Mr. Peiran Xu Profile

Peiran Xu

at Univ of New Orleans

SPIE Involvement:

Author

Publications (1)

Proceedings Article | 21 May 2011 Paper

Sensor management for collision alert in orbital object tracking

Peiran Xu, Huimin Chen, D. Charalampidis, Dan Shen, Genshe Chen, Erik Blasch, Khanh Pham

Proceedings Volume 8044, 80440E (2011) https://doi.org/10.1117/12.883632

KEYWORDS: Sensors, Satellites, Nonlinear filtering, Digital filtering, Motion models, Algorithm development, Collision avoidance, Data modeling, Picosecond phenomena, Surveillance

Read Abstract +

Given the increasingly dense environment in both low-earth orbit (LEO) and geostationary orbit (GEO), a sudden change in the trajectory of any existing resident space object (RSO) may cause potential collision damage to space assets. With a constellation of electro-optical/infrared (EO/IR) sensor platforms and ground radar surveillance systems, it is important to design optimal estimation algorithms for updating nonlinear object states and allocating sensing resources to effectively avoid collisions among many RSOs. Previous work on RSO collision avoidance often assumes that the maneuver onset time or maneuver motion of the space object is random and the sensor management approach is designed to achieve efficient average coverage of the RSOs. Few attempts have included the inference of an object's intent in the response to an RSO's orbital change. We propose a game theoretic model for sensor selection and assume the worst case intentional collision of an object's orbital change. The intentional collision results from maximal exposure of an RSO's path. The resulting sensor management scheme achieves robust and realistic collision assessment, alerts the impending collisions, and identifies early RSO orbital change with lethal maneuvers. We also consider information sharing among distributed sensors for collision alert and an object's intent identification when an orbital change has been declared. We compare our scheme with the conventional (non-game based) sensor management (SM) scheme using a LEO-to-LEO space surveillance scenario where both the observers and the unannounced and unplanned objects have complete information on the constellation of vulnerable assets. We demonstrate that, with adequate information sharing, the distributed SM method can achieve the performance close to that of centralized SM in identifying unannounced objects and making early warnings to the RSO for potential collision to ensure a proper selection of collision avoidance action.

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years