Mars Cruise Orbit Determination from Combined Optical Celestial Techniques and X-ray Pulsars

Abstract

The precise autonomous navigation for deep space exploration by combination of multi-source observation data is a key issue for probe control and scientific applications. In this paper, the performance of an integrated Optical Celestial Navigation (OCN) and X-ray Pulsars Autonomous Navigation (XNAV) system is investigated for the orbit of Mars Pathfinder. Firstly, OCN and XNAV single systems are realised by an Unscented Kalman Filter (UKF). Secondly, the integrated system is simulated with a Federated Kalman Filter (FKF), which can do the information fusion of the two subsystems of UKF and inherits the advantages of each subsystem. Thirdly, the performance of our system is evaluated by analysing the relationship between observation errors and navigation accuracy. The results of the simulation experiments show that the biases between the nominal and our calculated orbit are within 5 km in all three axes under complex error conditions. This accuracy is also better than current ground-based techniques.

Enhanced Kalman Filter using Noisy Input Gaussian Process Regression for Bridging GPS Outages in a POS

“…With the development of remote sensing technology, Position and Orientation Systems (POSs) are becoming a key motion compensation component, and are capturing growing attention in the high resolution airborne remote sensing field (Mostafa and Hutton, 2001; Zhang et al, 2012; Toth, 2001; Chen et al, 2011). POSs have a high integration density, and normally consist of Fibre-Optic Gyros (FOG), Inertial Measurement Units (IMU), a Global Navigation Satellite System (GNSS and a Processing Computer System (PCS) to perform Inertial Navigation System (INS)/GNSS data fusion using a Kalman Filter (KF) (Wei et al, 2013; Tan et al, 2015; Liu et al, 2017). Consequently, a POS possesses both excellent short-term accuracy provided by the INS solution and consistent long-term accuracy resulting from the GNSS (often the Global Positioning System (GPS)).…”

Observability-based Mars Autonomous Navigation Using Formation Flying Spacecraft

“…Observability analysis is inevitable in designing a system using formation flying spacecraft, because we cannot achieve satisfactory state estimation when the system is unobservable. Almost all systems are nonlinear in dynamics and nonlinear measurements are also widely exploited to realise autonomous navigation (Wang et al, 2016; Wang and Zheng, 2014; Liu et al, 2017). Considering the observability analysis methods, two approaches have been used to attack the observability of nonlinear systems (Wu et al, 2012).…”

Absolute Navigation and Positioning of Mars Rover Using Gravity-Aided Odometry

“…Mars exploration has received much attention over the last few years (Jin and Zhang, 2014). The Positioning and Navigation (PN) issues for explorers or rovers have been a research focus since the 1960s (Jin et al, 2013; Wei et al, 2013; Liu et al, 2017). Among these PN designs, the Mars Exploration Rovers (MER), Spirit and Opportunity , use several integrated PN methods that are considered state-of-the-art.…”