SVD-Aided EKF for Nanosatellite Attitude Estimation Based on Kinematic Relations

Nanosatellite attitude angles are estimated using vector measurements of star trackers in this chapter. As an estimation method, a nontraditional filter is used based on only the kinematics model which is propagated using rate gyro measurements. The issue related to gyro drifts is overcome by adding the bias terms into the state vector in order to estimate them. As a first stage, singular value decomposition (SVD) is used for determining the attitude measurements. As a second stage, an extended Kalman filter (EKF) is designed based on linear attitude measurements. These two stages are integrated for the whole estimation algorithm in order to have estimations with high accuracy, and it is called SVD-aided EKF.