Paper ID | ASPS-3.4 |
Paper Title |
OPTIMAL TOA LOCALIZATION FOR MOVING SENSOR IN ASYMMETRIC NETWORK |
Authors |
Sihao Zhao, Xiao-Ping Zhang, Ryerson University, Canada; Xiaowei Cui, Mingquan Lu, Tsinghua University, China |
Session | ASPS-3: IoT |
Location | Gather.Town |
Session Time: | Thursday, 10 June, 13:00 - 13:45 |
Presentation Time: | Thursday, 10 June, 13:00 - 13:45 |
Presentation |
Poster
|
Topic |
Applied Signal Processing Systems: Signal Processing over IoT [OTH-IoT] |
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Virtual Presentation |
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Abstract |
In a localization system based-on asymmetric network, only one of the anchor nodes (ANs) transmits signal. A sensor node (SN) receives it and then transmits signal that is received by all ANs to form time-of-arrival (TOA) measurements. SN localization is achieved based-on these TOA measurements along with the known AN positions. Existing work all assumes the SN is stationary. This will cause extra localization error for a moving SN. We develop an optimal localization method based-on maximum likelihood (ML) estimator, namely ML-LOC, utilizing information on the SN velocity and clock drift, to determine the position of a moving SN. We analyze its localization error and derive the Cramér-Rao lower bound (CRLB). Results from numerical simulations verify its optimal performance. We implement a prototype hardware localization system based-on consumer level ultra-wide band (UWB) chips. Experiments using the real system are carried out. Results validate the performance of the proposed method and show its feasibility in real-world applications. |