Modified filter for mean elements estimation with state jumping

To investigate the real-time mean orbital elements(MOEs)estimation problem under the influence of state jumping caused by non-fatal spacecraft collision or protective orbit trans-fer,a modified augmented square-root unscented Kalman filter(MASUKF)is proposed.The MASUKF is composed of sigma points calculation,time update,modified state jumping detec-tion,and measurement update.Compared with the filters used in the existing literature on MOEs estimation,it has three main characteristics.Firstly,the state vector is augmented from six to nine by the added thrust acceleration terms,which makes the fil-ter additionally give the state-jumping-thrust-acceleration esti-mation.Secondly,the normalized innovation is used for state jumping detection to set detection threshold concisely and make the filter detect various state jumping with low latency.Thirdly,when sate jumping is detected,the covariance matrix inflation will be done,and then an extra time update process will be con-ducted at this time instance before measurement update.In this way,the relatively large estimation error at the detection moment can significantly decrease.Finally,typical simulations are per-formed to illustrated the effectiveness of the method.

Analytic continuation extended Kalman filter framework for perturbed orbit estimation using a network of space-based observers with anglesonly measurements

This work presents a new method for space-based angles-only orbit estimation.The approach relies on the integration of a novel and highly accurate Analytic Continuation technique with a new measurement model for multiple observers for inertial orbit estimation.Analytic Continuation computes the perturbed orbit dynamics,as well as the perturbed state transition matrix(STM),in the inertial frame.A new measurement model is developed for simultaneous measurements using a constellation of low-cost observers with monocular cameras for angles-only measurements.Analytic Continuation and the new measurement model are integrated in an Extended Kalman Filter(EKF)framework,where the Analytic Continuation method is used to propagate the perturbed dynamics and compute the perturbed STM and error covariance,with the measurements obtained via the new measurement model.Two case studies comprising small and large constellations of observers are presented,along with cases of sparse measurements and a study of the computational efficiency of the proposed approach.The results show that the new approach is capable of producing highly accurate and computationally efficient perturbed orbit estimation results compared with classical EKF implementations.

Phase Residual Estimations for PCVs of Spaceborne GPS Receiver Antenna and Their Impacts on Precise Orbit Determination of GRACE Satellites

In-flight phase center systematic errors of global positioning system（GPS） receiver antenna are the main restriction for improving the precision of precise orbit determination using dual-frequency GPS.Residual approach is one of the valid methods for in-flight calibration of GPS receiver antenna phase center variations（PCVs） from ground calibration.In this paper,followed by the correction model of spaceborne GPS receiver antenna phase center,ionosphere-free PCVs can be directly estimated by ionosphere-free carrier phase post-fit residuals of reduced dynamic orbit determination.By the data processing of gravity recovery and climate experiment（GRACE） satellites,the following conclusions are drawn.Firstly,the distributions of ionosphere-free carrier phase post-fit residuals from different periods have the similar systematic characteristics.Secondly,simulations show that the influence of phase residual estimations for ionosphere-free PCVs on orbit determination can reach the centimeter level.Finally,it is shown by in-flight data processing that phase residual estimations of current period could not only be used for the calibration for GPS receiver antenna phase center of foretime and current period,but also be used for the forecast of ionosphere-free PCVs in future period,and the accuracy of orbit determination can be well improved.

Pico-satellite Autonomous Navigation with Magnetometer and Sun Sensor Data

This article presents a near-Earth satellite orbit estimation method for pico-satellite applications with light-weight and low-power requirements. The method provides orbit information autonomously from magnetometer and sun sensor, with an extended Kalman filter （EKF）. Real-time position/velocity parameters are estimated with attitude independently from two quantities： the measured magnitude of the Earth’s magnetic field, and the measured dot product of the magnetic field vector and the sun vector. To guarantee the filter’s effectiveness, it is recommended that the sun sensor should at least have the same level of accuracy as magnetometer. Furthermore, to reduce filter’s computation expense, simplification methods in EKF’s Jacobian calculations are introduced and testified, and a polynomial model for fast magnetic field calculation is developed. With these methods, 50% of the computation expense in dynamic model propagation and 80% of the computation burden in measurement model calculation can be reduced. Tested with simulation data and compared with original magnetometer-only methods, filter achieves faster convergence and higher accuracy by 75% and 30% respectively, and the suggested simplification methods are proved to be harmless to filter’s estimation performance.