Improved scheduling algorithm for signal processing in asynchronous distributed ultrasonic total-focusing-method system.

Abstract

Compared to the conventional ultrasonic phased-array system, a large-element phased-array system employing the total focusing method (TFM) can yield improved image resolution and accuracy, providing more flexible scanning methods and image merging functionality. In order to meet various forms of ultrasonic multi-group scanning, an architecture for multi-group scan integration called the "asynchronous distributed ultrasonic TFM system" is proposed, and a novel scheduling algorithm called "the sum of start time and processing time adjacent (SSPA) algorithm" is presented. The architecture adds a focus and group scheduler (FGS) and signal processing scheduler (SPS) to the traditional ultrasonic phased array system and constructs a signal processing arbitration (SPA) with several signal processing modules (SPMs). The FGS provides the focus parameters, pixel memory range, and number of pixels in each group. The SPS controls the SPA for the ultrasonic scanning data obtained from the elements, with SPM-sharing output data; hence, the optimal priority order and SPM assignment are realized, enabling switching of reading operations among the first-in-first-out memories for signal processing and minimal time-slot waiting. The SSPA algorithm is used to solve the job-shop scheduling problem with start time, which considers the processing time and start time, in order to reduce the time slot after each scheduling using adjacent operations. Therefore, the architecture enhances the flexibility of the multi-group scan, and this algorithm decreases the makespan, achieving higher efficiency compared to conventional scheduling algorithms. The reliability and validity of the algorithm are substantiated after its implementation using FPGA technology. The SPM utilization rate and the real-time performance of the ultrasonic TFM are improved. Thus, the proposed algorithm and architecture have considerable potential application in multi-sensor systems.