TY - JOUR
T1 - Detecting the Abnormal Attitude Variation of Space Target Through Residual Range Migration Analysis
AU - Yang, Hao
AU - Zhang, Xiongkui
AU - Wang, Junling
AU - Zhao, Lizhi
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Detecting the abnormal attitude variation (AAV) of noncooperative space targets is one of the most challenging tasks in space situational awareness. This article analyses the residual range migration (RRM), which is the uncompensated residual of the migration through resolution cells (MTRCs), to detect target's AAV. Unlike the target with known attitude variation, the RRM of the noncooperative target with AAV can be significantly larger than half of the range resolution unit, which stems from incomplete MTRC compensation because of target's unexpected attitude variation. First, this article analyzes the difference in the RRM between complete and incomplete MTRC compensation, and deduces the mathematical expression of the RRM. Second, the RRM of the space target is estimated by the generalized radon transform (GRT) fitting method, and the upper bound of the fitting error is also deduced. Then, the target's AAV detection method based on the RRM analysis is designed with a self-adaptive detection threshold. Finally, the simulations analyze the feasibility and effectiveness of the proposed method. Simulation results indicate that the accurately estimated RRM can be utilized for detecting AAV at low signal-to-noise ratio (SNR) and scatterers glinting scenarios, exhibiting a high detection rate even when the target rotates with a small angle. The comparison experiment with existing inverse synthetic aperture radar (ISAR) image-based methods demonstrates the robustness of the proposed method toward the target's initial attitudes.
AB - Detecting the abnormal attitude variation (AAV) of noncooperative space targets is one of the most challenging tasks in space situational awareness. This article analyses the residual range migration (RRM), which is the uncompensated residual of the migration through resolution cells (MTRCs), to detect target's AAV. Unlike the target with known attitude variation, the RRM of the noncooperative target with AAV can be significantly larger than half of the range resolution unit, which stems from incomplete MTRC compensation because of target's unexpected attitude variation. First, this article analyzes the difference in the RRM between complete and incomplete MTRC compensation, and deduces the mathematical expression of the RRM. Second, the RRM of the space target is estimated by the generalized radon transform (GRT) fitting method, and the upper bound of the fitting error is also deduced. Then, the target's AAV detection method based on the RRM analysis is designed with a self-adaptive detection threshold. Finally, the simulations analyze the feasibility and effectiveness of the proposed method. Simulation results indicate that the accurately estimated RRM can be utilized for detecting AAV at low signal-to-noise ratio (SNR) and scatterers glinting scenarios, exhibiting a high detection rate even when the target rotates with a small angle. The comparison experiment with existing inverse synthetic aperture radar (ISAR) image-based methods demonstrates the robustness of the proposed method toward the target's initial attitudes.
KW - Artificial satellites
KW - attitude determination
KW - generalized Radon transform (GRT)
KW - inverse synthetic aperture radar (ISAR)
KW - migration through resolution cells (MTRCs)
UR - http://www.scopus.com/inward/record.url?scp=85215373660&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2025.3529913
DO - 10.1109/TGRS.2025.3529913
M3 - Article
AN - SCOPUS:85215373660
SN - 0196-2892
VL - 63
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
M1 - 5203116
ER -