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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
Publication Date: 2017/02/01
Online ISSN: 1745-1337
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.