Anytime signal processing algorithms are to improve the overall performance of larger scale embedded digital signal processing (DSP) systems. In such systems there are cases where due to abrupt changes within the environment and/or the processing system temporal shortage of computational power and/or loss of some data may occur. It is an obvious requirement that even in such situations the actual processing should be continued to insure appropriate performance. This means that signal processing of somewhat simpler complexity should provide outputs of acceptable quality to continue the operation of the complete embedded system. The accuracy of the processing will be temporarily lower but possibly still enough to produce data for qualitative evaluations and supporting decisions. In this paper a new anytime Fourier transformation algorithm is introduced. The presented method reduces the delay problem caused by the block-oriented fast algorithms and at the same time keeps the computational complexity on relatively low level. It also makes possible the availability of partial results or estimates in case of abrupt reaction need, long or possibly infinite input data sequences.