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Training Convergence in Range-Based Cooperative Positioning with Stochastic Positional Knowledge
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences Vol.E95-A No.7 pp.1200-1204
Publication Date: 2012/07/01
Online ISSN: 1745-1337
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Information Theory
stochastic positional knowledge,
Cramer-Rao lower bound (CRLB),
squared position-error bound (SPEB),
Full Text: PDF(313.8KB)
This letter investigates the training convergence in range-based cooperative positioning with stochastic positional knowledge. Firstly, a closed-form of squared position-error bound (SPEB) is derived with error-free ranging. Using the derived closed-form, it is proved that the SPEB reaches its minimum when at least 2 out of N (> 2) agents send training sequences. Finally, numerical results are provided to elaborate the theoretical analysis with zero-mean Gaussian ranging errors.