基于循环谱理论的弱信号检测及载频估计

Weak signal detection and carrier frequency estimation based on cyclic spectrum theory

弱信号检测及载频等参数估计对于军用电子对抗以及民用频谱监管都具有重要的意义.由于无线通信环境的复杂性和不可预知,在低信噪比条件下,传统载频估计方法都难以实现预期效果.基于循环谱理论,根据常见通信信号与平稳噪声具有不同的谱相关特性,建立循环平稳模型,利用循环谱分析的方法估计了低信噪比条件下BPSK的载波频率.在有限数据条件下,分析了窗函数对时域平滑周期图法估计性能的影响,从而选取合适的数据分段长度,选用更加适合的窗函数,分析经过时域平滑后的BPSK信号载频估计精度.最后仿真实验实现了时域平滑FFT累加算法在低信噪比条件下对BPSK信号的载波频率准确估计,验证了算法的有效性.

Weak signal detection and carrier frequency estimation are important significance for military electronic warfare and civil spectrum supervision. At low SNR circumstance, traditional methods of carrier frequency estimation make it difficult to adapt to the complexity and unpredictable of wireless communication environment. Based on cyclic spectrum theory, property of spectral correlation for communication signal and stationary noise was analyzed, and a cyclostationary model was established. Cyclic spectrum analysis was used to estimate the carrier frequency of BPSK under low R SN . Under the condition of finite data, the influence of window function on the estimation performance of time smoothing symmetrical periodogram was analyzed. Thus, the best taper point and window function was selected. The estimation performance was analyzed for the cyclic spectrum by time smoothing symmetrical periodogram. Finally, simulation experiments are carried out to achieve the accurate estimation of carrier frequency of BPSK signals at low R SN . Simulation results showed that the proposed algorithm was effective.