Wireless-sensor-network-based target localization: A semidefinite relaxation approach with adaptive threshold correction
Wireless-sensor-network-based target localization: A semidefinite relaxation approach with adaptive threshold correction
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基于无线传感器网络的目标定位：具有自适应阈值校正的半定松弛方法
DOI：
10.1016/j.neucom.2020.04.046
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发表时间：
2020-09
期刊：
影响因子：
6
通讯作者：
Jun Zhou
中科院分区：
文献类型：
--
作者：
Xin Tian;Guoliang Wei;Licheng Wang;Jun Zhou
在基于无线传感器网络的定位环境中，无线信号的非视距传播会大大降低定位系统的性能。提出了一种新的基于半定松弛的自适应门限校正目标定位方法。首先，根据扩展卡尔曼滤波(EKF)算法的预测阶段来识别量测是否处于非视距传播。然后，根据到达时间(TOA)测量模型和接收信号强度指标(RSSI)测距方法，分别构造目标函数和约束条件。采用半定松弛方法，将原问题转化为SDP问题，得到了修正后的测量信息，从而提高了精度。此外，还提出了一种非视距传播门限的修正方法，利用该方法可以快速得到最优门限。与传统的不考虑障碍物的仿真环境不同，本文在仿真环境中设置障碍物，使之更接近工程实际。最后给出了仿真结果，验证了该方法的优越性。
In a localization environment based on wireless sensor networks, the non-line-of-sight (NLOS) propagation of wireless signal can greatly degrade the performance of the localization system. In this paper, a novel semidefinite-relaxation-based target localization method is presented by utilizing an adaptive threshold correction scheme. First, whether the measurement is in NLOS propagation is identified according to the prediction stage of extended Kalman filtering (EKF) algorithm. Then, the objective function and constraints are, respectively, constructed according to the measurement model of time of arrival (TOA) and received signal strength indicator (RSSI) ranging method. By employing the semidefinite relaxation method, the original problem is converted into the SDP problem, in which the corrected measurement information is obtained and thus the accuracy is improved. In addition, a correction method for NLOS propagation threshold is proposed by which an optimal threshold is obtained quickly. Different from the traditional simulation environment without the consideration of obstacles, in this paper, obstacles are set so as to make it closer to the engineering practice. Finally, the simulation results are given to show the superior performance of the proposed method.
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