湖南大学学报（自然科学版）2024，Vol.51Issue(8)：57-69,13.DOI:10.16339/j.cnki.hdxbzkb.2024278
GNSS拒止时基于并行CNN-BiLSTM回归和残差补偿的UAV导航误差校正方法
Method Based on Parallel CNN-BiLSTM Regression and Residual Compensation for Correcting UAV Navigation Error in GNSS Denied Environment
摘要
Abstract
When the global navigation satellite system(GNSS)signal is unavailable,the performance of GNSS/inertial navigation system(INS)integrated navigation system significantly degrades,which leads to the rapid divergence of INS errors of UAV swarms.At present,the neural network model is used to predict the position and speed instead of GNSS navigation information to correct the positioning error of the INS.However,this method suffers from high positioning errors and a sharp decline in prediction accuracy when the trajectory changes suddenly.Therefore,a position and velocity prediction method based on convolution neural networks(CNN)-bidirectional long short-term memory network(BiLSTM)joint residual compensation model is proposed to compensate for inertial navigation errors and improve position and velocity positioning accuracy.Firstly,aiming at the problem of high positioning error of GNSS/INS integrated navigation system after GNSS denial,a time series prediction network is formed by fusing CNN and BiLSTM to train and establish the relationship between inertial measurement unit(IMU)dynamics measurement and GNSS information,so as to realize position and speed prediction.Secondly,aiming at the problem that the prediction effect drops sharply when the trajectory changes abruptly,CNN-BiLSTM is used again to mine the relationship between the IMU dynamics measurement,prediction value and prediction residual,and to predict and compensate the prediction residual.Simulation results show that the proposed model outperforms traditional CNN-LSTM and LSTM network models in terms of prediction accuracy,effectiveness,and stability.关键词
全球导航卫星系统拒止/卷积神经网络/双向长短时记忆网络/残差补偿/自适应卡尔曼滤波Key words
global navigation satellite system(GNSS)denial/convolutional neural networks(CNN)/bidirec-tional long short-term memory network(BiLSTM)/residual compensation/adaptive kalman filter(AKF)分类
信息技术与安全科学引用本文复制引用
韩宾,邵一涵,罗颖,田杰,曾闵,江虹..GNSS拒止时基于并行CNN-BiLSTM回归和残差补偿的UAV导航误差校正方法[J].湖南大学学报（自然科学版）,2024,51(8):57-69,13.基金项目
国家自然科学基金资助项目(61771410),National Natural Science Foundation of China(61771410) （61771410）
四川省科技计划资助项目(2023NSFSC1373,2024NSFSC0476),Sichuan Provincial Science and Technology Plan Funded Project(2023NSFSC1373,2024NSFSC0476) （2023NSFSC1373,2024NSFSC0476）
西南科技大学博士基金项目(20zx7122,23zx7101),Doctoral Fund Project of Southwest University of Science and Technology(20zx7122,23zx7101) （20zx7122,23zx7101）
