1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become ...1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become one of the current research hotspots in spacecraft autonomous navigation. Spacecraft face complex electromagnetic interference in orbit. The time-varying, non-Gaussian interference from internal devices and external environment can lead to measurement distortion.展开更多
This article provides a review on X-ray pulsar-based navigation(XNAV).The review starts with the basic concept of XNAV,and briefly introduces the past,present and future projects concerning XNAV.This paper focuses on ...This article provides a review on X-ray pulsar-based navigation(XNAV).The review starts with the basic concept of XNAV,and briefly introduces the past,present and future projects concerning XNAV.This paper focuses on the advances of the key techniques supporting XNAV,including the navigation pulsar database,the X-ray detection system,and the pulse time of arrival estimation.Moreover,the methods to improve the estimation performance of XNAV are reviewed.Finally,some remarks on the future development of XNAV are provided.展开更多
For nonlinear state estimation driven by non-Gaussian noise,the estimator is required to be updated iteratively.Since the iterative update approximates a linear process,it fails to capture the nonlinearity of observat...For nonlinear state estimation driven by non-Gaussian noise,the estimator is required to be updated iteratively.Since the iterative update approximates a linear process,it fails to capture the nonlinearity of observation models,and this further degrades filtering accuracy and consistency.Given the flaws of nonlinear iteration,this work incorporates a recursive strategy into generalized M-estimation rather than the iterative strategy.The proposed algorithm extends nonlinear recursion to nonlinear systems using the statistical linear regression method.The recursion allows for the gradual release of observation information and consequently enables the update to proceed along the nonlinear direction.Considering the correlated state and observation noise induced by recursions,a separately reweighting strategy is adopted to build a robust nonlinear system.Analogous to the nonlinear recursion,a robust nonlinear recursive update strategy is proposed,where the associated covariances and the observation noise statistics are updated recursively to ensure the consistency of observation noise statistics,thereby completing the nonlinear solution of the robust system.Compared with the iterative update strategies under non-Gaussian observation noise,the recursive update strategy can facilitate the estimator to achieve higher filtering accuracy,stronger robustness,and better consistency.Therefore,the proposed strategy is more suitable for the robust nonlinear filtering framework.展开更多
The ability of the monolithic satellite,satellite orbit(especially GEO),and radio resource are very limited,so the development of distributed satellite cluster network(DSCN) receives more and more worldwide attention....The ability of the monolithic satellite,satellite orbit(especially GEO),and radio resource are very limited,so the development of distributed satellite cluster network(DSCN) receives more and more worldwide attention.In this paper,DSCN is surveyed and the study status of DSCN architecture design is summarized.The formation flying of spacecrafts,reconfiguration,networking,and applied research on distributed satellite spacecraft are described in detail.The DSCN will provide a great technology innovation for space information network,satellite communications,satellite navigation,deep space exploration,and space remote sensing.In addition,this paper points out future trends of the DSCN development.展开更多
This paper presents new methods for spacecraft relative pose estimation using the Unscented Kalman Filter(UKF),taking into account non-additive process and measurement noises.A twistor model is employed to represent t...This paper presents new methods for spacecraft relative pose estimation using the Unscented Kalman Filter(UKF),taking into account non-additive process and measurement noises.A twistor model is employed to represent the spacecraft's relative 6-DOF motion of the chaser with respect to the target,expressed in the chaser body frame.The twistor model utilizes Modified Rodrigues Parameters(MRPs)to represent attitude with a minimal number of parameters,eliminating the need for the normalization constraint that exists in the quaternion-based model.Additionally,it incorporates both relative position and attitude in a single model,addressing kinematic coupling of states and simplifying the estimator design.Despite numerous existing pose estimation algorithms,many rely on the simplification of additive noise assumptions.This work enhances the robustness and improves the convergence of non-additive noise algorithms by deriving two methods to accurately approximate process and measurement noise covariance matrices for systems with non-additive noises.The first method utilizes the Stirling Interpolation Formula(SIF)to obtain equivalent process and measurement noise covariance matrices.The second method employs State Noise Compensation(SNC)to derive the equivalent process noise covariance matrix and uses SIF to compute the equivalent measurement noise covariance matrix.These methods are integrated into the UKF framework for estimating the relative pose of spacecraft in proximity operations,demonstrated through two scenarios:one with a cooperative target using Position Sensing Diodes(PSDs)and another with an uncooperative target using LiDAR for 3-D imaging.The effectiveness of these methods is validated against others in the literature through Monte Carlo simulations,showcasing their faster convergence and robust performance.展开更多
基金supported by the National Level Project of China (No. 2020-JCJQ-ZQ-059)。
文摘1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become one of the current research hotspots in spacecraft autonomous navigation. Spacecraft face complex electromagnetic interference in orbit. The time-varying, non-Gaussian interference from internal devices and external environment can lead to measurement distortion.
