Analysis of RF Electromagnetic Compatibility Prediction Among UAV Airborne Communication Equipments

doi:10.3969/j.issn.1006-2475.2012.06.002

Computer and Modernization ›› 2012, Vol. 1 ›› Issue (6): 5-8,26.doi: 10.3969/j.issn.1006-2475.2012.06.002

• 人工智能 • Previous Articles Next Articles

Analysis of RF Electromagnetic Compatibility Prediction Among UAV Airborne Communication Equipments

ZHAO Yi-chi¹, SONG Zu-xun², LI Heng-bo³

1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China;2. No.365 Institute, Northwestern Polytechnical University, Xi’an 710065, China;3. School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710129, China

Received:2012-02-17 Revised:1900-01-01 Online:2012-06-14 Published:2012-06-14

Abstract

Abstract: As the internal space of UAV is limited and the equipments are closely installed, the electromagnetic environment of UAV system is fairly complex and the deteriorative electromagnetic environment causes serious interferences among different equipments. Therefore, electromagnetic compatibility prediction is a very effective means to ensure the electromagnetic compatibility among the UAV airborne communication equipments. According to the characteristics of UAV, an interference margin analysis method is proposed, which is fit for the RF electromagnetic compatibility prediction among the UAV airborne communication equipments. The effectiveness of this method is verified by the mathematical model of the airborne equipments about frequency and amplitude forecasting, which provides an effective solution for analyzing the RF electromagnetic compatibility among airborne communication equipments.

Key words: electromagnetic compatibility, prediction, interference margin

CLC Number:

O472.5

ZHAO Yi-chi;SONG Zu-xun;LI Heng-bo . Analysis of RF Electromagnetic Compatibility Prediction Among UAV Airborne Communication Equipments[J]. Computer and Modernization, 2012, 1(6): 5-8,26.

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Analysis of RF Electromagnetic Compatibility Prediction Among UAV Airborne Communication Equipments

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