Momentum Transfer Events: Detection and Analysis in LRI Data

The GRACE-FO mission is equipped with two ranging instruments, namely a laser ranging interferometer (LRI) and a microwave instrument (MWI), which are used to measure the distance variations between the two spacecraft (GF1 and GF2). Despite the LRI's role as a technology demonstrator in the current mission, the successor mission, GRACE-C, will exclusively utilise the LRI due to its nanometre-level accuracy in range measurements.

As a consequence of the high level of accuracy achieved, many more features can be observed at high frequencies compared to the MWI range. The range variations have, in general, a gravitational signal, which rolls off quickly above 10 mHz, and non-gravitational signals stemming from atmospheric drag and thruster firings. However, additional spontaneous and sudden range changes are observed (above the gravity-signal band) in LRI and the accelerometer, which we have designated as 'momentum transfer event' (MTE) candidates. When such events turn out to transfer considerable momentum (confirmed MTE), we attribute them to external factors, such as impacts by meteoroids or space debris. However, some events seem to produce no net Δv change but are like vibrations that we attribute to internal structural changes, as previously observed in the GRACE mission (Nadir radiator foil, Kornfeld et al., 2019).

The raw ranging phase, φ_LRI, is utilised to detect the MTE candidates, from which the range and range acceleration are calculated. A filter has been constructed using the algorithm created by Bähre (2023) in order to facilitate the calculation of the precise change in range rate (Δv_LRI). By applying a specific threshold to the Δv_LRI data, it is possible to identify instances where momentum transfer or vibrations could have occurred between each spacecraft. Moreover, the correlation between the range accelerations of these events and the change in momentum recorded by the accelerometer (ACC) data is analysed. This process detected over 150 events per satellite between June 2018 and July 2023.

In order to improve the detection algorithm, the filter is characterised by simulating different event types while varying the filter parameters. This parametric study facilitated the selection of optimal filter parameters that enable effective detection and accurate Δv estimation.  

We then apply the filter to GRACE-FO LRI data, classify the detected events in LRI data according to their correlation with accelerometer data, and present the event statistics. Subsequently, the classifications are examined to ascertain whether the events occur when specific surfaces of the satellite are illuminated by the sun.

As was the case with the effects identified in GRACE data, which informed the development of GRACE-FO, detecting and analysing the effects observed in LRI data are essential for understanding their underlying causes and preventing their recurrence in future missions like GRACE-C and NGGM.