刘云, 熊海楠. 协作定位在地下管廊监控中的优化研究[J]. 云南大学学报(自然科学版), 2017, 39(4): 559-564. doi: 10.7540/j.ynu.20160279
引用本文: 刘云, 熊海楠. 协作定位在地下管廊监控中的优化研究[J]. 云南大学学报(自然科学版), 2017, 39(4): 559-564. doi: 10.7540/j.ynu.20160279
LIU Yun, XIONG Hai-nan. Optimization research on cooperative localization in underground pipe gallery monitoring[J]. Journal of Yunnan University: Natural Sciences Edition, 2017, 39(4): 559-564. DOI: 10.7540/j.ynu.20160279
Citation: LIU Yun, XIONG Hai-nan. Optimization research on cooperative localization in underground pipe gallery monitoring[J]. Journal of Yunnan University: Natural Sciences Edition, 2017, 39(4): 559-564. DOI: 10.7540/j.ynu.20160279

协作定位在地下管廊监控中的优化研究

Optimization research on cooperative localization in underground pipe gallery monitoring

  • 摘要: 地下管廊是一种半封闭的窄长空间,其内情况复杂多变,由于非视距情况的出现,导致传感器节点定位困难、精度不高.针对地下管廊的多径干扰等特性,提出了最小二乘非凸估计算法(LSNCE).首先结合接收信号强度(RSSI)和到达角度信息(AOA),使用最小二乘法求出未知节点的位置估计.然后引入未知节点的辅助变量X及辅助向量z,通过应用半定规划松弛技术将位置估计转化为凸性,并得出上镜图(Epigraph)变量,再使用CVX工具箱(Matlab中包含)求出位置估计的最优解,即得到未知节点的最终位置.通过仿真验证,对比常规的选择混合加权算法(SHWA)和二次加权最小二乘算法(SWLS),最小二乘非凸估计算法能够有效地提高定位精度,同时表现出了良好的抗干扰能力.

     

    Abstract: Underground pipe rack,which is complex and changeable,is a semi-enclosed narrow space.Due to the emergence of non-line-of-sight situation,the sensor node positioning is very difficult,and the accuracy is not good. In view of the special situation of the underground pipe rack,like the multipath interference,this paper proposes the least squares non-convex estimation (LSNCE )algorithm.Combined the received signal strength(RSSI) and angle-of-arrival(AOA) information,we obtain the position estimation of the unknown node by using the least squares method.And then,we first introduce an auxiliary variable X and an auxiliary vector z of the unknown node.By applying the semidefinite programming relaxation technique,the position estimation is transformed into convexity,and we also obtained an Epigraph variable.Then,the optimal solution of the position estimation is obtained by using the CVX toolbox (included in Matlab),That is,the final location of the unknown node.Through the simulation,compared with conventional SHWA and SWLS algorithm,LSNCE algorithm can effectively improve the positioning accuracy,at the same time shows the good anti-jamming ability.

     

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