Joint DOA and Doppler frequency estimation of coherent and/or same‐direction signals. (4th December 2017)

• Record Type: Journal Article
• Authors: Shan, Zebiao; Liu, Xiaosong; Wang, Chunyang; Shi, Hongwei; Shi, Yaowu
• Other Names: Wang Kezhi guestEditor.; Jin Qun guestEditor.; Sharif Hamid guestEditor.
• Is Part Of: International journal of communication systems. Volume 31:Number 7(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-12-04
• Subjects: coherent signals -- direction of arrival (DOA) estimation -- Doppler frequency estimation -- same‐direction signals -- signal power estimation -- wireless communication; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.3482
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: The smart antenna is one of the most attractive technologies in mobile communications. In this paper, a modified 2D multiple signal classification (MUSIC) algorithm based on eigenspace is presented to jointly estimate the directions of arrival and Doppler frequencies for the coherent and/or same‐direction signals. First, a modified 2D MUSIC (MMUSIC) algorithm is provided using the conjugate data to cope with the estimation for the case of coherent signals and/or same‐direction signals. Then on this basis, we derive an eigenspace‐based MMUSIC (ES‐MMUSIC) algorithm, which uses the information of both signal and noise subspaces. The ES‐MMUSIC algorithm can also estimate signals power. Besides, this method has no influence on directions of arrival and Doppler frequencies estimation of uncorrelated signals; in the meanwhile, the computational complexity will have no obvious increase as well. Finally, the results of several contrastive numerical simulations demonstrate the superiority of the ES‐MMUSIC algorithm compared with the MMUSIC algorithm. Abstract : Highlights An efficient ES‐MMUSIC algorithm is proposed to jointly estimate the DOAs and Doppler frequencies of the coherent and/or same‐direction signals. The proposed ES‐MMUSIC algorithm uses both the signal and noise subspaces information. The ES‐MMUSIC algorithm can estimate the signals power as well, and the estimated parameters (DOAs, Doppler frequencies, and signals power) can be automatically paired.