Affiliation:
1. School of Artificial Intelligence, Chongqing University of Education, Chongqing 400065, P. R. China
Abstract
A new nonlinear beamformer named Double-Stage Delay Multiply and Sum (DS-DMAS) has recently been proposed as a variant of the Delay Multiply and Sum (DMAS) algorithm. DS-DMAS expands DMAS into a summation of multiple terms and considers this summation as Delay and Sum (DAS). In order to address the shortage of DAS, DS-DMAS replaced the DAS with DMAS. However, the construction of the new signal in the DS-DMAS algorithm still employs the DAS method. While DAS is a well-established and reliable method, its output is solely dependent on the signal amplitude. Therefore, signal similarity-based methods such as the Coherence Factor (CF) and the Sign Coherence Factor (SCF) have been proposed to weigh the DAS output and optimize its performance. Taking this into consideration, we incorporated the CF and SCF to weigh each newly generated signal in DS-DMAS, resulting in the Coherence Factor-based Double-Stage Delay Multiply and Sum (DS-DMAS-CF) and the Sign Coherence Factor-based Double-Stage Delay Multiply and Sum (DS-DMAS-SCF) approaches. Our focus is primarily on comparing the performance of DS-DMAS-CF and DS-DMAS-SCF. The results indicate that DS-DMAS-SCF exhibits better noise suppression capabilities compared to DS-DMAS-CF.
Publisher
World Scientific Pub Co Pte Ltd