Higher-Degree Stochastic Integration Filtering

Syed Safwan Khalid; Naveed Ur Rehman; Shafayat Abrar

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arXiv · 1608.00337

Higher-Degree Stochastic Integration Filtering

Syed Safwan Khalid·Naveed Ur Rehman·Shafayat Abrar

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Abstract

We obtain a class of higher-degree stochastic integration filters (SIF) for nonlinear filtering applications. SIF are based on stochastic spherical-radial integration rules that achieve asymptotically exact evaluations of Gaussian weighted multivariate integrals found in nonlinear Bayesian filtering. The superiority of the proposed scheme is demonstrated by comparing the performance of the proposed fifth-degree SIF against a number of existing stochastic, quasi-stochastic and cubature (Kalman) filters. The proposed filter is demonstrated to outperform existing filters in all cases.

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Syed Safwan Khalid, Naveed Ur Rehman, Shafayat Abrar. 2016-08-01. Higher-Degree Stochastic Integration Filtering. https://arxiv.org/abs/1608.00337

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