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A maximum-entropy algorithm is developed for real time estimation of the power spectrum mean frequency of a Doppler shifted probe. This technique is compared with a covariance argument approximation and performance is given in terms of noise immunity, measurement bias, and accuracy. Estimator evaluation is made from numerical results with a computer simulated signal having a Gaussian spectral density. The maximum-entropy and covariance argument algorithms are implemented on a digital signal processing microprocessor (Analog Devices ADSP2181) for comparison. The maximum entropy technique demonstrates substantial improvement over covariance processing with respect to noise immunity and exhibits no bias in the presence of band limited noise. The maximum-entropy algorithm can be implemented, without any post-processing required, using the ADSP2181 on typical acoustic Doppler signals in the frequency range between 150 and 1200 kHz by frequency down conversion to a fundamental Nyquist interval of 4 kHz. © 1997 American Institute of Physics.