为了在非协作情况下，对跳频信号的频率跳变时刻进行精确快速估计，提出一种基于压缩采样值的跳频信号跳变时刻快速估计算法。该算法首先通过压缩感知技术以远低于奈奎斯特采样定理要求的速率对跳频信号进行整周期滑动采样，然后根据不同时刻相邻两跳信号窗函数的特点，重构信号在傅里叶正交基上的2 个权值最大的稀疏系数，并由此对前后两跳持续时间进行判断，从而对跳频信号的跳变时刻进行参数估计。仿真结果显示，该算法能有效地估计跳频信号的跳频转换时刻，且实时性优于现有时频估计类算法。

An algorithm for rapidly estimating the frequency hopping transition time based on compressive samplings is proposed, in order to estimate the frequency hopping transition time of the Frequency-Hopping signal accurately and rapidly under the condition of non-cooperation. Firstly, the frequency hopping signal is acquired by slide sampling, at a sampling rate far slow than that of the Nyquist sampling. Then the first two sparse coefficients with the maximum weight of Frequency-Hopping signal are reconstructed. Based on the relationship between the different slide time and the time of the hops before and after, the frequency hopping transition time is estimated. Simulation results show that this algorithm can estimate the hopping transition time of Frequency-Hopping signal effectively, and its speed is superior to traditional algorithm based on time-frequency analysis.