The Variational Approach in Filtering and Correlated Noise

Fuente: arXiv
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Main Authors: Srinivasan, Sharan, Gupta, Vijay, Honnappa, Harsha
Format: Preprint
Published: 2026
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author Srinivasan, Sharan
Gupta, Vijay
Honnappa, Harsha
author_facet Srinivasan, Sharan
Gupta, Vijay
Honnappa, Harsha
contents The variational formulation of nonlinear filtering due to Mitter and Newton characterizes the filtering distribution as the unique minimizer of a free energy functional involving the relative entropy with respect to the prior and an expected energy. This formulation rests on an absolute continuity condition between the joint path measure and a product reference measure. We prove that this condition necessarily fails whenever the signal and observation diffusions share a common noise source. Specifically we show that the joint and product measures are mutually singular, so no choice of reference measure can salvage the formulation. We then introduce a conditional variational principle that replaces the prior with a reference measure that preserves the noise correlation structure. This generalization recovers the Mitter--Newton formulation as a special case when the noises are independent, and yields an explicit free energy characterization of the filter in the linear correlated-noise setting.
format Preprint
id arxiv_https___arxiv_org_abs_2604_03001
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle The Variational Approach in Filtering and Correlated Noise
Srinivasan, Sharan
Gupta, Vijay
Honnappa, Harsha
Probability
Systems and Control
Optimization and Control
The variational formulation of nonlinear filtering due to Mitter and Newton characterizes the filtering distribution as the unique minimizer of a free energy functional involving the relative entropy with respect to the prior and an expected energy. This formulation rests on an absolute continuity condition between the joint path measure and a product reference measure. We prove that this condition necessarily fails whenever the signal and observation diffusions share a common noise source. Specifically we show that the joint and product measures are mutually singular, so no choice of reference measure can salvage the formulation. We then introduce a conditional variational principle that replaces the prior with a reference measure that preserves the noise correlation structure. This generalization recovers the Mitter--Newton formulation as a special case when the noises are independent, and yields an explicit free energy characterization of the filter in the linear correlated-noise setting.
title The Variational Approach in Filtering and Correlated Noise
topic Probability
Systems and Control
Optimization and Control
url https://arxiv.org/abs/2604.03001