Radar Cross-Section Modeling of Space Debris

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Space domain awareness (SDA) has become increasingly important as industry and society seek further interest in occupying space for surveillance, communication, and environmental services. To maintain safe launch and orbit-placement of future satellites, there is a need to reliably track the positions and trajectories of discarded launch designs that are debris objects orbiting Earth. In particular, debris with sizes on the order of 20 cm or smaller travelling at high speeds maintain enough energy to pierce and permanently damage current, functional satellites. To monitor debris, the Dynamic Data Driven Applications Systems (DDDAS) paradigm can enhance accuracy with object modeling and observational updates. This paper presents a theoretical analysis of modeling the radar returns of space debris as simulated signatures for comparison to real measurements. For radar modeling, when the incident radiation wavelength is comparable to the radius of the debris object, Mie scattering is dominant. Mie scattering describes situations where the radiation scatter propagates predominantly, i.e., contains the greatest power density, along the same direction as the incident wave. Mie scatter modeling is especially useful when tracking objects with forward scatter bistatic radar, as the transmitter, target, and receiver lie along the same geometrical trajectory. The Space Watch Observing Radar Debris Signatures (SWORDS) baseline method involves modeling the radar cross-sections (RCS) of space debris signatures in relation to the velocity and rotational motions of space debris. The results show the impact of the debris radii varying from 20 cm down to 1 cm when illuminated by radiation of comparable wavelength. The resulting scattering nominal mathematical relationships determine how debris size and motion affects the radar signature. The SWORDS method demonstrates that the RCS is proportional to linear size, and that the Doppler shift is predominantly influenced by translation motion.

Original languageEnglish (US)
Title of host publicationDynamic Data Driven Applications Systems - 4th International Conference, DDDAS 2022, Proceedings
EditorsErik Blasch, Frederica Darema, Alex Aved
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages14
ISBN (Print)9783031526695
StatePublished - 2024
Event4th International Conference on Dynamic Data Driven Applications Systems, DDDAS 2022 - Cambridge, United States
Duration: Oct 6 2022Oct 10 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13984 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th International Conference on Dynamic Data Driven Applications Systems, DDDAS 2022
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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