English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

In this paper, we study performance limits of sensor localization from anovel perspective. Specifically, we consider the Cramer-Rao Lower Bound (CRLB)in single-hop sensor localization using measurements from received signalstrength (RSS), time of arrival (TOA) and bearing, respectively, butdifferently from the existing work, we statistically analyze the trace of theassociated CRLB matrix (i.e. as a scalar metric for performance limits ofsensor localization) by assuming anchor locations are random. By the CentralLimit Theorems for $U$-statistics, we show that as the number of the anchorsincreases, this scalar metric is asymptotically normal in the RSS/bearing case,and converges to a random variable which is an affine transformation of achi-square random variable of degree 2 in the TOA case. Moreover, we provideformulas quantitatively describing the relationship among the mean and standarddeviation of the scalar metric, the number of the anchors, the parameters ofcommunication channels, the noise statistics in measurements and the spatialdistribution of the anchors. These formulas, though asymptotic in the number ofthe anchors, in many cases turn out to be remarkably accurate in predictingperformance limits, even if the number is small. Simulations are carried out toconfirm our results.

A Statistically Modelling Method for Performance Limits in Sensor Localization