Reference-Filter-Driven Transition Probabilities for IMM-Based Satellite Maneuver Detection
Abstract
Maneuver detection of non-cooperative satellites is an essential task of space situational awareness. The interacting multiple model (IMM) filter has been applied to detect unannounced maneuvers, but the standard IMM assumes a fixed Markov transition probability matrix (TPM) that must be tuned without knowledge of the maneuver rate of the target. To avoid this tuning, adaptive-TPM approaches update the TPM online from statistics computed inside the IMM. However, these statistics already depend on the TPM through the mixing step, and this dependence forms a feedback loop. Under the dynamics mismatch of orbit tracking, the loop can keep the maneuver probability high in the absence of a maneuver or suppress its rise when a maneuver occurs. In this paper, the TPM is driven by the normalized innovation squared (NIS) of a reference coast filter that is not mixed with the IMM, and the NIS is mapped continuously to the coast-to-maneuver transition probability. The reference-driven IMM (RD-IMM) is evaluated with four space-based optical sensors tracking a geosynchronous target. RD-IMM detects small burns that the fixed-TPM IMM fails to detect, with few false declarations in maneuver-free runs, and avoids both failures of the closed-loop adaptation. Moreover, RD-IMM reduces the position error after a small in-track burn by more than 50% compared with the single-filter approaches.
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BibTeX
@misc{han2026referencefilterdriven,
title = {{Reference-Filter-Driven Transition Probabilities for IMM-Based Satellite Maneuver Detection}},
author = {Euiseok Han and Sangheon Choi and Seung-Hyun Kong},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.11242},
eprint = {2610.11242},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.11242},
}
RIS
TY - UNPB
TI - Reference-Filter-Driven Transition Probabilities for IMM-Based Satellite Maneuver Detection
AU - Euiseok Han
AU - Sangheon Choi
AU - Seung-Hyun Kong
PY - 2026
DA - 2026/10/08
PB - arXiv
DO - 10.48550/arxiv.2610.11242
UR - https://arxiv.org/abs/2610.11242
AB - Maneuver detection of non-cooperative satellites is an essential task of space situational awareness. The interacting multiple model (IMM) filter has been applied to detect unannounced maneuvers, but the standard IMM assumes a fixed Markov transition probability matrix (TPM) that must be tuned without knowledge of the maneuver rate of the target. To avoid this tuning, adaptive-TPM approaches update the TPM online from statistics computed inside the IMM. However, these statistics already depend on the TPM through the mixing step, and this dependence forms a feedback loop. Under the dynamics mismatch of orbit tracking, the loop can keep the maneuver probability high in the absence of a maneuver or suppress its rise when a maneuver occurs. In this paper, the TPM is driven by the normalized innovation squared (NIS) of a reference coast filter that is not mixed with the IMM, and the NIS is mapped continuously to the coast-to-maneuver transition probability. The reference-driven IMM (RD-IMM) is evaluated with four space-based optical sensors tracking a geosynchronous target. RD-IMM detects small burns that the fixed-TPM IMM fails to detect, with few false declarations in maneuver-free runs, and avoids both failures of the closed-loop adaptation. Moreover, RD-IMM reduces the position error after a small in-track burn by more than 50% compared with the single-filter approaches.
ER -