This paper presents a position-based attenuation and amplification method suitable for source separation and enhancement. Our novel sigmoidal time-frequency mask allows us to directly control the level within a target azimuth range and to exploit a trade-off between the production of musical noise artifacts and separation quality. The algorithm is fully describable in a closed and compact analytical form. The method was evaluated on a multitrack dataset and compared to another position-based source separation algorithm. The results show that although the sigmoidal mask leads to a lower source-to-interference ratio, the overall sound quality measured by the source-to-distortion ratio and the source-to-artifacts ratio is improved.

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