Search Results (4)

In sonar systems, the performance of adaptive beamformers severely degrades when mismatches occur between the actual and presumed steering vectors of the desired signal, mainly due to hydrophone position errors, amplitude-phase errors, and the scattered effect of arrays. Similarly, an inadequate number of “training” samples can lead to performance degradations similar to those caused by mismatches. In this paper, an adaptive beamforming algorithm based on oblique projection (OP-ABF) mismatch compensation is proposed to remove the degradation caused by the arbitrary-type steering vector mismatch of the desired signal. The proposed algorithm is motivated by the fact that the weight vector of adaptive beamforming can be represented as a linear combination of the optimal one and the oblique projection (OP) vector, which is generated by the steering vector mismatch and does not exist without this. Our algorithm was developed by constructing the oblique projection mismatch compensation vector (OPMCV) to provide the minimum variance distortionless response (MVDR) beamformer. Then, the algorithm could be implemented by the solution of the OP matrix with the formulation of the covariance matrix loading (CML). The simulation results of a uniform linear array (ULA) and a half-cylindrical conformal array (HCCA) show that the OP-ABF can optimize the original weight vector as much as possible without sacrificing the output signal-to-interference-plus-noise ratio (SINR) under different conditions. Experimental results for the HCCA also confirm the effectiveness of this algorithm. Full article

Adaptive beamforming can efficiently contract interference and noise. Due to high sensitivity of the beamformer to model mismatch, the capability of interference reduction will critically degrade when the signal model mismatch occurs, particularly when the sampling sequence contains the desired signal. For the purpose of enhancing the robustness of beamformers to signal model mismatch, we propose a new robust adaptive beamforming (RAB) method. Firstly, the precise steering vector (SV) associating with the desired signal is estimated by employing the minimum norm of subspace projection (MNSP) approach. Secondly, the nominal interference SVs are estimated via the maximum entropy power spectrum. Subsequently, the corrected interference SVs and powers are obtained by oblique projection. Finally, the interference-plus-noise covariance matrix (INCM) is reconstructed, and the proposed RAB is obtained. Multiple simulations are carried out and demonstrate the robustness of the proposed RAB method. Full article

Within a complex sea or ground surface background, multipath signals are strongly correlated or even completely coherent, which leads to signal cancellation when conventional optimal beamforming is performed. Aiming at the above problem, a coherent signal-receiving algorithm is proposed based on oblique projection technology in this paper. The direction of arrival (DOA) of incident signals is estimated firstly by the space smoothing-based MUSIC method. The composite steering vector of multipath coherent signals is then obtained utilizing the oblique projection matrix constructed with the estimated angles. The weight vector is thereby derived with the minimum variance distortionless response criteria. The proposed oblique projection-based beamformer can receive the multipath coherent signals effectively. Moreover, the proposed beamformer is more robust and converges to optimal beamformer rapidly without aperture loss. The theoretical analysis and simulation verify the validity and superiority of the proposed coherent signal beamformer. Full article

The presence of spoofing signals poses a significant threat to global navigation satellite system (GNSS)-based positioning applications, as it could cause a malfunction of the positioning service. Therefore, the main objective of this paper is to present a spatial-temporal technique that enables GNSS receivers to reliably detect and suppress spoofing. The technique, which is based on antenna array, can be divided into two consecutive stages. In the first stage, an improved eigen space spectrum is constructed for direction of arrival (DOA) estimation. To this end, a signal preprocessing scheme is provided to solve the signal model mismatch in the DOA estimation for navigation signals. In the second stage, we design an optimization problem for power estimation with the estimated DOA as support information. After that, the spoofing detection is achieved by combining power comparison and cross-correlation monitoring. Finally, we enhance the genuine signals by beamforming while the subspace oblique projection is used to suppress spoofing. The proposed technique does not depend on external hardware and can be readily implemented on raw digital baseband signal before the despreading of GNSS receivers. Crucially, the low-power spoofing attack and multipath can be distinguished and mitigated by this technique. The estimated DOA and power are both beneficial for subsequent spoofing localization. The simulation results demonstrate the effectiveness of our method. Full article