Direction-of-arrival estimation and sensor array error calibration based on FastICA

In this paper, a new method of direction of arrival(DOA)estimation and gain-phase error calibration based on FastICA is proposed to address the issue of performance deterioration in traditional high-resolution DOA estimation algorithms caused by gain-phase error. This method decomposes the gain-phase error into gain error and phase error, and estimates them separately. Our method utilizes the characteristics of the diagonal elements of the covariance matrix to estimate the gain error. The mixing matrix, composed of the array manifold matrix and gain-phase error matrix, is extracted from the snapshot samples using the FastICA algorithm. The mixing matrix is then projected onto the signal subspace to eliminate spurious signals and obtain the true steering vector. The algorithm utilizes the true steering vector to construct an oblique projection operator to acquire the single-component received data. The DOA estimation is obtained through subspace orthogonality spectral search, and the phase error is estimated based on it. The algorithm in this paper can maintain good performance in phase error large scenarios for both gain error estimation and DOA estimation. The correction process does not require the setting of additional auxiliary signal sources and avoids the issue of suboptimal convergence that occurs in the Weiss-Friedlander (WF) method. Numerical simulations validate the effectiveness of the proposed method.