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针对宽带条件下多跳频信号的参数估计问题,利用多跳频信号在空间频率域上的稀疏性,提出了基于稀疏贝叶斯重构的空间频率估计方法.通过重构信号获得信号瞬时频率估计,在此基础上完成了波达方向信息估计.为了提高低信噪比条件下参数的估计性能,采用形态学滤波的方法对得到的时频图进行修正,在修正的时频图上完成了信号频率集和跳周期的精准估计.仿真实验表明:该算法在信噪比低于0dB的情况下仍能够取得良好的估计性能.
In order to solve the parameter estimation problem of multi-frequency-hopping signals under wideband conditions, a spatial frequency estimation method based on sparse Bayesian reconstruction is proposed by taking advantage of the sparsity of multi-frequency-hopping signals in the spatial frequency domain. The instantaneous frequency In order to improve the estimation performance of the parameters under low signal-to-noise ratio, the morphological filtering method is used to correct the obtained time-frequency map and to complete the correction on the time-frequency map The accurate estimation of the signal frequency set and the hop period is given.The simulation results show that this algorithm can still obtain good estimation performance under the condition that the SNR is lower than 0dB.