Kalman Filter from the Mutual Information Perspective

Chi Guo; Jianlang Hu; Yarong Luo

REVIEW

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2101.00757 v1 pith:LMJD2PRM submitted 2021-01-04 cs.IT math.IT

Kalman Filter from the Mutual Information Perspective

Yarong Luo , Jianlang Hu , Chi Guo This is my paper

classification cs.IT math.IT

keywords filterkalmaninformationmutualperspectivestatebayesianbest

verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

0 comments

read the original abstract

Kalman filter is a best linear unbiased state estimator. It is also comprehensible from the point view of the Bayesian estimation. However, this note gives a detailed derivation of Kalman filter from the mutual information perspective for the first time. Then we extend this result to the R\'enyi mutual information. Finally we draw the conclusion that the measurement update of the Kalman filter is the key step to minimize the uncertainty of the state of the dynamical system.

Kalman Filter from the Mutual Information Perspective

discussion (0)