A Joint Particle Filter for Quaternion-Valued Alpha-Stable Signals via the Characteristic Function

Sayed Pouria Talebi, Stefan Werner, Yili Xia, Clive Cheong Took, Danilo Mandic

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Abstract

The filtering paradigm is revisited through the perspective of characteristic functions. This results in the derivation of a novel particle filtering technique for sequential estimation/tracking of quaternion-valued alpha-stable random signals. Importantly, the derived particle filter incorporates an efficient information fusion format and collaborative/distributed estimation framework to accommodate the push toward use of sensor networks. The distributed setting provides for the distribution of computational complexity among agents of a
sensor network, while allowing each agent to retain an estimate of the state. Furthermore, the quaternion-valued structure allows for the derivation of a rigorous algorithm that is advantageous when dealing with signals of a multidimensional nature commonly encountered in sensor arrays.
Original languageEnglish
Publication statusPublished - 22 Jul 2022

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