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Deterministic Least Squares Filtering (2004)

Abstract
deterministic interpretation of the Kalman #ltering formulas is given, using theprinc#RB of least squares estimation. The observed signal and the to-be-estimated signal are modeled as being generated as outputs of a #nite-dimensional linear system driven by an input disturbanc, Postulating that the observed signal is generated by the inputdisturbanc that has minimal least squares norm leads to a method ofcqB#B#;q an estimate of the to-be-estimated output. The derivation of the resulting #lter iscqBNBN out in ac;BNPq,VL self-c,VLLVPq way. The analogous approac to least squares cuares is alsodiscPILRq c 2003 Elsevier B.V. All rights reserved.

Publication details
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=?doi=10.1.1.4.7798
Source ftp://ftp.esat.kuleuven.ac.be/pub/SISTA/willems/reports/02-66.pdf
Contributors CiteSeerX
Repository CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Keywords Filtering, Least squares estimation, Kalman ltering, Mis t, Latency, Least squares control, Linear systems, Riccati equation
Type text
Language English
Relation 10.1.1.2.7511