Real-time signal-processing method of synthetic aperture sonar based on cluster processor and system

Abstract

The invention provides a real-time signal-processing method of synthetic aperture sonar based on a cluster processor and a system. The system comprises a data-collecting system, a cluster processor, a storage device, a display platform, and the like and finishes subtasks, such as preprocessing original data, comprehending motion, compressing pulses, imaging a delay table, processing image data, and the like so as to processing real-time signals of the synthetic aperture sonar. The real-time signal-processing method of the synthetic aperture sonar based on the cluster processor and the system use the cluster processor as a platform and utilize the multi-processor multi-core characteristics of the cluster processor for the parallel processing of a plurality of threads based on a shared memory so that various subtasks are started in an independent thread mode and are synchronized by semaphores to form a processing mode of a multi-stage pipeline structure. The system is stable and reliable to work and can greatly shorten the imaging time on the premise that high resolution is ensured so as to further satisfy the real-time imaging need of the synthetic aperture sonar.

Description

technical field [0001] The invention relates to the field of sonar signal processing, in particular to a synthetic aperture sonar (SAS) real-time signal processing method and system based on a cluster processor. Background technique [0002] Synthetic aperture sonar (Synthetic Aperture Sonar: SAS) uses the movement of the small-sized matrix in the azimuth direction to form a virtual large aperture, and obtains high-resolution sonar images by coherently processing the sonar echo signals at different positions. [0003] At present, synthetic aperture sonar imaging algorithms are mainly divided into two categories: time-domain algorithms and frequency-domain algorithms. The time-domain imaging algorithm has the advantages of clear physical meaning, small memory footprint, direct motion compensation and multi-subarray imaging, etc., but has the disadvantages of low computational efficiency and high system sampling rate requirements; the frequency-domain imaging algorithm has hig...

AI Technical Summary

Problems solved by technology

However, the dedicated digital signal processor is expensive, and the software development cycle is long, and the scalability is poor. With the update of the dedicated digital signal processor, the eliminated resources cannot be used, resulting in idle hardware resources and waste of funds.

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