Blind parameter estimation algorithm for frequency-hopping signals based on compressed sensing

A blind parameter estimation algorithm for frequency-hopping signals based on compressed sensing was proposed，in order to solve the problem that the existing parameter estimation algorithms did not take into account the sparse structural characteristics of the signals in frequency domain.Firstly，the maximum cosine method was used to process the segmented compressed sampling signals，and the hopping frequency was estimated.Then，the atom matching algorithm was used to process the signal with the hopping point，and the frequency hopping instance time was estimated accurately.Then the hopping speed and hopping time were estimated.The experimental results show that the algorithm can significantly reduce the sampling data and computational complexity，while improving estimation accuracy.