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

Various GNSS applications require low-cost, small-scale, lightweight and power-saving GNSS devices and require high precision in terms of low noise for carrier phase and code observations. Applications vary from navigation approaches to positioning in geo-monitoring units up to integration in multi-sensor-systems. For highest precision, only GNSS receivers are suitable that provide access to raw data such as carrier phase, code ranges, Doppler and signal strength. A system integration is only possible if the overall noise level is known and quantified at the level of the original observations. A benchmark analysis based on a zero baseline is proposed to quantify the stochastic properties. The performance of the consumer grade GNSS receiver is determined and evaluated against geodetic GNSS receivers to better understand the utilization of consumer grade receivers. Results indicate high similarity to the geodetic receiver, even though technical limitations are present. Various stochastic techniques report normally distributed carrier-phase noise of 2 mm and code-range noise of 0.5-0.8 m. This is confirmed by studying the modified Allan standard deviation and code-minus-carrier combinations. Derived parameters serve as important indicators for the integration of GNSS receivers into multi-sensor-systems.

Feasibility of Consumer Grade GNSS Receivers for the Integration in Multi-Sensor-Systems