Inertial-Based Integration With Transformed INS Mechanization in Earth Frame

نویسندگان

چکیده

This article proposes to use a newly derived transformed inertial navigation system (INS) mechanization fuse INS with other complementary systems. Through formulating the attitude, velocity, and position as one group state of double direct spatial isometries $\mathbb{S}{\mathbb{E}_2}(3)$ , has proven be affine, which means that corresponding vector error model will trajectory-independent. In order make in inertial-based integration, both right left models are derived. The INS/GPS INS/Odometer integration investigated two representatives integration. Some application aspects applications presented, include how select model, initialization based covariance, feedback correction definitions. Extensive Monte Carlo simulations land vehicle experiments conducted evaluate performance models. It is shown most striking superiority using their ability handle large initial attitude misalignments, just result log-linearity property Therefore, can used so-called alignment for applications. Moreover, state-space also very preferred long-endurance due filtering consistency caused by its less dependence on global estimate.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

GPS/INS Integration for Vehicle Navigation based on INS Error Analysis in Kalman Filtering

The Global Positioning System (GPS) and an Inertial Navigation System (INS) are two basic navigation systems. Due to their complementary characters in many aspects, a GPS/INS integrated navigation system has been a hot research topic in the recent decade. The Micro Electrical Mechanical Sensors (MEMS) successfully solved the problems of price, size and weight with the traditional INS. Therefore...

متن کامل

Inertial Sensor Bias Estimation in GPS/INS Integration through Nonlinear Kalman Filtering

The GPS/INS integration system estimates the navigation errors as well as internal sensor errors through the use of a Kalman filter. The tight integration processing mode uses the GPS range and range-rate measurements in a nonlinear Kalman filter. Extended Kalman filtering (EKF) has been discussed in many publications dealing with GPS/INS integration. The recently developed sigma-point Kalman f...

متن کامل

Using Allan Variance to Determine the Calibration Model of Inertial Sensors for Gps/ins Integration

In this research, Allan Variance analysis is used to identify the stochastic error sources existing in inertial sensors and to determine the corresponding noise parameters. According to the noise parameters, the power spectral density (PSD) function of the stochastic error sources can be determined. The differential equation descriptions for individual stochastic errors are then derived for two...

متن کامل

The feasibility of MEMS inertial sensors for deep integration of GPS and INS

Dr. Kedong Wang is an associate professor at the School of Astronautics, Beihang University, Beijing, P.R. China. He obtained a Ph.D. in Precision Instruments from Tsinghua University in 2003. He was a visiting researcher at the School of Surveying & Spatial Information Systems, University of New South Wales (UNSW), Sydney, Australia during 2009. His research interests include terrain-aided nav...

متن کامل

Gps/ins System Integration

In this paper, a technique for error estimation in a global positioning system and inertial navigation system (GPS/INS system) based on a low-cost inertial measurement unit (IMU) is offered. This technique is composed of Wavelet Transform (WT) and Adaptive Fuzzy System (AFS). The wavelet decomposition is used to de-noise the position and velocity components of the GPS and INS outputs. An AFS is...

متن کامل

ذخیره 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: IEEE-ASME Transactions on Mechatronics

سال: 2022

ISSN: ['1941-014X', '1083-4435']

DOI: https://doi.org/10.1109/tmech.2021.3090428