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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Autonomous unmanned aerial vehicle (UAV) inertial navigation exhibits anextreme dependency on the availability of global navigation satellite systems(GNSS) signals, without which it incurs in a slow but unavoidable positiondrift that may ultimately lead to the loss of the platform if the GNSS signalsare not restored or the aircraft does not reach a location from which it can berecovered by remote control. This article describes an stochastic high fidelitysimulation of the flight of a fixed wing low SWaP (size, weight, and power)autonomous UAV in turbulent and varying weather intended to test and validatethe GNSS-Denied performance of different navigation algorithms. Its open-source\nm{\CC} implementation has been released and is publicly available.  Onboard sensors include accelerometers, gyroscopes, magnetometers, a Pitottube, an air data system, a GNSS receiver, and a digital camera, so thesimulation is valid for inertial, visual, and visual inertial navigationsystems. Two scenarios involving the loss of GNSS signals are considered: thefirst represents the challenges involved in aborting the mission and headingtowards a remote recovery location while experiencing varying weather, and thesecond models the continuation of the mission based on a series of closelyspaced bearing changes.  All simulation modules have been modeled with as few simplifications aspossible to increase the realism of the results. While the implementation ofthe aircraft performances and its control system is deterministic, that of allother modules, including the mission, sensors, weather, wind, turbulence, andinitial estimations, is fully stochastic. This enables a robust evaluation ofeach proposed navigation system by means of Monte-Carlo simulations that relyon a high number of executions of both scenarios.

Stochastic High Fidelity Simulation and Scenarios for Testing of Fixed Wing Autonomous GNSS-Denied Navigation Algorithms