Joint Adaptive Beamforming Based on Distributed Moving Platforms

Qing Shen, Wei Liu*, Li Wang, Yin Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A distributed sensor array network consisting of sub-arrays with arbitrary locations and rotation angles placed on unmanned aerial vehicle (UAV) platforms is studied, where narrowband electro-magnetic waves are sent out by a transmitter, and the echo signals reflected from the targets are then received by the distributed UAV system. Based on this model, a joint reference signal based beamformer is proposed, leading to improved performance by exploiting the collected information across different sub-arrays simultaneously. Simulation results show that this novel beamformer is capable of extracting the signals of interest while suppressing interfering signals, and a lower mean square error (MSE) and higher output signal to interference plus noise ratio (SINR) are achieved compared with a regular reference signal based beamformer performed using a single sub-array.

Original languageEnglish
Title of host publication2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538668115
DOIs
Publication statusPublished - 2 Jul 2018
Externally publishedYes
Event23rd IEEE International Conference on Digital Signal Processing, DSP 2018 - Shanghai, China
Duration: 19 Nov 201821 Nov 2018

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume2018-November

Conference

Conference23rd IEEE International Conference on Digital Signal Processing, DSP 2018
Country/TerritoryChina
CityShanghai
Period19/11/1821/11/18

Keywords

  • Adaptive beamforming
  • distributed sensor network
  • reference signal based beamformer
  • unmanned aerial vehicle (UAV)

Fingerprint

Dive into the research topics of 'Joint Adaptive Beamforming Based on Distributed Moving Platforms'. Together they form a unique fingerprint.

Cite this