Adaptive sonar beamformer based on inverse QR decomposition and recursive least squares filter for underwater target detection

摘要

To enhance underwater target detection performance, a standard hexagonal array (HA) (plane array) is designed for active sonar implementation in shallow water environments. For the hexagonal receiving array, the numerically robust inverse QR (Q, orthogonal matrix; R, upper triangular matrix) decomposition and recursive least-squares (RLS) are used to derive the minimum variance distortionless response (MVDR) beamformer (BF) under a hexagonal fast Fourier transform (HFFT) framework. The HFFT inverse QR (IQR)-RLS algorithm offers computational saving and can be mapped onto coordinate rotation digital computer processor-based systolic arrays, which makes it suitable for array real-time application. An analysis of the numerical robustness and computational complexity of the adaptive beamforming is presented. Using the proposed scheme to build HA adaptive BF reduces the computational burden and offers a better convergence rate than conventional BF. The experimental data analysis demonstrates the effectiveness of the algorithm against reverberation interference, and its improvement of target localization accuracy in a reverberation-limited area during the underwater target detection process.View full textDownload full textRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/01431161.2010.523026