
Posterior Cramer‐Rao lower bound for wireless sensor localisation networks
Author(s) -
Li Siming,
Lv Jing,
Tian Shiwei
Publication year - 2018
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2018.6456
Subject(s) - cramér–rao bound , upper and lower bounds , wireless sensor network , computer science , position (finance) , algorithm , wireless , limit (mathematics) , bayesian probability , real time computing , telecommunications , estimation theory , mathematics , computer network , artificial intelligence , mathematical analysis , finance , economics
A general closed expression of posterior Cramer‐Rao lower bound (PCRLB) for wireless sensor networks is derived and presented, based on Bayesian estimation and well suited to dynamic systems. The aim is to guide the localisation algorithm design and anchor layout fulfilling certain accuracy requirement. There is a growing need for wireless sensor systems to determine the position information indoors and in somewhere satellite positioning cannot provide service. PCRLB sets a fundamental lower limit to all kinds of localisation algorithms within consideration of dynamic state transition. This result shows that the theoretically best position solution can be obtained.