Application of LSTM Neural Network in RISS/GNSS Integrated Vehicle Navigation System

Author:

Liu ZhejunORCID,Gao Yanbin,Sun Yunlong,Wang YeORCID

Publisher

Springer Nature Singapore

Reference10 articles.

1. Chu, C., Wu, J.: Application of neural network in SINS/GPS combined positioning. In: GNSS World of China, pp. 104–110 (2021). https://doi.org/10.12265/j.gnss.2020120802

2. Li, N., Guan, L., Gao, Y., Liu, Z., Wang, Y., Rong, H.: A low cost civil vehicular seamless navigation technology based on enhanced RISS/GPS between the outdoors and an underground garage. Electronics 9, 120 (2020)

3. Li, C., Gao, Y., Li, C., Jiang, L.: Analysis of positioning performance of GNSS/SINS integrated navigation module in different vehicle environments. In: Proceedings of the 12th China Satellite Navigation Conference, pp. 23–30 (2021)

4. Yan, K., Chen, B., Li, S., Zhang, Y.: An experimental study on the application modes of artificial neural networks in GNSS satellite clock error prediction. In: Proceedings of the 11th China Satellite Navigation Conference, pp. 21–30 (2020)

5. Deng, T., Yue, Y., Yang, Q., Fang, F.: High-precision positioning method for intelligent connected car based on LSTM. Comput. Eng. Design 41, 867–873 (2020)

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