Abstract
The uncontrolled growth of space debris around the Earth is forcing satellites to increasingly disrupt their operations in order to prevent potentially catastrophic collisions. Currently, decisions on avoidance maneuvers are made using tracking data mainly obtained through ground-based sensors. As the uncertainties in these data largely affect maneuvering rates, solutions are needed to obtain higher quality observations and therefore decrease the rate of unnecessary maneuvers. This paper studies the possibility of enabling satellites to make autonomous observations of space objects at risk of collision by using onboard LiDAR sensors. As space-based observations do not suffer from diffractions and other problems related to the atmosphere, the proposed solution could be an effective means of obtaining more precise risk estimates. An orbital mechanics analysis of typical conjunction dynamics has been performed to derive the required sensor performance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
European Space Agency, “CREAM - ESA's Proposal for Collision Risk Estimation and Automated Mitigation”, th. rep. (2019)
Setty, S.J., et al.: SLR for space debris monitoring and analysis on requirements and achievable orbital improvements. In: 1st NEO and Debris Detection Conference (2019)
Scott, R.L., et al.: On-orbit Observations of conjuncting space objects prior to the time of closest approach. J. Astronautical Sci. 67(4) (2020)
Mamani, J., et al.: LiDAR small satellite for space debris location and attitude determination. In: Proceedings of INCAS (2019)
Socrates. CelesTrak. (Retrieved 4 July 2022). https://celestrak.com/SOCRATES/
Campiti, G., et al.: Observing opportunities of space conjuncting objects in the orbits Prior to the closest approach. In: Space Debris Risk Assessment and Mitigation Analysis Workshop, ESA/ESOC (2022)
Wirth, W.: Radar Techniques Using Array Antennas. IET (2013)
Luo, Y., et al.: A review of uncertainty propagation in orbital mechanics. Prog. Aerosp. Sci. 89, 23–39 (2017)
Brunetti, G., et al.: Chip-scaled ka-band photonic linearly chirped microwave waveform generator. Front. Phys. 10(785650) (2022)
Hayes, M.: Statistical Digital Signal Processing and Modeling, John Wiley & Sons (1996)
Balanis, C.: Antenna Theory: Analysis and Design. John Wiley & Sons (2016)
Tan, K., et al.: Modeling hemispherical refectance for natural surfaces based on terrestrial laser scanning backscattered intensity data. Opt. Express 24, 22971–22988 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Campiti, G., Tagliente, M., Brunetti, G., Armenise, M.N., Ciminelli, C. (2023). Debris Detection and Tracking Through On-Board LiDAR. In: Berta, R., De Gloria, A. (eds) Applications in Electronics Pervading Industry, Environment and Society. ApplePies 2022. Lecture Notes in Electrical Engineering, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-031-30333-3_31
Download citation
DOI: https://doi.org/10.1007/978-3-031-30333-3_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-30332-6
Online ISBN: 978-3-031-30333-3
eBook Packages: EngineeringEngineering (R0)