A new Doppler system using second-order sampling is proposed. To reduce the hardware complexity and to eliminate the balancing problem between in-phase and quadrature-phase signal channels in conventional systems, the proposed system uses a single signal channel. This system can be used in a multigate or 2-dimensional Doppler system and implemented in a full digital system.
We analyze the effect of second-order sampling on estimating the mean frequency of the Doppler signal. In order to reduce the sampling frequency of analogue-to-digital converter, it is possible to obtain the Doppler signal by sampling the radio frequency echo signal with the low frequency of $4f_0$/5 or $4f_0$/9 instead of $4f_0$, where $f_0$ is the center frequency of the transmitted signal. The computer simulation and experiments show that if the narrowband signal is transmitted as is usual in the Doppler system, the error of the mean frequency estimates due to the low sampling frequency is negligible.
In order to estimate the mean frequency and variance of the diagnostic ultrasound Doppler signal in the presence of clutter noise, a new estimator using a second-order autoregressive (AR) model, called AR estimator, is proposed. In the proposed method, the sampled signal which contains information of both the Doppler signal and clutter is described by the second-order AR model with two poles. The mean frequency and variance of a unidirectional Doppler signal can be estimated, respectively, from the phase and the magnitude of the pole with larger phase among the two poles.
It turns out that if the clutter is not completely rejected, all conventional estimations including the autocorrelation (AC) estimator result in erroneous estimations for the mean frequency and variance of the Doppler signal, whereas the AR estimator gives an accurate estimation. In the absence of clutter, however, the performances of both the AC and AR estimators are similar. If the blood flows in both directions in a sample volume and the clutter is rejected to the extent that it not longer obscures the Doppler signal, the proposed method can estimate simultaneously the mean frequencies and variances of both the forward and reverse blood flows.
The performances of the proposed AR estimator were compared with those of the AC estimator by computer simulation and experiments, and it was found that when the number of available sampled data is small, the AR estimator does not request these of a clutter filter, which simplifies the Doppler signal detection.
