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In the presence of coherent interference, adaptive beamforming algorithm fails to form nulls in the direction of interference, leading to cancellation of expect signal. To address this issue, this paper proposes a coherent interference suppression method with virtual array and multi‐stage spatial smoothing (MSS). In the proposed method, the adaptive weight acquired by the spatial smoothing (SS) algorithm is applied to all subarrays to generate a virtual array. Another adaptive weight is then acquired from the virtual array using the SS algorithm and applied to all subarrays of the virtual array to generate another virtual array. The process is iterated until there are insufficient array elements for SS. The proposed method can deeply break the correlation between expect signal and coherent interference and form deep nulls in the direction of coherent interference. [ABSTRACT FROM AUTHOR]

When a small number of snapshots are used, the performance of the direction-of-arrival (DOA) estimation method based on the least squares (LS) degrades severely because of inadequate estimation of the covariance matrix. Although the subspace-based DOA estimation methods were proposed to improve the performance of DOA estimation method based on the LS; however these methods are computationally complex, especially for a large number of array elements. In this Letter, the DOA estimation method based on the LS is improved by reconstructing the covariance matrix with diagonal loading, where the diagonal loading factor is computed automatically by estimating the signal power. The reciprocal of the array pattern is taken to calculate the spatial spectrum, where the peak values correspond to the estimated DOAs of signals. The proposed method can achieve better performance with few snapshots and low computational complexity. The effectiveness of the proposed method is verified by the numerical simulations. [ABSTRACT FROM AUTHOR]

For the suppression of rapidly moving interferences in wideband beamforming, an adaptive null broadening method is proposed. In the proposed method, the taper matrix is calculated by adding virtual interferences around original interferences. Then, based on the obtained taper matrix and the sample covariance matrix, the covariance matrix is reconstructed to calculate the weight vector for adaptive null broadening. Simulation results verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A hybrid space–time adaptive processing (STAP) approach of the direct data domain (DDD) algorithm and adaptive localised domain transformation is proposed for discrete interference suppression in non‐homogeneous clutter which is inevitable in actual airborne radar applications. In the proposed method, the adaptive localised domain transformation matrix is firstly formed by the DDD weighting vectors in angle‐Doppler directions to suppress discrete interference. Afterwards, the adaptive localised domain transformation matrix is applied to the conventional STAP method to suppress the residual clutter. The proposed method is verified based on the actual airborne radar data. [ABSTRACT FROM AUTHOR]

The eigenvalue‐based minimum description length (MDL) method for source number estimation is widely applied in practical scenarios. However, the performance of the MDL method degrades significantly when it is applied to an asymmetrical subarray situation due to the inequality of the noise power of each channel. Therefore, an improved MDL method for subarray level is proposed by normalising noise power to reconstruct the received signal covariance matrix. Simulation results show that the proposed method outperforms the conventional source number estimation methods for a subarray situation. [ABSTRACT FROM AUTHOR]

When the training snapshots are contaminated by the desired signal, the performance of the orthogonal projection (OP) approach degrades significantly. Therefore, an improved OP adaptive beamforming is proposed by reconstructing interference covariance matrix to eliminate the desired signal cancellation effect. In the proposed method, by integrating the Capon spatial spectrum over a region separated from the desired signal direction, the interference‐plus‐noise covariance matrix is reconstructed first to remove the desired signal component from the sample covariance matrix. Subsequently, the interference subspace is estimated by eigenvalue decomposition, and then the adaptive weight vector is calculated using the OP algorithm to eliminate the noise perturbation. Simulation results show that the performance of the proposed algorithm is almost the same as the optimum beamforming. [ABSTRACT FROM AUTHOR]