利用一组数字信号处理器对声纳信号进行白噪声频谱整形的实时多通道仿真

G. Varkey
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引用次数: 1

摘要

多通道声纳模拟器的信号吞吐量为n*f,其中n为通道数,f为采样频率。在可以忽略高阶项的简化假设下,每个采样周期信号生成的处理负载要求与我们希望模拟的信号源的数量成正比,例如p。因此,模拟器所需的总指令周期可以取为n*f*(a+p*q),其中q为生成一个源对应的信号值所需的平均周期数,a为环境噪声的周期数。对于现实场景模拟,p不能太小。同样,q随着要合并的效果的复杂程度的增加而增加。因此,总负载在千兆aflops的范围内。并行处理技术最适合处理如此大的吞吐量要求。开发信号噪声模拟器的一个有吸引力的设计方法是使用一组并行操作的标准DSP元件。这样的系统可以生成用户指定的场景,其中包含多个移动目标,每个目标具有多个色调和不同程度的调制。可以提供许多工具来根据用户的需要调整模拟器输出。这种系统的模块化设计允许通过以标准化硬件模块的形式添加并行处理节点来增加模拟复杂性。本文描述了开发SNS所需的噪声产生、反波束形成、滤波和相关算法,以及并行实现的同步问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time multi-channel simulation of sonar signals by spectral shaping of white noise using an array of digital signal processors
The signal throughput of a multi-channel sonar simulator is n*f where n is the number of channels and f is the sampling frequency. Under the simplifying assumption that higher order terms can be ignored, the processing load requirement for signal generation per sampling period is proportional to the number of signal sources - say, p - that we wish to simulate. Thus, the total instruction cycles required for the simulator may be taken as n*f*(a+p*q), where q is the average number of cycles needed to generate a signal value corresponding to a source and a is that for the ambient noise. For realistic scenario simulation, p cannot be too small. Similarly, q increases with increased sophistication of the effects to be incorporated. The total load therefore is in the range of GigaFlops. Parallel processing technology is most suited to handle such large throughput requirement. One of the attractive design approaches for the development of a Signal Noise Simulator is to use an array of standard DSP elements operating in parallel. Such a system can generate user specified scenarios with multiple moving targets, each with multiple tonals and varying degree of modulation. A number of facilities may be provided to tune the simulator output as required by the user. The modular design of such a system allows incremental building up of simulation complexity by the addition of parallel processing nodes in the form of standardised hardware modules. This paper describes the noise generation, inverse beam forming, filtering and related algorithms needed in the development of an SNS and the synchronisation issues of the parallel implementation.
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