Improved Arithmetic of Two-position Fast Initial Alignment for Sins Using Unscented Kalman Filter

نویسندگان

  • Ji-zhou Lai
  • Jian Xiong
  • Jian-ye Liu
  • Bin Jiang
چکیده

An arithmetic of fast two-position initial alignment for Strapdown Inertial Navigation System (SINS) using Unscented Kalman Filter (UKF) is proposed in this paper to solve the initial alignment problems of SINS. Based on the analysis of initial alignment method of SINS, the nonlinear model for two-position attitude calculation is derived, and the two-position method is used to eliminate the constant error of inertial devices, while the errors of the inertial devices are not needed to be expanded to be states, and the amount of computation is reduced under the premise of ensuring the alignment accuracy of UKF. Furthermore, according to the characteristics of nonlinear model of two-position attitude algorithm, the UKF filter using hybrid model is designed to reduce the amount of initial alignment computation. Simulation results show that, within the nonlinear model of two-position attitude calculation, the heading angle is directly observable, and this system can improve the accuracy and speed of heading angle alignment, which satisfies the real-time requirements of UKF filter for the initial alignment of SINS.

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Estimation of LOS Rates for Target Tracking Problems using EKF and UKF Algorithms- a Comparative Study

One of the most important problem in target tracking is Line Of Sight (LOS) rate estimation for using from PN (proportional navigation) guidance law. This paper deals on estimation of position and LOS rates of target with respect to the pursuer from available noisy RF seeker and tracker measurements. Due to many important for exact estimation on tracking problems must target position and Line O...

متن کامل

Rotated Unscented Kalman Filter for Two State Nonlinear Systems

In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...

متن کامل

A Novel Scheme for DVL-Aided SINS In-Motion Alignment Using UKF Techniques

In-motion alignment of Strapdown Inertial Navigation Systems (SINS) without any geodetic-frame observations is one of the toughest challenges for Autonomous Underwater Vehicles (AUV). This paper presents a novel scheme for Doppler Velocity Log (DVL) aided SINS alignment using Unscented Kalman Filter (UKF) which allows large initial misalignments. With the proposed mechanism, a nonlinear SINS er...

متن کامل

Optimization Analysis of Adaptive UKF Filtering Algorithm in Self Alignment of SINS

In SINS, the inertial components are directly mounted on the carrier.The error can be divided into deterministic error and random drift error (dynamic error), in which, the formercan be compensated. In this case, the initial alignment of the pure static base can achieve a high accuracy. In the practical application, the dynamic error is directly reflected in the inertial device because of influ...

متن کامل

Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter

The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the...

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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012