跳频信号的归一化多普勒频差最大似然估计

Maximum Likelihood Estimation of Normalized Doppler Frequency Difference of Frequency Hopping Signals

针对双站定位涉及的跳频信号多普勒频差估计问题,提出了归一化的频差最大似然估计算法,利用两个定位站接收到的跳频脉冲串信号,构建一个关于基准跳频频率多普勒频差的似然函数,通过网格搜索得到使似然函数最大的多普勒频差估计,既解决了跳频信号在不同跳频频率上多普勒频差不一致的问题,又充分利用在不同频率的脉冲串信号提高了多普勒频差估计精度。通过仿真对算法的性能进行了评估,结果表明,与基于子空间的算法比较,在脉冲数达到240个时,所提算法执行效率提升30%以上。

The maximum likelihood estimation algorithm for frequency hopping( FH) signals is proposed for solving the problem of Doppler frequency difference estimation in dual station’s positioning system.A likelihood function is created to find the frequency difference which maximizes the likelihood function by grid search.By this way,the problem of Doppler frequency difference of FH signal at different frequency is solved and the pulse train signals are used to improve estimation accuracy.The performance of the algorithm is evaluated through simulation.Compared with that of the algorithm based on sub-space,the execution efficiency of the proposed algorithm is raised by more than 30% when FH pulses reach 240.