Real-time implementation of a Doppler signal spectral estimator using sequential and parallel processing techniques
Doppler signal spectral estimation has been used to evaluate blood flow parameters in order to diagnose cardiovascular diseases. The modified covariance (MC) method has proved to provide accurate estimation of the two spectral parameters employed in clinical diagnosis, namely mean frequency and bandwidth. The aim of the work reported in this paper is to determine an efficient real-time implementation of the MC spectral estimator by investigating several architectures and implementation methods. A comparative performance analysis of the implementation of the MC algorithm on several homogeneous and heterogeneous architectures incorporating transputers, digital signal processing (DSP) devices and a vector processor is reported. The performances of these architectures are evaluated and compared in terms of computational time (execution and communication) and gradient measurements. Analysis of the results reveals that both the homogeneous and heterogeneous DSP-based parallel architectures meet the real-time requirements.
doppler signal spectral estimator spectral estimation parallel processing heterogeneous architectures digital signal processing high performance computing homogeneous architectures real-time signal processing sequential processing