基于随机采样法的光生混沌雷达信号周期性减弱研究

激光器产生混沌信号时,由于腔长原因使产生的信号具有周期性,若将该信号应用于雷达系统,易被识别与攻破。针对上述问题,文中提出采用随机采样法对原始混沌序列进行不等间隔随机采样,讨论分析了采样前后混沌的自相关和功率谱性能,结果显示采样后混沌信号自相关及功率谱的周期性均明显减弱并逐步消除。搭建基于光生混沌的调频雷达信号模型,理论推导分析了信号的频谱和模糊函数。结果表明,混沌自相关的旁瓣较原始混沌序列明显降低,功率谱也更加平坦,可获得sinc函数频谱和图钉状的模糊函数,该信号可以应用于雷达探测系统。

A Study on Periodicity Weakening of Photonic Chaotic Radar Signal Based on the Random Sampling Method

When the laser generates the chaotic signal, the signal will have the periodicity because of the cavity length. That is easy to be identified and attacked when the signal is used for radar system. To solve this problem, a random sampling method is then proposed in this paper, which makes original chaotic sequence randomly sampled by different intervals. Autocorrelation and power spectrum analyses of origin and sampled chaotic sequences are discussed and analyzed. The results show that the periodicity of chaos autocorrelation and the spectrum is weakened and even disappeared; The frequency modulated waveform model based on photonic chaos is put forward for radar systems. Then the spectrum and ambiguity function are deduced and analyzed theoretically. Simulations results show that the side-lobes of sampled chaos autocorrelation are greatly lower than original chaos and power spectrum gets flatter as well. The designed radar signal not only has a sinc function spectrum but also has a thumbtack ambiguity function in accord with theoretical analysis, which proves that this signal can be used for radar system.