@inproceedings{f42e838f84204479b33a5c79a194bef3,
title = "Characteristic Frequency Input Neural Network for Inertia Identification of Tumbling Space Target",
abstract = "A novel characteristic frequency input network (CFIN) is investigated for inertia parameters identification of the tumbling space target from the quaternion measurements based on the back propagation neural network. The main innovation of the CFIN is it set the 15-dimensional characteristic frequency vector as the input of the neural network, which is extracted from the constant parameters of the target{\textquoteright}s attitude quaternion. The utilization of the characteristic frequency not only reduces the required number of nodes to less than 100, but also improves the learning rate of the neural network. The CFIN is trained using 10000 samples and tested using another 2000 data. It can work well in real-time with very little computational burden and storage space once successfully trained. Moreover, effectiveness analysis illustrates that the CFIN can provide more precise estimation of the inertia parameters than the conventional estimation method, like extend Kalman filter and unscented Kalman filter in most case.",
keywords = "BP neural network, Characteristic frequency, Inertia identification, Tumbling space target",
author = "Chuan Ma and Jianping Yuan and Dejia Che",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 ; Conference date: 08-08-2019 Through 11-08-2019",
year = "2019",
doi = "10.1007/978-3-030-27541-9_16",
language = "英语",
isbn = "9783030275402",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "174--187",
editor = "Haibin Yu and Jinguo Liu and Lianqing Liu and Yuwang Liu and Zhaojie Ju and Dalin Zhou",
booktitle = "Intelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings",
}