Abstract
A direction of arrival (DOA) estimator for two-dimensional (2D) incoherently distributed (ID) sources is presented under proposed double cross arrays, satisfying both the small interval of parallel linear arrays and the aperture equalization in the elevation and azimuth dimensions. First, by virtue of a first-order Taylor expansion for array manifold vectors of parallel linear arrays, the received signal of arrays can be reconstructed by the products of generalized manifold matrices and extended signal vectors. Then, the rotating invariant relations concerning the nominal elevation and azimuth are derived. According to the rotating invariant relationships, the rotating operators are obtained through the subspace of the covariance matrix of the received vectors. Last, the angle matching approach and angular spreads are explored based on the Capon principle. The proposed method for estimating the DOA of 2D ID sources does not require a spectral search and prior knowledge of the angular power density function. The proposed DOA estimation has a significant advantage in terms of computational cost. Investigating the influence of experimental conditions and angular spreads on estimation, numerical simulations are carried out to validate the effectiveness of the proposed method. The experimental results show that the algorithm proposed in this paper has advantages in terms of estimation accuracy, with a similar number of sensors and the same experimental conditions when compared with existing methods, and that it shows a robustness in cases of model mismatch.
Highlights
In view of the problem of localization, traditional parameter estimation algorithms are based on a point source model
The signal-to-noise ratio (SNR) is defined as 10log(1/σ2n ), where the noise is assumed to be the Gaussian white zero mean with a variance of σ2n
An estimation of the parameters of a 2D incoherently distributed (ID) source is presented based on a double cross array that satisfies both the small interval of parallel linear arrays and the aperture equalization in the elevation and azimuth dimensions
Summary
In view of the problem of localization, traditional parameter estimation algorithms are based on a point source model. In an underwater sonar background, with the reduction of distance, the spatial geometry of a target cannot be ignored, many parts of the target reflecting signals; the point target model cannot describe the characteristics of the source effectively, and distributed sources models are suitable in this context. There are similar scenarios, such as the area target or clutter involved in radar signal processing, whose array observation signal usually has a certain diffusion in the spatial and temporal domain [3,4] At this time, the parameters estimation of targets based on a point source model assumption is seriously deteriorated, while the algorithms based on a distributed source model can obtain more accurate information
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