ML and Bayesian TOA location estimators for NLOS environments
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Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx5/8066/22310/01040790.pdf?arnumber=1040790
Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Single-BS Simultaneous Environment Sensing and UE Localization Without LoS Path by Exploiting Near-Field Scatterers;IEEE Communications Letters;2024-09
2. Multipath Assisted Single Base Station Positioning for NLOS Environment;2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI);2022-07-10
3. Proximity-Distance Mapping and Jaya Optimization Algorithm Based on Localization for Wireless Sensor Network;International Journal of Pattern Recognition and Artificial Intelligence;2022-04-20
4. Performance Enhancements of the Indoor Localization System Based on Dynamic ToA and RSS Mechanisms;Proceedings of International Conference on Emerging Technologies and Intelligent Systems;2021-12-03
5. Non-line-of-sight error mitigating algorithms for transmitter localization based on hybrid TOA/RSSI measurements;Wireless Networks;2020-03-05
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