Proceedings Article | 2 May 2017
KEYWORDS: Data modeling, Standards development, Computer simulations, Filtering (signal processing), Sensors, Detection and tracking algorithms, Algorithm development, Defense and security, Surveillance, Situational awareness sensors, Target detection, Astronomy, Biology, Modeling, Software development, Data fusion
The ability to detect and unambiguously follow all moving entities in a state-space is important in multiple domains both
in defence (e.g. air surveillance, maritime situational awareness, ground moving target indication) and the civil sphere
(e.g. astronomy, biology, epidemiology, dispersion modelling). However, tracking and state estimation researchers and
practitioners have difficulties recreating state-of-the-art algorithms in order to benchmark their own work. Furthermore,
system developers need to assess which algorithms meet operational requirements objectively and exhaustively rather
than intuitively or driven by personal favourites.
We have therefore commenced the development of a collaborative initiative to create an open source framework for
production, demonstration and evaluation of Tracking and State Estimation algorithms. The initiative will develop a
(MIT-licensed) software platform for researchers and practitioners to test, verify and benchmark a variety of multi-sensor
and multi-object state estimation algorithms. The initiative is supported by four defence laboratories, who will
contribute to the development effort for the framework.
The tracking and state estimation community will derive significant benefits from this work, including: access to
repositories of verified and validated tracking and state estimation algorithms, a framework for the evaluation of multiple
algorithms, standardisation of interfaces and access to challenging data sets.
Keywords: Tracking,
