针对压缩域跳频信号参数估计方法需借助测量矩阵寻找压缩采样数据的数字特征, 造成运算复杂度高, 且存在基不匹配的问题, 提出一种压缩域数字特征和原子范数的跳频信号参数估计方法。建立块对角化的测量矩阵, 实现信号分段压缩, 分析压缩采样数据的数字特征, 实现跳变时刻粗估计; 分离出未发生频率跳变的信号段, 利用原子范数最小化方法实现跳变频率的精确估计; 最后依据精确估计的跳变频率, 设计原子字典, 并在压缩域实现跳变时刻的精确估计。基于该算法的跳变频率估计性能高于基于压缩感知的跳变频率估计, 亦能精确估计跳频信号的跳变时刻。仿真结果显示, 在信噪比高于 -2 dB, 压缩比高于 0.5时, 基于该算法的归一化跳变频率估计误差低于 10-4, 归一化跳变时刻估计误差低于 10-2。

The parameter estimation of frequency hopping signal in compressed domain needs to find the digital characteristics of compressed sampling data by means of measurement matrix, which results in high computational complexity and base mismatch. In order to solve this problem, a method for parameter estimation of frequency hopping signal based on digital characteristics in compressed domain and atomic norm is proposed. Firstly, a block diagonalization measurement matrix is established to realize signal piecewise compression, and the digital characteristics of compressed sampling data are analyzed to roughly estimate hop timing. Then, the signal segments without frequency hopping are separated and the accurate estimation of hopping frequency is realized by minimizing atomic norm. Based on the accurate estimation of hopping frequency, an atomic dictionary is designed and the accurate estimation of hop timing is realized in compressed domain. The proposed method's frequency estimation performance is better than that based on grid compressive sensing, and the hop timing of frequency hopping signals can also be accurately estimated. Simulation results show that when SNR is higher than -2 dB and the compression ratio is higher than 0.5, the normalized hopping frequency estimation error based on the proposed algorithm is less than 10-4, and the normalized hop timing estimation error is less than 10-2.