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地铁ASK低频信号由于频率间隔较小,在进行高精度检测时需要采样时间较长,且计算量很大,计算时间较长,导致识别时间无法满足要求。为解决实时高精度提取地铁ASK信号低频信息的问题,提出一种从频域进行频谱分析检测可兼容不同占空比信号的新方法,该方法将ZFFT技术,频率能量重心校正技术结合,有效降低了算法的计算复杂度,仿真和实地测试结果均符合技术要求。
Subway ASK low-frequency signal due to the smaller frequency interval, the need for high-precision detection of sampling time is longer, and a large amount of computation, calculation time is longer, resulting in recognition time can not meet the requirements. In order to solve the problem of extracting low frequency information of subway ASK signals in real time with high accuracy, a new method of spectrum analysis and detection compatible with different duty cycle signals in frequency domain is proposed. This method combines ZFFT technology and frequency energy center of gravity correction to reduce effectively The computational complexity of the algorithm, simulation and field test results are in line with technical requirements.