| Title |
ML-based Direction Estimation for Noncircular Signals in Moving Array |
| DOI |
https://doi.org/10.5573/ieie.2021.58.7.49 |
| Keywords |
Direction estimation; noncircular signals; maximum-likelihood; decoupled estimation; Doppler shift |
| Abstract |
In the estimation of directions of signals arriving at a sensor array, maximum-likelihood (ML) based methods can provide better performance than subspace-based ones. However the ML-based estimation should deal with a multidimensional problem that is computationally expensive. The multidimensional problem can be transformed into iterative one-dimensional problems via signal separations. A signal separation based method, which estimates the directions of noncircular signals incident into a moving array, requires the eigendecomposition of an N×N matrix at each search point where N is the number of snapshots. If N is large the computational burden for the eigendecomposition would be huge. This paper proposes a method that estimates the directions by using matrices of size 2, rather than of size N. Though the computational load of the proposed method is significantly decreased by virtue of the use of 2×2 matrices, its estimation performance is the same as that of the existing one. |