Paper
2 May 2007 Simulating and testing autonomous behaviour in multiple airborne sensor systems
Author Affiliations +
Abstract
The Multiple Airborne Sensor Targeting and Evaluation Rig (MASTER) is a high fidelity simulation environment in which data fusion, tracking and sensor management algorithms developed within QinetiQ Ltd. can be demonstrated and evaluated. In this paper we report an observer trajectory planning tool that adds considerable functionality to MASTER. This planning tool can coordinate multiple sensor platforms in tracking highly manoeuvring targets. It does this by applying instantaneous thrusts to each platform, the magnitude of which is chosen to gain maximum observability of the target. We use an efficient search technique to determine the thrust that should be applied to each platform at each time step, and the planning horizon can either be one-step (greedy) or two-step. The measure of performance used in evaluating each potential sensor manoeuvre (thrust) is the posterior Cramer-Rao lower bound (PCRLB), which gives the best possible (lowest mean square error) tracking performance. We exploit a recent novel approach to approximating the PCRLB for manoeuvring target tracking (the "best-fitting Gaussian" (BFG) approach: Hernandez et al., 2005). A closed-form expression gives the BFG approximation at each sampling time. Hence, the PCRLB can be approximated with a very low computational overhead. As a result, the planning tool can be implemented as an aid to decision-making in real-time, even in this time-critical airborne domain. The functionality of MASTER enables one to access the performance of the planning tool in a range of sensor-target scenarios, enabling one to determine the minimal sensor requirement in order to satisfy mission requirements.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Moira I. Smith, Marcel L. Hernandez, and Matthew Cooper "Simulating and testing autonomous behaviour in multiple airborne sensor systems", Proc. SPIE 6561, Unmanned Systems Technology IX, 65610O (2 May 2007); https://doi.org/10.1117/12.719482
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Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Unmanned aerial vehicles

Motion models

Algorithm development

Detection and tracking algorithms

Computer simulations

Monte Carlo methods

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