Direction of Arrival Identification Using MUSIC Method and NLMS Beamforming

Conference proceedings article

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Suleesathira R.

ผู้เผยแพร่: Hindawi

ปีที่เผยแพร่ (ค.ศ.): 2020

ISBN: 9780740000000

นอก: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103739952&doi=10.1109%2fiSAI-NLP51646.2020.9376838&partnerID=40&md5=f89b94b3d98c3b73736d99d5667c53ff

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

This paper provides the capability of the direction of arrival (DOA) identification to determine which the estimated DOA belongs to the desired signal and to undesired signals. One of the well known subspace-based methods for finding directions is MUSIC (MUltiple Signal Classification). The separation of signal and noise subspaces is the crucial step to give the precise estimation. The skewness coefficient is proposed to reinforce the conventional MUSIC method for the subspace division without knowing the number of source signals. The normalized least mean square (NLMS) beamforming is used to compute the weight vector so that it directs the mainbeam towards the desired user. The angle of the mainbeam is identified to be the DOA of the desired signal which makes the rest estimated DOAs belong to interference signals. The application of the DOA identification is shown to be advantageous to the null broadening beamforming. The simulation results confirm the effectiveness of the proposed method in the case of limited snapshots. © 2020 IEEE.

คำสำคัญ

DOA estimation, DOA identification, null broadening beamforming