传感技术学报
傳感技術學報
전감기술학보
Journal of Transduction Technology
2014年
8期
1088-1093
,共6页
张亚明%史浩山%刘燕%程伟%蒋毅
張亞明%史浩山%劉燕%程偉%蔣毅
장아명%사호산%류연%정위%장의
无线传感器网络%定位%最小二乘估计%抗差估计
無線傳感器網絡%定位%最小二乘估計%抗差估計
무선전감기망락%정위%최소이승고계%항차고계
wireless sensor networks%localization%least square estimation%robust estimation EEACC%6150P%7230
针对无线传感器网络在实际应用中,节点间测距结果往往含有粗差,并会严重影响未知节点坐标估计值的准确性和可靠性这一问题,引入抗差估计理论,采用IGGⅢ权因子函数,设计了一种基于抗差估计的节点定位算法。该算法能对含有不同幅度的测量误差分别采取保权、降权和淘汰等相应处理,明显提高定位精度。仿真实验表明:在无粗差的情况下,本文算法与经典最小二乘定位算法的定位效果保持了良好的等效性;在含有粗差的情况下,本文算法借助于选择的阈值,对不同的粗差采取剔除以及降权等适当处理,比经典最小二乘定位取得了更高的定位精度,保证了估计结果的无偏性,体现出良好的抗差性能。
針對無線傳感器網絡在實際應用中,節點間測距結果往往含有粗差,併會嚴重影響未知節點坐標估計值的準確性和可靠性這一問題,引入抗差估計理論,採用IGGⅢ權因子函數,設計瞭一種基于抗差估計的節點定位算法。該算法能對含有不同幅度的測量誤差分彆採取保權、降權和淘汰等相應處理,明顯提高定位精度。倣真實驗錶明:在無粗差的情況下,本文算法與經典最小二乘定位算法的定位效果保持瞭良好的等效性;在含有粗差的情況下,本文算法藉助于選擇的閾值,對不同的粗差採取剔除以及降權等適噹處理,比經典最小二乘定位取得瞭更高的定位精度,保證瞭估計結果的無偏性,體現齣良好的抗差性能。
침대무선전감기망락재실제응용중,절점간측거결과왕왕함유조차,병회엄중영향미지절점좌표고계치적준학성화가고성저일문제,인입항차고계이론,채용IGGⅢ권인자함수,설계료일충기우항차고계적절점정위산법。해산법능대함유불동폭도적측량오차분별채취보권、강권화도태등상응처리,명현제고정위정도。방진실험표명:재무조차적정황하,본문산법여경전최소이승정위산법적정위효과보지료량호적등효성;재함유조차적정황하,본문산법차조우선택적역치,대불동적조차채취척제이급강권등괄당처리,비경전최소이승정위취득료경고적정위정도,보증료고계결과적무편성,체현출량호적항차성능。
In practical applications,the ranging distance between sensor nodes in wireless sensor networks( WSNs) usually contain gross error. It will seriously affect the accuracy and reliability of localization result. We introduce differential robust estimation theory,use the IGGⅢ weight factor function,and design a robust estimation based localization algorithm. The proposed algorithm can handle the different measurement data contains different amplitude error properly,and get more accurate positioning results.The simulation results show that,the localization results estimated by the proposed algorithm and that estimated by the traditional least-squares( LS) algorithm keep a good equivalence when there is no gross error in the ranging distance;and when the ranging distance contain gross error,by means of choosing threshold,the proposed algorithm achieve higher accuracy than traditional LS algorithm,and show robust property for parameter estimation.