Precise orbit determination using the batch filter based on particle filtering with genetic resampling approach

Kim, Young-Rok; Park, Eunseo; Choi, Eun Jung; Park, Sang Young; Park, Chandeok; Lim, Hyung-Chul

doi:10.1016/j.asr.2014.06.001

Cited by 7 publications

(3 citation statements)

References 37 publications

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“…However, the classical Kalman filtering is only applicable to linear systems. In order to solve the estimation problem in nonlinear systems, particle filtering algorithm [13,14] is selected to improve the accuracy of observation. erefore, this paper investigates the problem of orbit estimation and error analysis of the ascent phase of the spacecraft based on passive detectors of satellites.…”

Section: Introductionmentioning

confidence: 99%

Estimation and Analysis of Powered Phase’s Orbit of the Spacecraft Based on Multiple-Point Intersection Algorithm

Wei

Fan

et al. 2022

Mathematical Problems in Engineering

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To estimate and analyze the orbit of a spacecraft in the ascent phase, three algorithms are proposed in this paper: a two-satellite point-by-point intersection positioning algorithm, single-satellite positioning algorithm, and multiple-point intersection collaborative positioning algorithm. Meanwhile, two mathematic models of the spacecraft orbit are presented based on the kinematics characteristic and the least square method. Besides, by combining the results of the proposed satellite positioning algorithms with mathematic models of the spacecraft orbit, the particle filtering based on the Monte Carlo algorithm is applied to filtering of the final results of the spacecraft. Finally, the effectiveness of the two-satellite point-by-point intersection positioning algorithm and the single-satellite positioning algorithm is verified through the experiment simulation on the real data.

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Section: Introductionmentioning

confidence: 99%

Estimation and Analysis of Powered Phase’s Orbit of the Spacecraft Based on Multiple-Point Intersection Algorithm

Wei

Fan

et al. 2022

Mathematical Problems in Engineering

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“…Although these filters could effectively alleviate the degeneracy phenomenon, they also increase the computational burden. The filters contained in the second category are proposed by modifying the resampling method, 12,13) such as regularized particle filter (RPF) and genetic resampling particle filter (GRPF). These filters, especially the GRPF, can ensure validity and effectively improve diversity.…”

Section: Introductionmentioning

confidence: 99%

Genetic Resampling Particle Filter with Randomly Delayed Measurements and Its Application to Line-of-Sight Rate Estimation

Zhang

Wang

Qin

et al. 2019

Trans. Japan Soc. Aero. S Sci.

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To deal with randomly delayed measurements and glint noise, a novel recursive filter referred as a randomly delayed genetic resampling particle filter (RD-GRPF) is proposed in this paper. By making use of Bernoulli random variables, the measurement model is modified to describe the random delay. Then, the weight update equation is reformulated based on this model. To avoid the particle degeneration and sample impoverishment that always arise in the application of a particle filter, the genetic resampling method is utilized to resample the particles. Then, the RD-GRPF is obtained. Therefore, the filter proposed not only copes with randomly delayed measurements, it also keeps the advantage of the standard particle filter, which ensures good performance in the case of non-Gaussian noise. In addition, the RD-GRPF proposed is applied to line-of-sight (LOS) rate estimation, the model for which is also presented in this paper. A simulation was conducted and the results demonstrate the superiority of the RD-GRPF.

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“…Lee & Alfriend (2007) pointed out that an inaccurate initial orbit and sparse measurements can result in unstable solutions of orbit estimation. To overcome this problem, various estimation algorithms such as unscented transformation and a particle filter have been suggested by Lee & Alfriend (2007), Park et al (2010), and Kim et al (2011Kim et al ( , 2014b. Another way to avoid sparseness is to use a short-arc estimation strategy.…”

Section: Introductionmentioning

confidence: 99%

Orbit Determination Using SLR Data for STSAT-2C: Short-arc Analysis

Kim

Park²,

Kucharski³

et al. 2015

Journal of Astronomy and Space Sciences

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Precise orbit determination using the batch filter based on particle filtering with genetic resampling approach

Cited by 7 publications

References 37 publications

Estimation and Analysis of Powered Phase’s Orbit of the Spacecraft Based on Multiple-Point Intersection Algorithm

Estimation and Analysis of Powered Phase’s Orbit of the Spacecraft Based on Multiple-Point Intersection Algorithm

Genetic Resampling Particle Filter with Randomly Delayed Measurements and Its Application to Line-of-Sight Rate Estimation

Orbit Determination Using SLR Data for STSAT-2C: Short-arc Analysis

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