H∞ Sub-optimal Filter for Low-cost Integrated Navigation System
نویسندگان
چکیده
منابع مشابه
Robust Integrated Navigation of a Low Cost System
Robust nonlinear integrated navigation of GPS and low cost MEMS is a hot topic of research these days. A robust filter is required to cope up with the problem of unpredictable discontinuities and colored noises associated with low cost sensors. H∞ filter is previously used in Extended Kalman filter and Unscented Kalman filter frame. Unscented Kalman filter has a problem of Cholesky matrix facto...
متن کاملOn-Line Smoothing for an Integrated Navigation System with Low-Cost MEMS Inertial Sensors
The integration of the Inertial Navigation System (INS) and the Global Positioning System (GPS) is widely applied to seamlessly determine the time-variable position and orientation parameters of a system for navigation and mobile mapping applications. For optimal data fusion, the Kalman filter (KF) is often used for real-time applications. Backward smoothing is considered an optimal post-proces...
متن کاملCalibration of a Low Cost Mems Ins Sensor for an Integrated Navigation System
The method, the procedure and the results of the calibration of a low cost MEMS INS sensor are described and discussed. The reduced cost of the MEMSs sensors is very advantageous, but these sensors are characterized by much large errors. The accurate calibration of the sensors is very important for the determination of the systematic errors, like bias, scale factor and misalignment of the axes....
متن کاملAutonomous Navigation System Using a Fuzzy Adaptive Nonlinear H∞ Filter
Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlin...
متن کاملA Low Cost Ins/gps Navigation System Integrated with a Multilayer Feed Forward Neural Network
This article investigates the use of a multilayer feedforward artificial neural network into a GPS integrated low cost inertial navigation system based on MEMS sensors. The neural network is applied as an alternative of integration technique, with the purpose of providing better navigation solutions, during the lack of information in GPS outages portions of time. An input-output neural network ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Chinese Journal of Aeronautics
سال: 2004
ISSN: 1000-9361
DOI: 10.1016/s1000-9361(11)60237-9