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A new approach for active-sonar target detection and bearing estimation from a mobile two-dimensional array of sensors operating in a predominantly noisy environment is presented. Sensor-level adaptive noise cancellation featuring an unconventional method for reference-noise estimation is the key preprocessing step in the proposed approach. A signal-subspace algorithm resulting from two-stage optimisation based on a generalised eigendecomposition of the signal plus (residual) noise covariance matrix is employed to estimate the bearing of the detected target. Simulation results conclusively demonstrate that the proposed scheme is capable of performing target detection and the subsequent two-dimensional bearing estimation with a high degree of reliability at signal-to-noise power ratios as low as -70 and -40-dB, respectively.