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      傳感網(wǎng)中不規(guī)則復(fù)雜3D平面定位策略研究

      2015-09-06 00:44李澤軍等

      李澤軍等

      摘要:針對(duì)具有障礙物的復(fù)雜3D平面定位誤差大以及能耗高的問(wèn)題,如何進(jìn)行未知節(jié)點(diǎn)的定位,提出了一種具有障礙物的不規(guī)則復(fù)雜3D平面定位策略,該策略將復(fù)雜三維平面劃分為水平邏輯層并標(biāo)記節(jié)點(diǎn)的所屬層,然后在具有障礙物的水平層進(jìn)行子區(qū)域的劃分及合并,最后利用大氣壓傳感器測(cè)距進(jìn)行計(jì)算未知節(jié)點(diǎn)的坐標(biāo)從而得到3D復(fù)雜平面的定位.通過(guò)與最新SV定位機(jī)制及COLA定位機(jī)制在定位誤差及能耗進(jìn)行綜合仿真實(shí)驗(yàn)對(duì)比,本文的定位策略3DCCD平均定位誤差比SV少了5%,比COLA的平均定位誤差少8%以上,定位精度上比SV和COLA提高了6.5%以上,及在能耗上比SV和COLA減少了2.7%左右.因此該定位策略(3DCCD)在解決復(fù)雜不規(guī)則圖形的不確定節(jié)點(diǎn)具有較大的優(yōu)越性.

      關(guān)鍵詞:定位誤差;邏輯層;子區(qū)域;定位機(jī)制

      中圖分類號(hào):TP39 文獻(xiàn)標(biāo)識(shí)碼:A

      The Study of Positioning Strategy of Irregular 3D Plane

      in Sensor Networks

      LI Zejun1,2, CHEN Min1,2

      (1.College of Information Science and Engineering, Hunan Univ,Changsha, Hunan 410082, China;

      2.School of Computer and Information Science,Hunan Institute of Technology,Hengyang , Hunan412002,China)

      Abstract:Considering the large positioning error and high energy consumption concerning irregular and complex 3D plane with obstacles, this paper put forward a new strategy to locate the unknown nodes. This policy divides the complex threedimensional plane into different logic layers and labels each layer node it belongs to. Then, subregions are divided and merged in horizontal layers. Finally, the positioning of 3D complex plane is possible by calculating the location coordinate of unknown nodes after atmospheric pressure sensor ranging. Compared with SV and COLA, the 3DCCD positioning strategy in the average positioning error is 5% less than SV and 8% less than COLA. Its positioning precision increases more than 6.5%, and the energy consumption reduces 2.7% than SV and COLA. The 3DCCD has great advantages in terms of positioning error, accuracy and energy.

      Key words:positioning error;logic layer;subdomain ;positioning mechanism

      復(fù)雜環(huán)境下的定位機(jī)制大多數(shù)都是基于2D網(wǎng)絡(luò)拓?fù)洵h(huán)境,導(dǎo)致節(jié)點(diǎn)路徑估算產(chǎn)生較大的誤差以及誤差難以控制、傳感器節(jié)點(diǎn)能耗大等諸多因素.如:ACDL經(jīng)典方法采用2D定位機(jī)制解決復(fù)雜網(wǎng)絡(luò)定位問(wèn)題,該方法設(shè)定一臨界點(diǎn),傳感器節(jié)點(diǎn)利用鄰居節(jié)點(diǎn)的通信來(lái)判定凹凸表面,并將復(fù)雜表面劃分為幾個(gè)子區(qū)域,節(jié)點(diǎn)通過(guò)MDS建立節(jié)點(diǎn)的相對(duì)位置.最后利用相對(duì)位置建立全局2D平面圖.這樣方法過(guò)度臨界值的選擇,當(dāng)復(fù)雜不平表面無(wú)臨界值時(shí),該策略將導(dǎo)致失敗,另外該定位方法對(duì)邊界噪音比較敏感.目前,學(xué)者們嘗試從2D平面擴(kuò)展到3D平面,其主要采用的定位方法有兩種,一是通過(guò)將3D復(fù)雜平面映射到2D平面來(lái)定位其坐標(biāo)[1,2].二是采用特殊裝置來(lái)測(cè)量凹凸平面的高度值和拋錨節(jié)點(diǎn)的距離[3].上述方法對(duì)于簡(jiǎn)單的3D表面定位具有較高的精確度,但對(duì)于復(fù)雜表面以及具有較大凸高時(shí),其定位誤差明顯增大和定位不明確.而SV(SingleValue)根據(jù)不同節(jié)點(diǎn)映射到不同2D平面上且平面的點(diǎn)具有唯一性.然后根據(jù)二維平面來(lái)定位三維平面.一定程度上解決了較簡(jiǎn)單的3D平面節(jié)點(diǎn)重疊問(wèn)題[4].但SV的代價(jià)較高,對(duì)于不規(guī)則三維平面也將導(dǎo)致節(jié)點(diǎn)重疊現(xiàn)象.COLA定位機(jī)制[5]采用移動(dòng)錨節(jié)點(diǎn)來(lái)定位三維平面,該方法的精確度較高,但對(duì)于復(fù)雜3D的平面,由于錨節(jié)點(diǎn)的不斷移動(dòng)產(chǎn)生大量的誤差值,難以適用大規(guī)模3D平面定位.

