基于多通道数据融合的跳频信号频率跳变时刻估计算法

针对低信噪比条件下宽带高速跳频信号的参数估计问题，提出一种多通道数据融合跳频信号频率跳变时刻估计算法。该算法利用无盲区数字信道化预处理实现宽带跳频信号的全概率、全盲接收，通过数据融合得到一路包含全部频率跳变信息的参考信号，并利用该参考信号进行最大似然估计得到频率跳变时刻精确估计值。给出了所提出跳变时刻估计算法的Cramer-Rao下界并进行实验仿真。理论推导和仿真结果表明:针对一定的输入信噪比，适当选择信道化数和估计时间可实现较高的估计精度。在0dB信噪比条件下，采用16通道数字信道化处理，估计方差小于10-3。 

Hop Timing Estimation Algorithm for Frequency Hopping Signals based on Multi-Channel Data Fusion

A new hop timing estimation algorithm for frequency hopping signals based on non-blind zone channelization preprocessing and data fusion is proposed to solve the parameters estimation problem for wide-band high speed frequency hopping signals in low signal-noise-ratio (SNR) circumstances. This algorithm can blindly receive wide-band frequency hopping signals with full probability using non-blind zone channelization preprocessing method, and multi-channel transition signals are obtained, data fusion method is used to generate the reference signal which has the same transition information as the original multi-channel transition signals, then maximum likelihood estimation method is used to estimate hop timing. Theoretic Cramer-Rao lower bound of proposed algorithm is also analyzed. The analysis and simulation results show that the hop timing estimation variance performance depends on signal-noise-ratio condition, channel numbers and hop numbers used. The estimation variance is less than 10-3 with channel number equals to 16 in 0dB SNR circumstances.