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7 May 2019 Stone Soup: announcement of beta release of an open-source framework for tracking and state estimation
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Abstract
Tracking and state estimation technologies are used in a variety of domains that include astronomy, air surveillance, maritime situational awareness, biology, and the internet. Algorithms for tracking and state estimation are becoming increasingly complex and it is difficult for researchers and skilled practitioners to implement and systematically evaluate these state-of-the-art algorithms. System designers also need to objectively assess the performance of algorithms against operational requirements, and tools to conveniently perform such systematic assessment have been lacking. Recognising this problem, an initiative was taken to create an open-source frame- work called Stone Soup", which would be used for the development, demonstration, and evaluation of tracking and state estimation algorithms. Stone Soup was made openly available in April 2019 as a beta version (V0.1b1). This paper introduces the Stone Soup framework and describes how users can take advantage of this framework to develop their own algorithms, set up experiments with real-world data, and evaluate algorithms.
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© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David Last, Paul Thomas, Steven Hiscocks, Jordi Barr, David Kirkland, Mamoon Rashid, Sang Bin Li, and Lyudmil Vladimirov "Stone Soup: announcement of beta release of an open-source framework for tracking and state estimation", Proc. SPIE 11018, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII, 1101807 (7 May 2019); https://doi.org/10.1117/12.2518514
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