UAV Path Prediction for CD&R to Manned Aircraft in a Confined Airspace for Cooperative Mission

Joint Authors

Lin, Chin E.
Lai, Ya-Hsien

Source

International Journal of Aerospace Engineering

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-03-01

Country of Publication

Egypt

No. of Pages

9

Abstract EN

In this paper, a new path prediction approach for unmanned aerial vehicles (UAVs) for conflict detection and resolution (CD&R) to manned aircraft in cooperative mission in a confined airspace is proposed.

Path prediction algorithm is established to estimate UAV flight trajectory to predict conflict threat to manned aircraft in time advances (front-end process of CD&R system).

A hybrid fusion model is formulated based on three different trajectory prediction conditions considering scenarios in geographical conditions to aid the generation of appropriate resolution advisory of conflict alert.

It offers a more precise CD&R system for manned and unmanned aircraft in cooperative rescue missions.

American Psychological Association (APA)

Lin, Chin E.& Lai, Ya-Hsien. 2018. UAV Path Prediction for CD&R to Manned Aircraft in a Confined Airspace for Cooperative Mission. International Journal of Aerospace Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1167891

Modern Language Association (MLA)

Lin, Chin E.& Lai, Ya-Hsien. UAV Path Prediction for CD&R to Manned Aircraft in a Confined Airspace for Cooperative Mission. International Journal of Aerospace Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1167891

American Medical Association (AMA)

Lin, Chin E.& Lai, Ya-Hsien. UAV Path Prediction for CD&R to Manned Aircraft in a Confined Airspace for Cooperative Mission. International Journal of Aerospace Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1167891

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1167891