Improved BP neural network RSSI ranging algorithm

Hui Lv

doi:10.1117/12.2656732

20 October 2022 Improved BP neural network RSSI ranging algorithm

Hui Lv

Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 124513Y (2022) https://doi.org/10.1117/12.2656732
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China

Abstract

With the construction of urbanization, large-scale commercial buildings and large-scale hubs appear in people's lives. Indoor positioning technology plays an important role in many fields. However, in complex situations, in the indoor dynamic environment, it is easy to suffer from multipath interference, and the positioning accuracy will be significantly reduced, resulting in a large error in RSSI observation. This thesis presents an improved BP neural network ranging model algorithm. Compared with the traditional logarithmic distance ranging model, the algorithm does not need to estimate the parameters, which reduces the accumulation of errors. After the BP neural network model is trained, the RSSI data is input into it, and the corresponding distance will be obtained. The experimental results show that the model established by BP neural network can reflect the effect of RSSI value attenuation with distance, which is more in line with the real situation of signal propagation in complex indoor environment. Therefore, the BP neural network proposed in this thesis can improve the ranging accuracy and reduce the error.

Citation Download Citation

Hui Lv "Improved BP neural network RSSI ranging algorithm", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 124513Y (20 October 2022); https://doi.org/10.1117/12.2656732

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