Paper
22 May 2013 Air route selection for improved air-to-ground situation assessment
Marc Oispuu, Massimo Sciotti, Alexander Charlish
Author Affiliations +
Abstract
Air-to-Ground Situation Assessment (SA) requires gathering information on the entities evolving on the ground (e.g., people, vehicles), and inferring the relations among them and their final intent. Several airborne sensor data might concur in the compilation of such high-level picture, which is aimed at identifying threats and promptly raising alarms. However, this process is intrinsically prone to errors: as the evidence - provided to the SA algorithm - originates from noisy sensor observations, the final outcome is also affected by uncertainty. High-level inferred variables, such as "Situation" and "Threat Level", can be seen as error-affected, incomplete estimates of the ground truth, hence they are subject to improvement by properly steering the data acquisition process. In this paper we address the problem of optimizing the air route of the sensing platform, in order to reduce the number of false declarations or the delay in threat declaration in the SA stage. Specifically, we consider the problem of detecting a hostile behavior between pairs of ground targets by exploiting track data generated from airborne bearings-only measurements. We model the optimization problem with a sequential Markov Decision Process (MDP): the platform sequentially selects the best maneuver (i.e., its acceleration vector) in order to maximize the total reward over an infinite horizon. We define the potential contribution of an action as a function of the expected environmental conditions (e.g., obscurations of the line-of-sight) and the improvement of the localization accuracy achievable for the tracked objects. We demonstrate that following the optimized trajectory the delay in the declaration of a hostile behavior between two targets is reduced at the same erroneous declaration rate.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marc Oispuu, Massimo Sciotti, and Alexander Charlish "Air route selection for improved air-to-ground situation assessment", Proc. SPIE 8742, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV, 87420M (22 May 2013); https://doi.org/10.1117/12.2015372
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Sensors

Particles

Error analysis

Detection and tracking algorithms

Target detection

Process modeling

Data processing

Back to Top