GPS-based onboard real-time orbit determination for leo satellites using consider Kalman filter

2016 ◽  
Vol 52 (2) ◽  
pp. 769-777 ◽  
Author(s):  
Yang Yang ◽  
Xiaokui Yue ◽  
Andrew G. Dempster
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Orbit Determination ◽  
Leo Satellites

Fifth-degree strong tracking cubature Kalman filter for real-time orbit determination by multiple terminals

2017 ◽  
Vol 25 (8) ◽  
pp. 2195-2203
Author(s):  
李兆铭 LI Zhao-ming ◽  
杨文革 YANG Wen-ge ◽  
丁 丹 DING Dan ◽  
廖育荣 LIAO Yu-rong
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Orbit Determination ◽  
Cubature Kalman Filter

scholarly journals Real-Time Kinematic Precise Orbit Determination for LEO Satellites Using Zero-Differenced Ambiguity Resolution

2019 ◽  
Vol 11 (23) ◽  
pp. 2815 ◽  
Author(s):  
Xingxing Li ◽  
Jiaqi Wu ◽  
Keke Zhang ◽  
Xin Li ◽  
Yun Xiong ◽  
...  
Keyword(s):  
Real Time ◽  
Ambiguity Resolution ◽  
Orbit Determination ◽  
Precise Orbit Determination ◽  
The Real ◽  
Precise Orbit ◽  
Ambiguity Fixing ◽  
Real Time Kinematic ◽  
Leo Satellites ◽  
Fixed Solution

The rapid growing number of earth observation missions and commercial low-earth-orbit (LEO) constellation plans have provided a strong motivation to get accurate LEO satellite position and velocity information in real time. This paper is devoted to improve the real-time kinematic LEO orbits through fixing the zero-differenced (ZD) ambiguities of onboard Global Navigation Satellite System (GNSS) phase observations. In the proposed method, the real-time uncalibrated phase delays (UPDs) are estimated epoch-by-epoch via a global-distributed network to support the ZD ambiguity resolution (AR) for LEO satellites. By separating the UPDs, the ambiguities of onboard ZD GPS phase measurements recover their integer nature. Then, wide-lane (WL) and narrow-lane (NL) AR are performed epoch-by-epoch and the real-time ambiguity–fixed orbits are thus obtained. To validate the proposed method, a real-time kinematic precise orbit determination (POD), for both Sentinel-3A and Swarm-A satellites, was carried out with ambiguity–fixed and ambiguity–float solutions, respectively. The ambiguity fixing results indicate that, for both Sentinel-3A and Swarm-A, over 90% ZD ambiguities could be properly fixed with the time to first fix (TTFF) around 25–30 min. For the assessment of LEO orbits, the differences with post-processed reduced dynamic orbits and satellite laser ranging (SLR) residuals are investigated. Compared with the ambiguity–float solution, the 3D orbit difference root mean square (RMS) values reduce from 7.15 to 5.23 cm for Sentinel-3A, and from 5.29 to 4.01 cm for Swarm-A with the help of ZD AR. The SLR residuals also show notable improvements for an ambiguity–fixed solution; the standard deviation values of Sentinel-3A and Swarm-A are 4.01 and 2.78 cm, with improvements of over 20% compared with the ambiguity–float solution. In addition, the phase residuals of ambiguity–fixed solution are 0.5–1.0 mm larger than those of the ambiguity–float solution; the possible reason is that the ambiguity fixing separate integer ambiguities from unmodeled errors used to be absorbed in float ambiguities.

scholarly journals Autonomous Orbit Determination for a Hybrid Constellation

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Muzi Li ◽  
Bo Xu ◽  
Jun Sun
Keyword(s):  
Remote Sensing ◽  
Monte Carlo ◽  
Kalman Filter ◽  
Orbit Determination ◽  
Main Idea ◽  
Altimeter Data ◽  
Range Data ◽  
Leo Satellites ◽  
Autonomous Orbit Determination ◽  
Hybrid Constellation

