Robust beamforming technology for small platform conformal array based on covariance matrix fitting

To address the challenges of detection on small-scale platforms like unmanned undersea vehicles(UUV), which are characterized by their maneuverability and the constraints of limited array apertures, we design various beamforming algorithms leverage U-shaped conformal planar arrays specifically tailored for compact platforms. This study evaluates the impact of factors such as snapshot rate, input signal-to-noise ratio(SNR), and inaccuracies in the steering vector on the robustness of these beamforming techniques. While the Minimum Variance Distortionless Response(MVDR) method is noted for its superior array gain, its performance significantly deteriorates in the presence of steering vector errors and inaccuracies in the covariance matrix estimation. To mitigate these issues, this paper introduces the covariance matrix fitting and the dual-constraint covariance matrix fitting beamforming approaches, enhancing the original method's robustness. The efficacy of the algorithm of this paper is validated through numerical simulations by comparing it with various beamforming techniques, thereby assessing their robustness in conformal arrays used on underwater small-scale platforms. Additionally, the reliability of these methods is further corroborated through experimental in an anechoic pool, taking into account the positional inaccuracies of the array elements.