GDOP and the CRB for Positioning Systems

Wanchun LI  Ting YUAN  Bin WANG  Qiu TANG  Yingxiang LI  Hongshu LIAO  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E100-A   No.2   pp.733-737
Publication Date: 2017/02/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E100.A.733
Type of Manuscript: LETTER
Category: Information Theory
geometric dilution of precision,  Cramer-Rao bound,  positioning systems,  Fisher information matrix,  

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In this paper, we explore the relationship between Geometric Dilution of Precision (GDOP) and Cramer-Rao Bound (CRB) by tracing back to the original motivations for deriving these two indexes. In addition, the GDOP is served as a sensor-target geometric uncertainty analysis tool whilst the CRB is served as a statistical performance evaluation tool based on the sensor observations originated from target. And CRB is the inverse matrix of Fisher information matrix (FIM). Based on the original derivations for a same positioning application, we interpret their difference in a mathematical view to show that.