A new orbit determination scheme targeting communication and remote sensing satellites in a hybrid constellation is investigated in this paper. We first design one such hybrid constellation with a two-layer configuration (LEO/MEO) by optimizing coverage and revisit cycle. The main idea of the scheme is to use a combination of imagery, altimeter data, and inter-satellite range data as measurements and determine orbits of the satellites in the hybrid constellation with the help of the extended Kalman filter (EKF). The performance of the new scheme is analyzed with Monte Carlo simulations. We first focus on an individual remote sensing satellite and compared the performance of orbit determination using only imagery with its counterpart using both imagery and altimeter measurements. Results show that the performance improves when imagery is used with altimeter data pointing to geometer calibration sites but declines when used with ocean altimeter data. We then expand the investigation to the whole constellation. When inter-satellite range data is added, orbits of all the satellites in the hybrid constellation can be autonomously determined. We find that the combination of inter-satellite range data with remote sensing observations lead to a further improvement in orbit determination precision for LEO satellites. Our results also show that the performance of the scheme would be affected when remote sensing observations on certain satellites are absent.

How can Thermospheric Neutral Density (TND) estimates from CHAMP and GRACE accelerometer observations be used to improve empirical models?

2020 ◽  
Author(s):  
Ehsan Forootan ◽  
Saeed Farzaneh ◽  
Mona Kosary ◽  
Maike Schumacher
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Orbit Determination ◽  
Ensemble Kalman Filter ◽  
Precise Orbit Determination ◽  
Accurate Estimation ◽  
Neutral Density ◽  
Square Root ◽  
Precise Orbit ◽  
Leo Satellites

<p>An accurate estimation of the Thermospheric Neutral Density (TND) is important to compute drag forces acting on Low-Earth-Orbit (LEO) satellites and debris. Empirical thermospheric models are often used to compute TNDs (along-track of LEO satellites) for the Precise Orbit Determination (POD) experiments. However, recent studies indicate that the TNDs of available models do not perfectly reproduce TNDs derived from accelerometer observations. In this study, we use TND estimates from the Challenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE) missions and merge them with the NRLMSISE00 from the Mass Spectrometer and Incoherent Scatter family. The integration is implemented by applying a simultaneous Calibration and Data Assimilation (C/DA) technique. The application of C/DA is advantageous since it uses model equation to interpolate and extrapolate TNDs that are not covered by CHAMP and GRACE. It also modifies the model's selected parameters to simulate TNDs that are closer to those of CHAMP and GRACE. The C/DA of this study is implemented daily using CHAMP- and/or GRACE-TNDs, while using the Ensemble Kalman Filter (EnKF) and Ensemble Square-Root Kalman Filter (EnSRF) as merger. Compared to the original model, on average, we found 27% (in the range of 2% to 56%) improvements in the estimation of TNDs. In addition, the results of the C/DA are compared with the TND outputs of the JB2008 model along the CHAMP and GRACE orbits, whose results indicate that the daily C/DA outputs are 60% closer to the observed TNDs (that are not used for the C/DA). Overall, our assessment indicates that EnSRF results in more realistic TND simulation and prediction compared to those derived from EnKF. We show that the improved TND estimates of this study will be beneficial for Precise Orbit Determination (POD) studies.  </p><p><strong>Keywords: </strong>Thermosphere, Calibration and Data Assimilation (C/DA), NRLMSISE00, Ensemble Kalman Filter (EnKF), Ensemble Square-Root Kalman Filter (EnSRF)</p>

scholarly journals A Novel Fifth-Degree Cubature Kalman Filter for Real-Time Orbit Determination by Radar

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Zhaoming Li ◽  
Wenge Yang ◽  
Dan Ding ◽  
Yurong Liao
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Orbit Determination ◽  
Nonlinear Function ◽  
State Equation ◽  
Bayesian Filtering ◽  
Measurement Equation ◽  
J2 Perturbation ◽  
Cubature Kalman Filter ◽  
Weighted Integral

A novel fifth-degree cubature Kalman filter is proposed to improve the accuracy of real-time orbit determination by ground-based radar. A fully symmetric cubature rule, approaching the Gaussian weighted integral of a nonlinear function in general form, is introduced, and the specific points and weights are calculated by matching the monomials of degree not greater than five with the exact values. On the basis of the above rule, a novel fifth-degree cubature Kalman filter, which can achieve a higher accuracy than UKF and CKF, is derived under the Bayesian filtering framework. Then, to describe the nonlinear system more accurately, the orbital dynamics equation with J2 perturbation is used as the state equation, and the nonlinear relationship between the radar measurement elements and orbital states is built as the measurement equation. The simulation results show that, compared with the traditional third-degree algorithm, the proposed fifth-degree algorithm has a higher accuracy of orbit determination.

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