波形
声纳
计算机科学
声学
信号(编程语言)
频率调制
海洋哺乳动物与声纳
电子工程
电信
工程类
带宽(计算)
人工智能
物理
程序设计语言
雷达
摘要
Cognitive sonar systems leverage information gathered from earlier sensing interactions with the acoustic environment to adapt its system parameters for optimal performance. Of the many system parameters, an active cognitive sonar system could adapt, the acoustic signal projected into the medium, also known as the transmit waveform, has a profound impact on system performance as many of the physical characteristics of the acoustic environment are contained in the return echo signal. This research examines utilizing multi-tone sinusoidal frequency modulated (MTSFM) waveforms as an adaptive transmit waveform model for use in active cognitive sonar systems. The MTSFM waveform’s frequency and phase modulation functions are composed of a finite set of weighted sinusoidal harmonics. The weights for each harmonic are utilized as a discrete set of design coefficients. Adjusting these coefficients results in constant amplitude, spectrally compact FM waveforms that possess a wide variety of performance characteristics, which in the past required a diverse set of waveform types to achieve. The adaptability of the MTSFM waveform model enables a cognitive sonar system to generate waveforms that are finely tuned for the novel scenarios and environments that it may encounter.
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