The convergence speed of multichannel adaptive active noise control algorithms can be improved by pre-whitening the reference signals and reducing their cross-correlations. When considering nonstationary processes, like road noise, it proves advantageous to use a short time-based cross-correlation estimation of the reference signal, which can be obtained as part of the bin-normalised frequency domain least-means-squares algorithm. However, the regularisation of such an algorithm is crucial to its success and can further improve the convergence rate. In addition, virtual sensors can be employed by using the additional filter method, which provides targets for the measured error signals to follow, generated from the reference signals. Still, the performance of this virtual sensing is known to be degraded if the properties of the reference signals change, so special consideration should be taken when the reference signals are nonstationary.