X‐ray pulsar navigation using multiple detectors based on a new observation strategy

Guo, Pengbin; Sun, Jian; Xue, Jianru

doi:10.1049/iet-rsn.2017.0571

Cited by 6 publications

(2 citation statements)

References 13 publications

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“…In fact, all terms in B i should be considered seriously; thus, a simple calculation is conducted to get the magnitude of every item in Equation (3); the specific position in the orbit of the ARGOS vehicles was chosen at time = 2451538.96769266 JD, and the results were only valid for this specific location. The single source used in this analysis was the Crab Pulsar, along with its proper motion of µ α = −17 mas/year and µ δ = 7 mas/year and a distance of 2 kpc [26]. A value of ∆t n = 100 days was selected as a representation of the elapsed time between the measured D 0 and the current time [18].…”

Section: Analysis Of System Errormentioning

confidence: 99%

An Improved Augmented Algorithm for Direction Error in XPNAV

Ren

Nie

2020

Symmetry

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Recently, X-ray pulsar-based navigation (XPNAV) as a significant navigation method has been widely used in deep space exploration. However, the accuracy of XPNAV is limited to the existence of the pulsar direction error. To improve the performance of XPNAV, we have proposed a novel algorithm named “the modified augmented state extended Kalman filter” (MASEKF). The algorithm considers the high-order terms of direction error and then adds a more precise direction error into state equation and measurement equation. In the simulation, by comparing the performance of MASEKF, EKF, and ASEKF at the same time, it is found that MASEKF has better performance in the accuracy and stability, and the results also demonstrate that MASEKF algorithm has faster convergence speed. This paper provides a strong reference for other improvements of algorithms towards direction error. The purpose of this study is to establish MASEKF and add the direction error into the measurement equation and the state equation, so as to realize the coordination and symmetry of the algorithm.

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Section: Analysis Of System Errormentioning

confidence: 99%

An Improved Augmented Algorithm for Direction Error in XPNAV

Ren

Nie

2020

Symmetry

View full text Add to dashboard Cite

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“…Throughout the solar system, pulsars, which are a type of high-speed spinning neutron star, are useful in aquiring a spacecraft's alttitude, location, and time (Guo et al 2018;Sheikh & Pines 2006;Xiaolin et al 2018). Navigation using pulsars, particularly X-ray pulsar navigation (XNAV; Li et al 2018;Sheikh 2005), has become a popular autonomous navigation method.…”

Section: Introductionmentioning

confidence: 99%

Formation of a Satellite Navigation System Using X-Ray Pulsars

Zhang

Rong

et al. 2019

PASP

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The ephemeris of a pulsar is stable for a long time, which allows navigation based on pulsar orientation to be vector feasible. The formation of a satellite navigation model using the orientation vector of an X-ray pulsar signal is presented in this paper. To obtain the time difference of arrival (TDOA), a new estimation method is constructed, which can measure the photon sequence of an X-ray pulsar signal and is based on the fast Fourier transform (FFT). Next, three new observation variables are constructed. The variables are satellite phase incrementation; the angle between the satellite baseline and the pulsar direction vector; and the angle between the plane spanned by three satellite baselines and the pulsar direction vector. All three variables, along with the TDOA of the X-ray pulsar signal, are utilized to determine the orbit. The position and velocity of the satellite formations are estimated by using the adaptive divided difference filter (ADDF) to eliminate nonlinearity. Several simulation cases are designed to verify the proposed method.

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Distributed adaptive cubature information filtering for bounded noise system in wireless sensor networks

Zhang

Gao

Xia

et al. 2021

Intl J Robust & Nonlinear

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This article is concerned with the nonlinear state estimation for the multisenor networked system with uncertain bounded noise. Traditional distributed methods only pay attention to the information fusion of state estimations, but neglect the fusion of noise statistics. The difference of noise statistics among sensor nodes usually affects the precision of state estimation in wireless sensor networks, especially for the distributed state estimation. In this article, in order to improve the accuracy of noise statistic estimations, a distributed noise statistic estimator is derived based on covariance intersection criterion and modified Sage-Husa maximum posterior. Then, distributed adaptive cubature information filtering (DACIF) is founded based on weighted average consensus to obtain accurate state estimation. Two-step information fusion, including the information fusion of state estimations and noise statistics, is derived to enhance the precision of state estimations. Meanwhile, a novel weighted rule is devised based on the state and measurement innovation vectors to improve the accuracy of distribution information fusion. Next, the estimation errors of DACIF are proved to be bounded in mean square. Simulations and semisimulation experiments are conducted to verify the effectiveness of the proposed algorithm.

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X‐ray pulsar navigation using multiple detectors based on a new observation strategy

Cited by 6 publications

References 13 publications

An Improved Augmented Algorithm for Direction Error in XPNAV

An Improved Augmented Algorithm for Direction Error in XPNAV

Formation of a Satellite Navigation System Using X-Ray Pulsars

Distributed adaptive cubature information filtering for bounded noise system in wireless sensor networks

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