王林林,
李赞,
赵越
西安电子科技大学ISN国家重点实验室 ??西安 ??710071
基金项目:国家自然科学基金重点项目(61631015)，陕西省重点科技创新团队计划(2016KCT-01)，国家自然科学基金(61471395)，中央高校基础科研业务费(7215433803)
详细信息
作者简介:郝本建：男，1982年生，副教授，主要研究方向为无线通信、电磁频谱监测、无线传感器网络、信号源定位与跟踪等
王林林：女，1993年生，硕士生，研究方向为信号源定位与跟踪
李赞：女，1975年生，教授、博士生导师，主要研究方向为突发通信、数字信号处理、无线通信系统等
赵越：男，1994年生，博士生，研究方向为被动定位及信号处理
通讯作者:郝本建 bjhao@xidian.edu.cn
中图分类号:TN911.23计量
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被引次数:0
出版历程
收稿日期:2018-03-28
修回日期:2018-11-16
网络出版日期:2018-11-22
刊出日期:2019-02-01
Sensor Selection Method for TDOA Passive Localization
Benjian HAO,,Linlin WANG,
Zan LI,
Yue ZHAO
State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, China
Funds:The Key Project of National Natural Science Foundation of China (61631015), The Key Scientific and Technological Innovation Team Plan of Shaanxi Province (2016KCT-01), The National Natural Science Foundation of China (61471395), The Fundamental Research Funds for the Central Universities (7215433803)
摘要
摘要:该文主要研究一种面向到达时间差(TDOA)被动定位的定位节点选择方法。首先，通过经典的闭式解析算法将TDOA非线性方程转化为伪线性方程，并使用位置误差的协方差矩阵来度量定位精度。其次，在可用节点数量给定的条件下，在数学上将定位节点选择问题转化为最小化位置误差协方差矩阵的迹这一非凸优化问题。然后，将非凸优化问题凸松弛并化为半正定规划问题，从而快速有效地求解出最优的定位节点组合。仿真结果表明，所提节点优选方法的性能非常接近穷尽搜索方法，而且克服了穷尽搜索方法运算复杂度高、时效性差的不足，从而验证了所提方法的有效性。
关键词:到达时间差/
被动定位/
节点优选
Abstract:This paper focuses on the sensor selection optimization problem in Time Difference Of Arrival (TDOA) passive localization scenario. Firstly, the localization accuracy metric is given by the error covariance matrix of classical closed-form solution, which is introduced to convert the TDOA nonlinear equations into pseudo linear equations. Secondly, the problem of sensor selection can be mathematically transformed into the non-convex optimization problem, to minimize the trace of localization error covariance matrix under the condition that the number of active sensors is given. Then, the non-convex optimization problem is relaxed and transformed into a positive semi-definite programming problem so that the optimal subset of positioning nodes can be solved quickly and effectively. Simulation results validate that the performance of proposed sensor selection method is very close to the exhausted-search method, and overcomes the shortcomings of the high computation complexity and poor timeliness of the exhausted-search method.
Key words:Time Difference Of Arrival (TDOA)/
Passive localization/
Sensor selection optimization
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