長。 ⑤ 網絡安全 ： 網絡 信息的安全和加密同樣制約著 WSN 的推廣和應用。 WSN傳感器節點通常被隨機的或特 定 的布撒在應用環境中的某些位置，其采集和處理的數據信息在傳輸的過程中完全暴露在空氣中，很容易被惡意的竊取和篡改。直接導致的結果就是用戶的隱私性和數據的安全性得不到保證，這將使無線傳感器網絡的應用受到很大的限制。無線傳感器網絡安全研究主要從密鑰管理、安全路由、安全組播、數據融合和安全定位來考慮 [17]，目標是要確保傳輸數據的安全、可靠、 機密、完整和時效 性 。 1.1.3 無線傳感器網絡發展和應用 1979 年，美 國國 防曙 DARPA 的分布式傳感器網絡項目開啟無線傳感器網絡研究先河。 1993 年，無線集成傳感器網絡 WINS 項目在 DARPA 的支持幫助下正式啟動。該項目涉及了 MEMS 傳感器和接收器、監測理論的基本原理、信號處理結構、網絡協議設計等多方面的問題 [18]。 1996 年，開始設計低功耗的傳感器節點，提出了節能、可重構的成組遞階網絡通信協議即 LEACH 協議 [19]。 2002 年，英特爾公司發布了 “ 基于微型傳感器網絡的新型計算發展規劃 ” ，該規劃試將無線傳感器網絡技術應用于環境監測、預防醫學，甚至于海底板塊調查、行星探測等眾多領域。 2004 年，無線傳感器網絡被中國國家自然科學基金委員會列為重點研究項目。 2006 年，國務院發布《國家中長期科學與技術發展規劃綱要》 [20]，將智能感知技術、自組織網絡技術、虛擬現實技術作為信息技術的前沿技術。無線傳感器網絡是我國 2010 年遠景規劃和 “ 十一五 ” 規劃中的重點發展的產業之一。 發展無線傳感器網絡的初衷是服務于軍事國防領域的需要，后來隨著相關技術的不斷成熟，應用領域逐漸擴展到民用和商用，其中涉及反恐抗災、環境監測、醫療健康、工商服務、交通管理等領域 [21]。預計在不久的將來， WSN 技術會在各行各業中發揮 更大的 作用。 ① 軍事方面 發展無線傳感器網絡的初衷是服務于軍事國防領域的需要。戰爭期間將若干個傳感器節點由飛行器布撒在敵方目標區域，借此了解實時準確的軍事信息。 2001年，美軍為了獲取更加全面準確的戰場信息，制定了 “ Smart Sensor Network Communication” 計劃。計劃在目標區域內布撒若干微型傳感器，通過傳感器反饋戰場特征信息，便于軍方及時了解戰場信息做出正確決策。 2003年，同樣是美國軍方在 Ohio進行名為 “ A Line IN the Sand” 系統測試 [22]，該系統主要由無線傳感器重慶大學碩士學位論文 1 緒論 5 網絡構成。利用事先布撒在戰場內的相關微型傳感器進行偵測，完成對軍事目標的識別和定位等任務。 ② 民用方面 民用方面的應用涉及范圍更廣，包括在工農業生產、建筑節能監測、生態環境保護監測、定位于導航等多個應用領域。伴隨微型傳感器種類的增多，傳感器完成的功能也更加多樣化。例如采集感官信息的溫濕度傳感器、紅外光照傳感器、壓力傳感器等；負責采集視覺信息的視頻圖像傳感器；負責采集嗅覺信息的氣體傳感器、酸堿值傳感器、化學需氧量傳感器等；采集物理運動信息方面有震動傳感器、速度 /加速度傳感器、方向傳感器等。隨著微型傳感器價格 的不斷下降，以及相關技術的逐漸成熟，相信不久的將來無線傳感器網絡在民用領域會有更大的應用前景。 1.2 無線傳感器網絡定位技術 1.2.1 現有定位