Nano Satellite Attitudes Error Estimation Using Magnetometer Data with Utilization of Kalman Filter

Abstract

This paper focus on Nano satellite attitudes (Roll angles, Pitch angles, and Yaw angles) errors estimation using Kalman Filters. The filter predicts the future estimates from on board sensors such as IMU and magnetometer. The Kalman algorithms implemented with low-cost sensor using MATLAB/SIMULINK environment. The NPSAT-1 Nano satellite attitudes estimations was performed. The Aerodynamic and solar disturbances torque considered for the simulations. The satellite on-board sensors, IMU and Magnetometer into fuze the data with low earth orbit (LEO). NPSAT-1analysis of magnetometers data from reference LEO is (0–5000) Seconds in the orbit. The process and measurement error covariance considered with six state matrices (3 angular angles, 3 angular rates). The Nano satellite Kalman algorithm results accurately estimated the attitudes angles (Roll, Yaw, Pitch) with considered inertia of the model. Finding pointing accuracy of satellite 0.1° from the final value theorem vehicle steady states.