A TOA/ AOA Location Algorithm in NLOS Environment

2009Engineering被引 6

摘要

In order to mitigate the effect of NLOS propagation, based on the Geometry Based Single- Bounced (GBSB)statistical model, a TOA/AOA location algorithm based on the RBF neural network is proposed. The fast study and non-linear approach capacity of the neural network is made use of to correct the error of NLOS propagation, then the position is calculated by Least-Square (LS) algorithm to improve the location[0] accuracy. The simulation results indicate that the location accuracy is significantly improved and the performance of this algorithm is better than that of Chan algorithm, Taylor algorithm and LS algorithm in NLOS environment.

引用本文（GB/T 7714）

Yongyi Mao, Mingyuan Li, Baojun Zhang. A TOA/ AOA Location Algorithm in NLOS Environment[J]. 未知来源, 2009.

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DOI：https://doi.org/10.3724/sp.j.1146.2007.01157

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