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/

Global: Zendy Plus annual

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

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Target tracking with time difference of arrival measurements usually encounters the problem of correlated measurement noises. When the sensor network utilizes the common reference sensor, the covariance matrix of the correlated measurement noises becomes off-diagonal such that the computational complexity of the inverse of the covariance matrix as well as the subsequent matrix operations increases proportionally to the cube of the sensor number. This makes target tracking algorithms inconvenient for practical applications, and an appropriate measurement noise decorrelation method is required. In multi-sensor environments, the parallel update and the serial update are applied for exploiting the measurements from different sensors. Although the two methods deliver the equivalent tracking performances in linear systems, this equivalence does not hold in nonlinear systems as linearizing the nonlinear functions leads to approximation error. Additionally, the requirements of the two methods for storage structure and computational resource allocations are different. This paper presents a target tracking algorithm which integrates the Cholesky decomposition to decorrelate the measurement noises for the serial update which shows computational efficiency. The tracking performance is evaluated by estimation accuracy, execution time.

Indoor Target Tracking using Time Difference of Arrival Measurements in 3D