Research on the System of Mine Intelligent Positioning

Author:

Ma Hongmei,Xue Weining

Funder

Central University Basic Research Operating Funding Project

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Reference12 articles.

1. Huang, Y., Zhang, S., Jing, Y., et al. (2017). Non-line of sight localization algorithm based on TDOA and RSS by feasible region particle filter. Control and Decision, 32(8), 1415–1420.

2. Li, K., Huang, Z., Cheng, Y. C., et al. (2014). A maximal figure-of-merit learning approach to maximizing mean average precision with deep neural network based classifiers. In IEEE international conference on acoustics, speech and signal processing (pp. 4503–4507). IEEE.

3. Shao, X., Li, K., & Chen, X. (2018). A method of TOA positioning for mine to effectively reduce the impact of Non-Line of sight error propagation. In Proceedings of the 30thChinese Control and Decision Conference, CCDC 2018 (pp. 4650–4655). Shenyang: Institute of Electrical and Electronics Engineers Inc.

4. Zhao, J., Zhang, X., & Zeng, L. (2012). An approach to improving the accuracy of the indoor positioning with NLOS Environment. Journal of Beijing University of Posts and Telecommunications, 35(6), 38–43.

5. Greenstein, L. J., Erceg, V., Yeh, Y. S., et al. (1997). A new path-gain/delay spread propagation model for digital cellular channels. IEEE Transactions on VT, 46(2), 477–484.

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