X-ray Pulsar Navigation Model and Algorithm Based on Kalman Filte

Abstract

It is a issue technology to establish the X-ray Pulsar-based Navigation (XPNAV) system model and select the effective algorithm in the field of navigation and positioning research. Extended Kalman Filtering (EKF) applied to the navigation system exist the shortcomings of low precision, poor real-time per-formance. It can't get the optimal the state estimate of the navigation system and even divergence when the noise covariance and model parameters are not exact. In this paper, authors establish the XPNAV model and propose to apply the Strong Tracking Extended Kalman Filter (STEKF) into the navigation orbit precision estimate, and contrast experiments results with EKF calculation. The simulation results show that STEKF convergence speed and the filtering precision is better than EKF and has higher estimation precision, because STEKF does not require a precise priori statistical of random noise in navigation system, and STEKF has adaptive adjustment ability for the navigation system random noise. This Verifies STEKF is a very good filter method for balance estimation precision and computational load, and it has strong tracking ability for the navigation system state parameters. STEKF can overcome uncertainty robustness in the navigation system model and greatly shortens the navigation calculating time. STEKF is an effective algorithm to meet the requirements of the navigation accuracy.