Q-method Extended Kalman Filter

نویسندگان

  • Renato Zanetti
  • Thomas Ainscough
  • John Christian
  • Pol D. Spanos
چکیده

The well-known Wahba Problem [1] is a non-linear, weighted least-squares problem that seeks to obtain the optimal attitude matrix from a set of at least two independent vector measurements. The most common technique used to solved the Wahba problem is the so-called q-method, developed by Davenport and documented in [2]. The q-method rearranges the Wahba performance index into a quadratic performance index of the attitude quaternion, which is constrained to have unit norm. The extremals of this performance index are the eigenvalues of the Davenport matrix, and the optimal quaternion is the unit eigenvector corresponding to the largest eigenvalue.

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

Tuning of Extended Kalman Filter using Self-adaptive Differential Evolution Algorithm for Sensorless Permanent Magnet Synchronous Motor Drive

In this paper, a novel method based on a combination of Extended Kalman Filter (EKF) with Self-adaptive Differential Evolution (SaDE) algorithm to estimate rotor position, speed and machine states for a Permanent Magnet Synchronous Motor (PMSM) is proposed. In the proposed method, as a first step SaDE algorithm is used to tune the noise covariance matrices of state noise and measurement noise i...

متن کامل

Time Delay and Data Dropout Compensation in Networked Control Systems Using Extended Kalman Filter

In networked control systems, time delay and data dropout can degrade the performance of the control system and even destabilize the system. In the present paper, the Extended Kalman filter is employed to compensate the effects of time delay and data dropout in feedforward and feedback paths of networked control systems. In the proposed method, the extended Kalman filter is used as an observer ...

متن کامل

A New Adaptive Extended Kalman Filter for a Class of Nonlinear Systems

This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...

متن کامل

Design of Instrumentation Sensor Networks for Non-Linear Dynamic Processes Using Extended Kalman Filter

This paper presents a methodology for design of instrumentation sensor networks in non-linear chemical plants. The method utilizes a robust extended Kalman filter approach to provide an efficient dynamic data reconciliation. A weighted objective function has been introduced to enable the designer to incorporate each individual process variable with its own operational importance. To enhance...

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

IMPLEMENTATION OF EXTENDED KALMAN FILTER TO REDUCE NON CYCLO-STATIONARY NOISE IN AERIAL GAMMA RAY SURVEY

Gamma-ray detection has an important role in the enhancement the nuclear safety and provides a proper environment for applications of nuclear radiation. To reduce the risk of exposure, aerial gamma survey is commonly used as an advantage of the distance between the detection system and the radiation sources. One of the most important issues in aerial gamma survey is the detection noise. Various...

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