A Framework for Robust Assimilation of Potentially Malign Third-Party Data, and its Statistical Meaning
Matthew A. Wright,
Roberto Horowitz
Abstract:This paper presents a model-based method for fusing data from multiple sensors with a hypothesis-test-based component for rejecting potentially faulty or otherwise malign data. Our framework is based on an extension of the classic particle filter algorithm for real-time state estimation of uncertain systems with nonlinear dynamics with partial and noisy observations. This extension, based on classical statistical theories, utilizes statistical tests against the system's observation model. We discuss the applic… Show more
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