A triply primed array (TPA) is configured on three mutually primed integers (N1, N2 and N3), which operates with O(N1N2N3) degree-of-freedoms to estimate the direction-of-arrivals (DOAs) of multiple incident quasi-stationary signals. The set of unique and contiguous lags of the proposed TPA is searched and verified. Simulation results verify that the proposed TPA can detect more incident signals with higher accuracy than its compatible counterparts.
2. Roy, R. and T. Kailath, "ESPRIT-estimation of signal parameters via rotational invariance techniques," IEEE Trans. Acous. Speech Signal Process., Vol. 37, No. 7, 984-995, 1989.
3. Mao, W. K., T. H. Hsieh, and C. Y. Chi, "DOA estimation of quasi-stationary signals with less sensors than sources and unknown spatial noise covariance: A Khatri-Rao subspace approach," IEEE Trans. Signal Process., Vol. 58, No. 4, 2168-2180, 2010.
4. Pal, P. and P. P. Vaidyanathan, "Nested arrays: A novel approach to array processing with enhanced degrees of freedom," IEEE Trans. Signal Process., Vol. 58, No. 8, 4167-4181, 2010.
5. Vaidyanathan, P. P. and P. Pal, "Sparse sensing with co-prime samplers and arrays," IEEE Trans. Signal Process., Vol. 59, No. 2, 573-586, 2011.
6. Pal, P. and P. P. Vaidyanathan, "Coprime sampling and the MUSIC algorithm," Proc. IEEE DSP/SPE Workshop, 289-294, 2011.
7. Guo, M., T. Chen, and B. Wang, "An improved DOA estimation approach using coarray interpolation and matrix denoising," Sensors, Vol. 17, No. 5, 1140, 2017.
8. Zhou, C. and J. Zhou, "Direction-of-arrival estimation with coarray ESPRIT for coprime array," Sensors, Vol. 17, No. 8, 1779, 2017.
9. Kim, J. M., O. K. Lee, and J. C. Ye, "Compressive MUSIC: Revisiting the link between compressive sensing and array signal processing," IEEE Trans. Info. Theory, Vol. 58, No. 1, 278-301, 2012.
10. Zhang, Y. D., M. G. Amin, and B. Himed, "Sparsity-based DOA estimation using co-prime arrays," IEEE Int. Conf. Acous. Speech Signal Process., 3967-3971, 2013.
11. Qin, S., Y. D. Zhang, and M. G. Amin, "Generalized coprime array configurations for direction-of-arrival estimation," IEEE Trans. Signal Process., Vol. 63, No. 6, 1377-1390, 2015.
12. Xu, L., J. Chen, and Y. Gao, "Off-grid DOA estimation based on sparse representation and rife algorithm," Progress In Electromagnetics Research M, Vol. 59, 193-201, 2017.
13. Shen, Q., W. Liu, W. Cui, S. Wu, Y. D. Zhang, and M. G. Amin, "Low-complexity direction-of-arrival estimation based on wideband co-prime arrays," IEEE/ACM Trans. Audio Speech Lang. Process., Vol. 23, No. 9, 1445-1456, 2015.
14. Liu, S., J. Zhao, and Z. Xiao, "DOA estimation with sparse array under unknown mutual coupling," Progress In Electromagnetics Research Letters, Vol. 70, 147-153, 2017.
15. Shen, Q., W. Liu, W. Cui, and S. Wu, "Extension of co-prime arrays based on the fourth-order difference co-array concept," IEEE Signal Process. Lett., Vol. 23, No. 5, 615-619, 2016.
16. CVX Research Inc., "CVX: Matlab Software for Disciplined Convex Programming, version 2.0 beta,", http://cvxr.com/cvx, 2013.
17. Grant, M. and S. Boyd, "Graph implementations for nonsmooth convex programs," Recent Advances in Learning and Control, V. Blondel, S. Boyd, and H. Kimura (eds.), 95–110, Springer-Verlag, 2008.