全球定位系统
估计
大地测量学
职位(财务)
计算机科学
控制理论(社会学)
遥感
实时计算
工程类
地理
电信
人工智能
控制(管理)
系统工程
财务
经济
作者
Xusheng Lei,Rui Wang,Fa Fu
出处
期刊:Measurement
[Elsevier]
日期:2022-08-01
卷期号:199: 111474-111474
被引量:2
标识
DOI:10.1016/j.measurement.2022.111474
摘要
• An INS/GPS integrated navigation solution is designed for GPS denial environments. • An adaptive-gain complementary filter is proposed for attitude estimation. • A function is introduced to suppress maneuvering acceleration under dynamics. • A position prediction method based on the improved ANFIS is proposed. • The GPS position increment rather than position error is chosen to be predicted. Aiming to improve the accuracy of navigation systems during GPS outages, this paper presents an adaptive-gain complementary filter for attitude estimation. With the introduction of the acceleration vector as the observation, system dynamic information is considered to handle the high-frequency interference caused by external acceleration. Meanwhile, this paper presents a position prediction algorithm based on fuzzy neural networks with velocity and GPS position increment as the desired outputs. A hybrid method of the Least Mean Square (LMS) and conjugate gradient method is utilized to tune the parameters. With a 160 s non-overlapping sliding window, a flight test has been done using the proposed methods during 240 s GPS outages. The results indicate that the attitude estimation algorithm (RMSE of 0.89° and 0.45° for roll and pitch angles) performed better than the Mahony algorithm, and position prediction errors are 0.93 m and 1.12 m for latitude and longitude respectively.
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