Joint Position Localisation of Spacecraft and Debris for Autonomous Navigation Applications using Angle Measurements only

Abstract

In this paper, we consider the joint estimation of the position of a spacecraft and debris in Earth orbit to achieve spacecraft localisation based on angular measurements and precise measurements of the debris relative to the spacecraft. The dynamic model of the spacecraft caters for several perturbing effects, such as Earth and Moon gravitational field asymmetry and the Earth's oblateness effect. The Moon's position is assumed to be accurately known for the purposes of simulation from published Jet Propulsion Laboratory (JPL) ephemerides. The measurement process is based on the elevation and azimuth of the Moon and the Sun with respect to the spacecraft reference system. Range measurements are not assumed to be available. Position and velocity of the spacecraft are estimated by using the Unscented Kalman Filter (UKF). The performance of the filters are evaluated on an example of an Earth-orbiting satellite at an altitude over 1200 km with measurements of the directions of the Moon and the Sun only. It is shown that the estimates of position and velocity components track the corresponding simulated position and velocity components.

Application of the Nonlinear Tschauner-Hempel Equations to Satellite Relative Position Estimation and Control

“…A total of 13 noisy measurements are made: a pair of angles that the satellite makes with the Sun, and another pair with the Moon, the satellite's distance vector from the Earth which is assumed to be relatively very noisy or uncertain and the satellite's relative position and velocity vectors relative to the secondary orbiting body. The positions of the Sun and Moon are assumed to be known from the relevant ephemeris and obtained in the same manner as in Vepa (2017).…”

“…The basic unscented Kalman filter is identical to the filter implemented in Vepa and Amzhari (2011) and Vepa (2017) which is briefly summarised in the following.…”

A Quaternion‐Based Robust Adaptive Spherical Simplex Unscented Particle Filter for MINS/VNS/GNS Integrated Navigation System

“…Reliable and accurate estimation of location, velocity, and attitude of a dynamic vehicle is key to a number of applications, particularly to autonomous navigation of ground and air vehicles. Since the autonomous navigation has been paid growing interesting in recent years, various methods and sensory modalities have been introduced to tackle this problem [1][2][3][4][5]. As the most common sensor, the inertial measurement unit (IMU, such as accelerometers and gyroscopes) has the advantage of high frame rate, relatively small latency, and a high degree of autonomy.…”