Kammel C, Ullmann I, Vossiek M (2023)
Publication Type: Journal article
Publication year: 2023
Book Volume: 1
Pages Range: 681-697
This paper presents a novel approach for estimating the motion parameters of noncooperative, free-floating space debris objects by assessing data from a multiple-input multiple-output radar system. The deployment of radar data renders the presented method particularly robust and reliable for use in the challenging space environment, with its frequently encountered harsh lighting conditions. The proposed algorithm initially extracts, locates, and tracks the dominant scatterers of the target by evaluating the range-Doppler diagrams derived from the radar data. Considering both the tracking results and a motion model, a cubature Kalman filter subsequently determines the rotational and translational motion parameters of the debris object, employing dual quaternions to describe its attitude and position. Thereby, the suggested method does not require prior information about the target object, such as its computer-aided design model, thus forming the basis for fully autonomous docking maneuvers and space debris removal. The algorithm was validated in a simulated space scenario and its performance simulatively assessed for small targets in the lower range of analyzability. Using an automated gimbal setup that realizes arbitrary controlled rotational movements, the proposed method was also practically tested in terms of achieved estimation errors and required convergence time. Finally, a comparison with a state-of-the-art unscented Kalman filter was performed to analyze the suitability of the chosen cubature Kalman filter approach.
APA:
Kammel, C., Ullmann, I., & Vossiek, M. (2023). Motion Parameter Estimation of Free-Floating Space Debris Objects Based on MIMO Radar. IEEE Transactions on Radar Systems, 1, 681-697. https://doi.org/10.1109/TRS.2023.3333434
MLA:
Kammel, Christoph, Ingrid Ullmann, and Martin Vossiek. "Motion Parameter Estimation of Free-Floating Space Debris Objects Based on MIMO Radar." IEEE Transactions on Radar Systems 1 (2023): 681-697.
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