https://doi.org/10.7892/boris.153156 | downloaded: 31.1.2022
Impact of accelerometer modelling and parameterization
on the BepiColombo orbit determination and gravimetry experiment
Alireza HosseiniArani 1,2,5, Stefano Bertone3,4, Daniel Arnold1, Adrian Jäggi1, Nicolas Thomas2
1 Astronomical Institute, University of Bern, Bern, Switzerland
2 Physics Institute, University of Bern, Bern, Switzerland
3 NASA Goddard Space Flight Center (GSFC), Baltimore, MD, United States
4 Center for Research and Exploration in Space Science and Technology, University of Maryland Baltimore County, Baltimore, MD, USA
5 Institute of geodesy, Leibniz University Hannover, Hannover, Germany (current affiliation)
43th COSPAR Scientific Assembly
28. Jan –04. Feb 2021 | Sydney, Australia
Introduction
Mission:
BepiColombo mission Launch: October 2018
Arrival to Mercury: Dec. 2025 MPO: Mercury planetary orbiter
Relevant on-board instruments:
ISA: Italian Spring Accelerometer
MORE: Mercury Orbiter Radio-science Experiment
Goal of the study:
Impact of accelerometer noise modelling and its parameterization on the MPO orbit determination and gravimetry experiment
Tool:
Planetary extension ofBernese GNSS software
Developed at the Astronomical institute of the University of Bern
Also used for planetary POD for GRAIL and for mission concepts at Europa
2
Model description 3
Force model:
• Mercury gravity field HGM050 d/o 50
• Sun and planets third body gravitational perturbation
• Tidal perturbations (Sun)
• Solar and planetary radiation pressure Simulation of Doppler observations:
• 2-way X-band and K-band
• White noise on the observations
• Station and planetary eclipses Simulation of accelerometer measurements:
• White and colored noise based on ISA team publications
• Random biases are added to the accelerometer measurements (constant for every two weeks)
Simulation
Parameter estimation
Assumptions:
• Error on the initial state vector of each arc
• NO knowledge of non-gravitational forces We solve for:
• Initial state vector of the arcs
• Coefficients of the gravity field
Τ𝒎𝒔𝟐
Alessi et al (2012)
Τ𝒎𝒔𝟐Τ𝒎𝒔𝟐
Model description 4
Τ𝒎𝒔𝟐 Τ𝒎𝒔𝟐Τ𝒎𝒔𝟐
5
Τ𝒎𝒔𝟐 Τ𝒎𝒔𝟐Τ𝒎𝒔𝟐
Model description 5
Accelerometer model
Alessi et al (2012)
Model verification 6
Zero test: A test for model verification
• No Doppler noise, No initial condition error
• We use the same force model in simulation and parameter estimation
• Doppler residuals are in the order of 1E-5 Hz
Doppler residuals
0 0.2 0.4 0.6 0.8 1 days
• A zero-test solution
• We use a gravity field with d/o 10 as synthetic reality as
• We use the same gravity field with d/o 10
• We use 1 month of Doppler observation
• We solve up to d/o 10
• Red: No Doppler noise, No initial error
• Green: Doppler noise , initial error
Sensitivity analysis
Recovery of the accelerometer parameters to the arc length
Results 7
0.00E+00 2.00E-09 4.00E-09 6.00E-09 8.00E-09 1.00E-08 1.20E-08 1.40E-08 1.60E-08 1.80E-08
0 2 4 6 8 10 12 14
Recovery error(m/s2 )
length of arc (days)
Recovery error of ACC biases as a function of arc length
Radial Along-track Cross-track
Factor 10 improvement with 5 days arc
Factor 50 improvement with 10 days arc Along-track direction of the ACC bias can be determined with one day arc
ACC RMS error
Using 1 day of observationUsing 15 daysof observation
Recovery of ACC biasRecovery of ACC bias
Results 8
Factor 10 improvement with 5 days arc
Factor 50 improvement with 10 days arc
0.00E+00 5.00E-09 1.00E-08 1.50E-08 2.00E-08 2.50E-08 3.00E-08 3.50E-08 4.00E-08 4.50E-08 5.00E-08
0.01 0.1
1
Recovery error (m/s2)
Doppler noise (mHz)
R S W
1.5 0.15 0.015
1E-8 1 E-9 1E-10
Accelerometer noise (m/s2)
Sensitivity analysis
Recovery of the accelerometer parameters to the Doppler and accelerometer noise
• Recovery of the gravity field, spacecraft orbit and accelerometer parameters
• At least 5 days of observation for the recovery of the ACC parameters
• Different assumptions on the accelerometer noise and bias lead different results for the recovery of the orbit and the gravity field
Results 9
Factor 10 improvement with 5 days arc
Unconstrained d/o 30 with Primary Mission data
• If the a priori field is similar/close to the real field the process is
• If a degraded field is used, accelerometer parameters must be dealt with very carefully.
• If not constrained, the ACC parameters can absorb the unmodelled dynamics and ruin the solution
• Stochastic pulses / empirical accelerations are needed to absorb the unmodelled dynamics and avoid them from going to the ACC parameters.
• One solution is to first solve for the orbit/gravity by ignoring the ACC parameters and solve for them using the recovered field
• Testing different orbit determination strategies
• Full results, including the final accuracy of the gravity/orbit recovery in different cases will be presented in the paper to be submitted
