Single Station Antenna–Based Spacecraft Orbit Determination via Robust EKF against the Effect of Measurement Matrix Singularity

Sofyalı, Ahmet; Hajiyev, Chingiz

doi:10.1061/(asce)as.1943-5525.0000373

Cited by 3 publications

(5 citation statements)

References 15 publications

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“…The EKF for the estimation of spacecraft position and velocity on nonlinear antenna measurements is derived in Sofyali and Hajiyev (2015). In this work, both the equations of system and measurements are nonlinear, and the EKF estimates spacecraft’s position and velocity using direct range-azimuth-elevation measurements.…”

Section: Extended Kalman Filter For Estimation Of Satellite Position and Velocity Based On Indirect X-y-z Measurementsmentioning

confidence: 99%

“…In this work, both the equations of system and measurements are nonlinear, and the EKF estimates spacecraft’s position and velocity using direct range-azimuth-elevation measurements. Although EKF is a highly preferable method for orbit estimation of spacecraft (Crassidis and Junkins, 2004), the EKF in Sofyalı and Hajiyev (2015) has some disadvantages, especially for the highly nonlinear systems. Generally, this is caused by the mandatory linearization phase of the EKF procedure, so, by the derived Jacobian matrices.…”

Section: Extended Kalman Filter For Estimation Of Satellite Position and Velocity Based On Indirect X-y-z Measurementsmentioning

confidence: 99%

“…Calculating θ and then the transformation matrices between UEN-ECEF-ECI according to Sofyalı and Hajiyev (2015), the range components in ECI given in equation (24) can be written as a function of the range components in UEN, which is the coordinate frame of the real measurements. The resulting measurement vector seen in equation (13), which can simply be calculated by using equation (24), will be input to the EKF.…”

Section: Simulationsmentioning

confidence: 99%

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Spacecraft localization by indirect linear measurements from a single antenna

Hajiyev

Sofyalı

2018

AEAT

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Purpose The purpose of this paper is to present a two-stage approach for estimation of spacecraft’s position and velocity by indirect linear measurements from a single antenna. Design/methodology/approach In the first stage, direct nonlinear antenna measurements are transformed to linear x-y-z coordinate measurements of spacecraft’s position, and statistical characteristics of orbit determination errors are analyzed. Variances of orbit parameters’ errors are chosen as the accuracy criteria. In the second stage, the outputs of the first stage are improved by the designed Extended Kalman Filter for estimation of the spacecraft’s position and velocity on indirect linear x-y-z measurements. Findings The complex content of the measurement matrix in the conventional method causes periodic singularities in simulation results. In addition, the convergence of the filter using direct measurements is highly dependent on the initialization parameters’ values due to the nonlinear partial derivatives in the Jacobian measurement matrix. The comparison of the accuracy of both methods shows that the estimation by using indirect measurements reduces the absolute estimation errors. The simulation results show that the proposed two-stage procedure performs both with better estimation accuracy and better convergence characteristics. The method based on indirect measurements provides an unnoticeably short transient duration. Practical implications The proposed method can be recommended for satellite orbit estimation regarding its presented superiorities. Originality/value Inputting the single antenna measurements to the filter indirectly results in a quite simpler measurement matrix. As a result, the convergence of the filter is faster and estimation errors are lower.

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Section: Extended Kalman Filter For Estimation Of Satellite Position and Velocity Based On Indirect X-y-z Measurementsmentioning

confidence: 99%

Section: Extended Kalman Filter For Estimation Of Satellite Position and Velocity Based On Indirect X-y-z Measurementsmentioning

confidence: 99%

Section: Simulationsmentioning

confidence: 99%

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Spacecraft localization by indirect linear measurements from a single antenna

Hajiyev

Sofyalı

2018

AEAT

Self Cite

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“…An AOA measurement consists of two components: azimuth and elevation. A conventional approach is to model the measurements as noisy versions of the true azimuth and elevation [2][3][4][5][6], and use extended Kalman fiter (EKF) or unscented Kalman filter (UKF) that assume that the measurement noises of azimuth and elevation follow normal distributions. However, this model is problematic in a number of ways: I In this model the solid angle of measurement uncertainty is smaller close to the "pole" directions, i.e.…”

Section: Introductionmentioning

confidence: 99%

“…3) Rotations of the spherical coordinate system in which the azimuth and elevation are expressed change the measurement error model. The nonlinearity problem has been reported to result in divergence of the EKF [3].…”

Section: Introductionmentioning

confidence: 99%

3D Angle-of-Arrival Positioning Using von Mises-Fisher Distribution

Nurminen

Suomalainen

Ali-Löytty

et al. 2018

2018 21st International Conference on Information Fusion (FUSION)

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We propose modeling an angle-of-arrival (AOA) positioning measurement as a von Mises-Fisher (VMF) distributed unit vector instead of the conventional normally distributed azimuth and elevation measurements. Describing the 2dimensional AOA measurement with three numbers removes discontinuities and reduces nonlinearity at the poles of the azimuth-elevation coordinate system. Our computer simulations show that the proposed VMF measurement noise model based filters outperform the normal distribution based algorithms in accuracy in a scenario where close-to-pole measurements occur frequently.

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Orbit Determination and Thrust Estimation for Noncooperative Target Using Angle-Only Measurement

Zhang,

Shu,

Zhang

et al. 2023

Space Sci Technol

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The classical interactive multimodel (IMM) algorithm has some disadvantages in tracking a noncooperative continuous thrust maneuvering spacecraft, such as poor steady-state accuracy, difficult selection of subfilter parameters, and mismatched model jump. To address the abovementioned problems, a variable-dimensional adaptive IMM strong tracking filtering algorithm (VAIMM-STEKF) is proposed to estimate the spacecraft’s position, velocity, and maneuvering acceleration state. VAIMM-STEKF contains 2 models, model 1 and model 2, which correspond to the tracking of the spacecraft in maneuvering and nonmaneuvering situations. Model 1 estimates the position and velocity of the spacecraft to ensure tracking accuracy when no maneuver occurs. Model 2 is a strong tracking filter with an augmented state. The adaptive IMM algorithm adjusts the fixed Markov transfer matrix in real time according to the model output probability. According to the different states of the spacecraft, the corresponding model interactive fusion method, together with the strong tracking filter, is adopted to ensure fast tracking when the spacecraft state changes. This method can also adapt to continuous thrust maneuvering spacecraft with different orders of magnitude. Simulation results show that the position accuracy of VAIMM-STEKF can be improved by approximately 27% and the speed accuracy can be enhanced by approximately 17% under different levels of maneuvering acceleration compared with those of the IMM algorithm. The convergence speed of VAIMM-STEKF is also better than the IMM algorithm.

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Single Station Antenna–Based Spacecraft Orbit Determination via Robust EKF against the Effect of Measurement Matrix Singularity

Cited by 3 publications

References 15 publications

Spacecraft localization by indirect linear measurements from a single antenna

Spacecraft localization by indirect linear measurements from a single antenna

3D Angle-of-Arrival Positioning Using von Mises-Fisher Distribution

Orbit Determination and Thrust Estimation for Noncooperative Target Using Angle-Only Measurement

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