Paper
7 May 2010 Space object tracking with delayed measurements
Author Affiliations +
Abstract
This paper is concerned with the nonlinear filtering problem for tracking a space object with possibly delayed measurements. In a distributed dynamic sensing environment, due to limited communication bandwidth and long distances between the earth and the satellites, it is possible for sensor reports to be delayed when the tracking filter receives them. Such delays can be complete (the full observation vector is delayed) or partial (part of the observation vector is delayed), and with deterministic or random time lag. We propose an approximate approach to incorporate delayed measurements without reprocessing the old measurements at the tracking filter. We describe the optimal and suboptimal algorithms for filter update with delayed measurements in an orbital trajectory estimation problem without clutter. Then we extend the work to a single object tracking under clutter where probabilistic data association filter (PDAF) is used to replace the recursive linear minimum means square error (LMMSE) filter and delayed measurements with arbitrary lags are be handled without reprocessing the old measurements. Finally, we demonstrate the proposed algorithms in realistic space object tracking scenarios using the NASA General Mission Analysis Tool (GMAT).
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huimin Chen, Dan Shen, Genshe Chen, Erik Blasch, and Khanh Pham "Space object tracking with delayed measurements", Proc. SPIE 7691, Space Missions and Technologies, 76910J (7 May 2010); https://doi.org/10.1117/12.849785
Lens.org Logo
CITATIONS
Cited by 22 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Digital filtering

Electronic filtering

Nonlinear filtering

Detection and tracking algorithms

Linear filtering

Filtering (signal processing)

Sensors

Back to Top