Concurrent orbit and attitude estimation using minimum sigma point unscented Kalman filter

Concurrent orbit and attitude determination (COAD) plays a key role in reducing the cost of navigation and control subsystem for small satellites. This article is devoted to the problem of the COAD of satellites. A measurement package consisting of three axis magnetometer (TAM) and a sun sensor is shown to be sufficient to estimate the attitude and orbit information. To this end, an autonomous gyro-less COAD algorithm is proposed and implemented through the centralized data fusion of the TAM and the sun sensor. The set of nonlinear-coupled roto-translation dynamics of the satellite is used with a modified unscented Kalman filter (MUKF) to estimate the full satellite states. The MUKF is specially proposed to substantially cut the run time by minimizing the number of required sigma points. The results indicate that the adopted strategy fulfills the essential requirements of accuracy and the speed of state estimation. Local observability is demonstrated and an extensive Monte Carlo simulation has shown desirable stability characteristics for the proposed algorithm. Additionally, a sensitivity analysis on the orbital elements and sensor characteristics is performed to verify the feasibility and utility of the MUKF over a wider acceptable range of sensory and operating environments.