Data driven interference source localization based on train real-time onboard interference monitoring

被引：0

作者：

Ning, Ruirui ^{[1
]}

Lin, Siyu ^{[1
]}

Wang, Hongwei ^{[2
]}

Feng, Weiyang ^{[1
]}

Sun, Bin ^{[2
]}

Ding, Jianwen ^{[2
]}

Jiang, Wenyi ^{[1
]}

Zhong, Zhangdui ^{[1
]}

机构：

[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China

[2] Beijing Jiaotong Univ, Natl Res Ctr Railway Safety Assessment, Beijing 100044, Peoples R China

来源：

COMPUTER COMMUNICATIONS | 2021年 / 176卷

基金：

北京市自然科学基金; 中国国家自然科学基金;

关键词：

Railway mobile communication; Interference localization; Data driven; ALGORITHM;

D O I：

10.1016/j.comcom.2021.05.021

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Interference is an important factor affecting railway mobile communications, which leads to deterioration of communication quality. In serious cases, the link connection interruption will lead to degraded operation of train control system, then affect the operation efficiency of the railway system. In order to reduce the impact of interference on railway communications, the interference source should be localized and eliminated timely. However, the traditional interference localization methods require auxiliary equipment to be arranged along the track. In this paper, a data driven interference source localization method based on train real-time onboard interference monitoring is proposed, which can reduce the interference localization cost. Based on the collected Received Signal Strength (RSS) of interference signal, the particle filter principle is used to locate the target interference source combined with the data driven path-loss models. Besides, the modified whale optimization algorithm (MWOA) is introduced to further improve the positioning accuracy. The simulation and experiment results show that the proposed data driven interference source localization method outperforms the traditional localization method, and the positioning accuracy is improved from tens of meters degree to meters degree, which can meet the requirements of engineering practice to find the interference source.

引用

页码：56 / 65

页数：10

共 20 条

[11] The Whale Optimization Algorithm [J].

Mirjalili, Seyedali ;

Lewis, Andrew .

ADVANCES IN ENGINEERING SOFTWARE, 2016, 95 :51-67

[12] SDP Relaxation Methods for RSS/AOA-Based Localization in Sensor Networks [J].

Qi, Hengnian ;

Mo, Lufeng ;

Wu, Xiaoping .

IEEE ACCESS, 2020, 8 :55113-55124

[13] On the Joint Estimation of the RSS-Based Location and Path-loss Exponent [J].

Salman, Naveed ;

Ghogho, Mounir ;

Kemp, Andrew H. .

IEEE WIRELESS COMMUNICATIONS LETTERS, 2012, 1 (01) :34-37

[14] Least Squared Relative Error Estimator for RSS Based Localization With Unknown Transmit Power [J].

Shi, Jiong ;

Wang, Gang ;

Jin, Liping .

IEEE SIGNAL PROCESSING LETTERS, 2020, 27 :1165-1169

[15] Approximate Analytic Quadratic-Optimization Solution for TDOA-Based Passive Multi-Satellite Localization With Earth Constraint [J].

Shu, Feng ;

Yang, Shuping ;

Qin, Yaolu ;

Li, Jun .

IEEE ACCESS, 2016, 4 :9283-9292

[16] Semidefinite Programming for NLOS Error Mitigation in TDOA Localization [J].

Su, Zhenqiang ;

Shao, Genfu ;

Liu, Huaping .

IEEE COMMUNICATIONS LETTERS, 2018, 22 (07) :1430-1433

[17] Eigenspace Solution for AOA Localization in Modified Polar Representation [J].

Sun, Yimao ;

Ho, K. C. ;

Wan, Qun .

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2020, 68 :2256-2271

[18] A Particle Filter-Based Approach for Vehicle Trajectory Reconstruction Using Sparse Probe Data [J].

Wei, Lei ;

Wang, Yunpeng ;

Chen, Peng .

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 22 (05) :2878-2890

[19] Big Data Driven Vessel Trajectory and Navigating State Prediction With Adaptive Learning, Motion Modeling and Particle Filtering Techniques [J].

Xiao, Zhe ;

Fu, Xiuju ;

Zhang, Liye ;

Zhang, Wanbing ;

Liu, Ryan Wen ;

Liu, Zhao ;

Goh, Rick Siow Mong .

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (04) :3696-3709

[20] A Novel Trilateration Algorithm for RSSI-Based Indoor Localization [J].

Yang, Bo ;

Guo, Luyao ;

Guo, Ruijie ;

Zhao, Miaomiao ;

Zhao, Tiantian .

IEEE SENSORS JOURNAL, 2020, 20 (14) :8164-8172

← 1 2 →