基金the National Natural Science Foundation of China(No.61703413)the Science and Technology Innovation Program of Hunan Province,China(No.2021RC3078).
文摘This article provides a review on X-ray pulsar-based navigation(XNAV).The review starts with the basic concept of XNAV,and briefly introduces the past,present and future projects concerning XNAV.This paper focuses on the advances of the key techniques supporting XNAV,including the navigation pulsar database,the X-ray detection system,and the pulse time of arrival estimation.Moreover,the methods to improve the estimation performance of XNAV are reviewed.Finally,some remarks on the future development of XNAV are provided.
基金co-supported by the National Natural Science Foundation of China(No.62303246,No.62103204)the China Postdoctoral Science Foundation(No.2023M731788)。
文摘For nonlinear state estimation driven by non-Gaussian noise,the estimator is required to be updated iteratively.Since the iterative update approximates a linear process,it fails to capture the nonlinearity of observation models,and this further degrades filtering accuracy and consistency.Given the flaws of nonlinear iteration,this work incorporates a recursive strategy into generalized M-estimation rather than the iterative strategy.The proposed algorithm extends nonlinear recursion to nonlinear systems using the statistical linear regression method.The recursion allows for the gradual release of observation information and consequently enables the update to proceed along the nonlinear direction.Considering the correlated state and observation noise induced by recursions,a separately reweighting strategy is adopted to build a robust nonlinear system.Analogous to the nonlinear recursion,a robust nonlinear recursive update strategy is proposed,where the associated covariances and the observation noise statistics are updated recursively to ensure the consistency of observation noise statistics,thereby completing the nonlinear solution of the robust system.Compared with the iterative update strategies under non-Gaussian observation noise,the recursive update strategy can facilitate the estimator to achieve higher filtering accuracy,stronger robustness,and better consistency.Therefore,the proposed strategy is more suitable for the robust nonlinear filtering framework.
基金National Natural Science foundations of China(Nos.61032004,91338201,and 61231011)National High Technology Research and Development Program of China(863 Program)(No.2012AA121605)
文摘The ability of the monolithic satellite,satellite orbit(especially GEO),and radio resource are very limited,so the development of distributed satellite cluster network(DSCN) receives more and more worldwide attention.In this paper,DSCN is surveyed and the study status of DSCN architecture design is summarized.The formation flying of spacecrafts,reconfiguration,networking,and applied research on distributed satellite spacecraft are described in detail.The DSCN will provide a great technology innovation for space information network,satellite communications,satellite navigation,deep space exploration,and space remote sensing.In addition,this paper points out future trends of the DSCN development.
基金the startup and UPAR grants funded by College of Engineering at United Arab Emirates University(UAEU).The grant codes are G00003527 and G00004562.
文摘This paper presents new methods for spacecraft relative pose estimation using the Unscented Kalman Filter(UKF),taking into account non-additive process and measurement noises.A twistor model is employed to represent the spacecraft's relative 6-DOF motion of the chaser with respect to the target,expressed in the chaser body frame.The twistor model utilizes Modified Rodrigues Parameters(MRPs)to represent attitude with a minimal number of parameters,eliminating the need for the normalization constraint that exists in the quaternion-based model.Additionally,it incorporates both relative position and attitude in a single model,addressing kinematic coupling of states and simplifying the estimator design.Despite numerous existing pose estimation algorithms,many rely on the simplification of additive noise assumptions.This work enhances the robustness and improves the convergence of non-additive noise algorithms by deriving two methods to accurately approximate process and measurement noise covariance matrices for systems with non-additive noises.The first method utilizes the Stirling Interpolation Formula(SIF)to obtain equivalent process and measurement noise covariance matrices.The second method employs State Noise Compensation(SNC)to derive the equivalent process noise covariance matrix and uses SIF to compute the equivalent measurement noise covariance matrix.These methods are integrated into the UKF framework for estimating the relative pose of spacecraft in proximity operations,demonstrated through two scenarios:one with a cooperative target using Position Sensing Diodes(PSDs)and another with an uncooperative target using LiDAR for 3-D imaging.The effectiveness of these methods is validated against others in the literature through Monte Carlo simulations,showcasing their faster convergence and robust performance.
