Title :
New generalized ESPRIT for direction estimation and its mathematical link to RARE method
Author :
Guangmin Wang ; Jingmin Xin ; Jiayi Wu ; Jiasong Wang ; Nangning Zheng ; Sano, Akihide
Author_Institution :
Inst. of Artificial Intell. & Robot., Xi´an Jiaotong Univ., Xi´an, China
Abstract :
The generalized ESPRIT (GESPRIT) method extends the conventional ESPRIT estimator to estimate the directions-of-arrival (DOAs) of multiple incident signals by using the array with more general geometrical configurations, where the translational invariance structure is not required. Unfortunately, the GESPRIT has serious ambiguous DOA estimates in some scenarios, and its performance degrades severely at low signal-to-noise ration (SNR) and with a small number of snapshots. Although a polynomial version of a new GESPRIT (NGESPRIT) method was given, but its derivation and estimation performance are unavailable in published literature. In this paper, in order to overcome the ambiguity of the GESPRIT and improve the estimation performance, the NGESPRIT method is derived explicitly. Moreover, the equivalence between the proposed NGESPRIT method and the rank reduction (RARE) method is clarified, while the former is more computationally efficient than the latter. Finally the effectiveness of the NGESPRIT method is substantiated through numerical examples.
Keywords :
array signal processing; direction-of-arrival estimation; polynomials; GESPRIT method; NGESPRIT method; RARE method; SNR; direction estimation; directions-of-arrival estimation; general geometrical configurations; generalized ESPRIT method; mathematical link; polynomial version; rank reduction method; sensor array processing; signal-to-noise ration;
Conference_Titel :
Signal Processing (ICSP), 2012 IEEE 11th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2196-9
DOI :
10.1109/ICoSP.2012.6491675