最小均方误差解调算法在彩色超声血流成像中的研究

研究了最小均方误差正交解调算法在超声血流成像中的应用。首先由设计的期望信号与接收信号在最小均方误差原则下得到其迭代解调形式,获得回波信号同相分量和正交分量,然后由得到的正交解调信号通过自相关的方法对血流流速进行估计。解调算法的仿真结果表明,对高斯噪声信噪比为0.5—10dB的正弦波调制信号,解调输出平均信噪比与Hilbert变换法和I/Q解调法相比分别提高了15dB和4dB;血流成像的仿真结果表明,在流速估计性能相当的情况下,解调的乘法运算量仅分别为上述对比方法的18%和9%。因此在超声血流成像中应用最小均方误差正交解调算法,对于提高估计性能和降低运算量都有一定意义。 

Research on minimum mean square error demodulation algorithm for ultrasound color flow imaging

An algorithm of minimum mean square error (MMSE) quadrature demodulation is studied and applied in ultrasonic blood flow imaging. At first, an iterative form of the MMSE is established to obtain the amplitudes and phases of the in-phase and quadrature components of the echo signals by comparing the desired signals and the received signals. Then, the autocorrelation method is used to estimate the blood flow velocity using the signals obtained from the MMSE. The simulation results show that, for sinusoidal modulation signals with Gaussian noise of different energy and SNRs from 0.5 dB to 10 dB, the mean SNR of the output signals with this algorithm is higher 15 dB and 4 dB than the SNR with Hilbert algorithm and I/Q demodulation algorithm, respectively The simulation results of the flow imaging show that the required amount of multiplication has been reduced to 18% and 9% compared with the above methods when they have the comparable performance on blood flow velocity estimation. Therefore, the application of the MMSE for ultrasonic blood flow imaging has certain significance for improving the estimation performance and reducing the computation amount.