简历详情

Deep Neural Network-Based Footprint Prediction and Attack Intention Inference of Hypersonic Glide Vehicles

In response to the increasing threat of hypersonic weapons, it is of great importance for the defensive side to achieve fast prediction of their feasible attack domain and online inference of their most probable targets. In this study, an online footprint prediction and attack intention inference algorithm for hypersonic glide vehicles (HGVs) is proposed by leveraging the utilization of deep neural networks (DNNs). Specifically, this study focuses on the following three contributions. First, a baseline multi-constrained entry guidance algorithm is developed based on a compound bank angle corridor, and then a dataset containing enough trajectories for the following DNN learning is generated offline by traversing different initial states and control commands. Second, DNNs are developed to learn the functional relationship between the flight state/command and the corresponding ranges; on this basis, an online footprint prediction algorithm is developed by traversing the maximum/minimum ranges and different heading angles. Due to the substitution of DNNs for multiple times of trajectory integration, the computational efficiency for footprint prediction is significantly improved to the millisecond level. Third, combined with the predicted footprint and the hidden information in historical flight data, the attack intention and most probable targets can be further inferred. Simulations are conducted through comparing with the state-of-the-art algorithms, and results demonstrate that the proposed algorithm can achieve accurate prediction for flight footprint and attack intention while possessing significant real-time advantage.

期刊: Mathematics  2022
作者: Lin Cheng,Changhong Dong,Jingjing Xu
DOI:10.3390/math11010185

Approximate time-optimal low-thrust rendezvous solutions between circular orbits

期刊: Aerospace Science and Technology  2022
作者: Hexi Baoyin,Shengping Gong,Lin Cheng,Di Wu
DOI:10.1016/j.ast.2022.108011

Real-time optimal control for irregular asteroid landings using deep neural networks

期刊: Acta Astronautica  2020
作者: Fanghua Jiang,Yu Song,Zhenbo Wang,Lin Cheng
DOI:10.1016/j.actaastro.2019.11.039

Real-Time Optimal Control for Spacecraft Orbit Transfer via Multiscale Deep Neural Networks

期刊: IEEE Transactions on Aerospace and Electronic Systems  2019
作者: Chengyang Zhou,Fanghua Jiang,Zhenbo Wang,Lin Cheng
DOI:10.1109/taes.2018.2889571