On the Cramér-Rao Bound Under a Linear Transformation of the Parameter

Hai Victor Habi, Hagit Messer, Shay Sagiv, Joseph Tabrikian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper deals with the case where the Crarnér-Rao bound (CRB) on the estimation error of a deterministic parameter vector is given, and it is desired to evaluate a bound on a linear transformation of it. The literature suggests two versions of the bound on the estimation error of the reparameterized vector, denoted by B_1 and B_2. We first identify the conditions under which either of these bounds exist, focusing on the case where they co-exist, Under such scenario, we find the relations between B_1, B_2, and CRB. The results are demonstrated on two practical applications of multi-sensor signal processing.

Original languageEnglish
Title of host publication2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages426-430
Number of pages5
ISBN (Electronic)9798350344523
DOIs
StatePublished - 2023
Event9th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2023 - Herradura, Costa Rica
Duration: 10 Dec 202313 Dec 2023

Publication series

Name2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2023

Conference

Conference9th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2023
Country/TerritoryCosta Rica
CityHerradura
Period10/12/2313/12/23

Keywords

  • Cramér-Rao bound
  • linear transfor-mation
  • reparameterization

Fingerprint

Dive into the research topics of 'On the Cramér-Rao Bound Under a Linear Transformation of the Parameter'. Together they form a unique fingerprint.

Cite this