Thinned coprime arrays for DOA estimation. Raza, A., Liu, W., & Shen, Q. In 2017 25th European Signal Processing Conference (EUSIPCO), pages 395-399, Aug, 2017.
Paper doi abstract bibtex Sparse arrays can generate a larger aperture than traditional uniform linear arrays (ULA) and offer enhanced degrees-of-freedom (DOFs) which can be exploited in both beamforming and direction-of-arrival (DOA) estimation. One class of sparse arrays is the coprime array, composed of two uniform linear subarrays which yield an effective difference co-array with higher number of DOFs. In this work, we present a new coprime array structure termed thinned coprime array (TCA), which exploits the redundancy in the structure of the existing coprime array and achieves the same virtual aperture and DOFs as the conventional coprime array with much fewer number of sensors. An analysis of the DOFs provided by the new structure in comparison with other sparse arrays is provided and simulation results for DOA estimation using the compressive sensing based method are provided.
@InProceedings{8081236,
author = {A. Raza and W. Liu and Q. Shen},
booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
title = {Thinned coprime arrays for DOA estimation},
year = {2017},
pages = {395-399},
abstract = {Sparse arrays can generate a larger aperture than traditional uniform linear arrays (ULA) and offer enhanced degrees-of-freedom (DOFs) which can be exploited in both beamforming and direction-of-arrival (DOA) estimation. One class of sparse arrays is the coprime array, composed of two uniform linear subarrays which yield an effective difference co-array with higher number of DOFs. In this work, we present a new coprime array structure termed thinned coprime array (TCA), which exploits the redundancy in the structure of the existing coprime array and achieves the same virtual aperture and DOFs as the conventional coprime array with much fewer number of sensors. An analysis of the DOFs provided by the new structure in comparison with other sparse arrays is provided and simulation results for DOA estimation using the compressive sensing based method are provided.},
keywords = {array signal processing;compressed sensing;direction-of-arrival estimation;thinned coprime array;DOA estimation;sparse arrays;direction-of-arrival estimation;uniform linear subarrays;coprime array structure;uniform linear arrays;DOF;difference co-array;Sensor arrays;Indexes;Direction-of-arrival estimation;Estimation;Array signal processing;Thinned coprime array;DOA estimation;degrees of freedom;difference co-array},
doi = {10.23919/EUSIPCO.2017.8081236},
issn = {2076-1465},
month = {Aug},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570347059.pdf},
}
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