In towed array sonar, the directional noise originating from the tow ship, mainly machinery and hydrodynamic noise, often limits the sonar performance. When processed with classical beamforming techniques, loud tow ship noise induces high sidelobes that may hide detection of quiet targets in forward bearings. As it is not easy to reduce the emitted tow ship noise to the desired extent, several studies are conducted to cancel this noise with optimised beamformers. Adaptive beamforming techniques seem the most promising in that aim. Therefore, apart from conventional beamforming, two adaptive techniques have been implemented and tuned to optimise tow ship noise cancelling: MVDR beamforming and inverse beamforming. These algorithms are applied to real and simulated towed array data. Their beamforming performance is compared in passive and active use. Although it is hard to find objective criteria for the performance of totally different beamformers, it is found that in both simulated and real environments, the adaptive beamformers outperform conventional beamformers.