      3.3合并子區(qū)域及構(gòu)建層區(qū)域

      在進(jìn)行子區(qū)域的建立時(shí)采用廣播的方式進(jìn)行信息傳遞,導(dǎo)致在層區(qū)域內(nèi)形成若干個(gè)子區(qū)域并且子區(qū)域可能產(chǎn)生重疊現(xiàn)象.若節(jié)點(diǎn)p接收多個(gè)構(gòu)建子區(qū)域信息時(shí),以第一時(shí)間收到的信息作為標(biāo)記加入到該子區(qū)域中,其余消息將被丟棄.否則若子區(qū)域標(biāo)記不相同則合并兩個(gè)子區(qū)域直到合并消息不存在.

      復(fù)雜凹凸平面的分解與子區(qū)域的合并算法描述如下:

      4復(fù)雜平面定位與計(jì)算

      在復(fù)雜3D平面定位計(jì)算中主要考慮模型構(gòu)建差生的誤差以及定位方法和過(guò)程.傳感器節(jié)點(diǎn)在進(jìn)行通信時(shí)其物理層的傳播模式可以任意,其公式為[7,8]:

      圖11表示3DCCD算法的開(kāi)銷在不同測(cè)量誤差時(shí)都要比SV及COLA算法的開(kāi)銷要小,這是由于3DCCD采用的迭代次數(shù)少的緣故.

      6結(jié)束語(yǔ)

      本文研究復(fù)雜3D平面的定位機(jī)制,該策略首先將復(fù)雜三維平面進(jìn)行邏輯水平分層,然后在水平層進(jìn)行子區(qū)域的劃分及合并處理,最后用大氣壓傳感器測(cè)距進(jìn)行計(jì)算未知節(jié)點(diǎn)的坐標(biāo)從而得到3D復(fù)雜平面的定位.該思路為不規(guī)則復(fù)雜三維平面提供了新的思路.該策略尤其適用于不確定節(jié)點(diǎn)的定位.

      參考文獻(xiàn)

      ZHAO Y,WU H,JIN M,et al.Localization in 3D surface sensor networks: Challenges and solutions[C]//The 31st Annual IEEE International Conference on Computer Communications (IEEE INFOCOM 2012).Orlando, Florida,USA,2012:55-63.

      〖LL〗[2]LIU Q,REN P,ZHOU Z. Threedimensional accurate positioning algorithm based on wireless sensor networks[J].Journal of Computers, 2011, 6(12): 2582-2589.

      [3]LIU C,JIANG H,ZENG L D.Unitary matrix pencil algorithm for rangebased 3d localization of wireless sensor network nodes[J]. Journal of Networks, 2012, 7(9):1384-1390.

      [4]趙德鑫,李婷,黃芝平,等.無(wú)人潛航器舷側(cè)陣聲吶匹配場(chǎng)被動(dòng)定位方法研究[J].湖南大學(xué)學(xué)報(bào):自然科學(xué)版,2013,40(8):76-82.

      ZHAO Dexin,LI Ting,HUANG Zhiping,et al.Matchedfield source localization using the flank array of unmanned under water vehicle[J].Journal of Hunan University:Natural Sciences, 2013,40(8):76-82. (In Chinese)

      [5]STOLERU R,HE T,MATHIHARAN S S,et al.Asymmetric eventdriven node localization in wireless sensor networks[J]. Parallel and Distributed Systems, IEEE Transactions on, 2012,23(4): 634-642.

      [6]楊高波,吳瀟,張兆揚(yáng),等.基于過(guò)渡像素的視頻圖像文本檢測(cè)與定位[J]. 湖南大學(xué)學(xué)報(bào):自然科學(xué)版,2011,38(6):69-74.

      YANG Gaobo,WU Xiao,ZHANG Zhaoyang,et al.A transition pixels based text detection and localization for video images[J]. Journal of Hunan University:Natural Sciences, 2011,38(6):69-74.(In Chinese)

      [7]CUI H,WANG Y.Fourmobilebeacon assisted localization in threedimensional wireless sensor networks[J]. Computers & Electrical Engineering, 2012, 38(3): 652-661.

      [8]WANG R J,QIN Z G.A weighted 3D localization algorithm based on partial hopsize in wireless sensor network[J]. International Journal of Advancementsin Computing Technology,2012, 4(9): 504-513.

      [9]WANG Y,LIU Y,GUO Z.Threedimensional ocean sensor networks: A survey[J]. Journal of Ocean University of China, 2012, 11(4): 436-450.

      [10]王小平,羅軍,沈昌祥.無(wú)線傳感器網(wǎng)絡(luò)定位理論和算法[J].計(jì)算機(jī)研究與發(fā)展, 2011,48(3):353-363.

      WANG Xiaoping,LUO Jun,SHEN Changxiang. Theory and algorith mson localization in wireless sensor networks[J]. Journal of Computer Research and Development, 2011,48(3):353-363. (In Chinese)

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