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

This thesis introduces a novel sorting pairing method for the azimuth-elevation estimates obtained from the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) based closed-form source localization algorithm. The ESPRIT algorithm estimates Direction of Arrival (DOA) angles from a given source using arbitrarily spaced three-dimensional arrays of vector sensors, whose locations need not be known. In estimating the DOAs there can be miss-pairings of DOA azimuth and elevation direction cosines in certain cases. In such cases, the incident angles calculated can be permuted which produces miss matching of angles or misses. The sorting pairing method presented exploits the order of eigenvalues and thereby the DOAs estimated from the ESPRIT algorithm. The sorting pairing method is compared to two other pairing methods: the traditional pairing method, a method that is simplistic in nature when dealing with misses; and the exhaustive pairing method, a method that exhaustively attempts to find the eigenvalue pairing that yields the least amount of error. Simulation results provides strong evidence that the sorting pairing method gives good results over a much larger range of signal-to-noise ratios than the traditional method, and has an accuracy that is nearly co-linear with the exhaustive method.

Eigenvalue Pairing for Direction Finding with Vector Sensor Arrays