An open source framework for tracking and state estimation ('Stone Soup')

Paul A. Thomas; Jordi Barr; Bhashyam Balaji; Kruger White

doi:10.1117/12.2266249

2 May 2017 An open source framework for tracking and state estimation ('Stone Soup')

Paul A. Thomas, Jordi Barr, Bhashyam Balaji, Kruger White

Proceedings Volume 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI; 1020008 (2017) https://doi.org/10.1117/12.2266249
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

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,

Conference Presentation

Citation Download Citation

Paul A. Thomas, Jordi Barr, Bhashyam Balaji, and Kruger White "An open source framework for tracking and state estimation ('Stone Soup')", Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 1020008 (2 May 2017); https://doi.org/10.1117/12.2266249

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