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

In this paper, a parameter estimation algorithm for wideband multiple FH (multi-FH) signals based on compressed sensing (CS) is proposed. Our proposed algorithm is aiming at the condition of existing synchronous and asynchronous frequency-hopping (FH) signals, and meanwhile considering the frequency switching time. Firstly, by segmenting the received signals into several compressed measurement signals, the sparsity is estimated through the compressed spectrum sensing algorithm without reconstructing signals. Secondly, the improved orthogonal matching pursuit (OMP) algorithm is used to the roughly estimate the frequency of multi-FH signals, and the frequency is accurately estimated by frequency clustering algorithm, then the hopping time and hopping speed are roughly estimated through time-frequency analysis. Finally, inspired by the traditional sliding window algorithm, the adaptive sliding window (ASW) algorithm is proposed, which can adaptively adjust the window length and step size so as to increase the accuracy of the hopping time and hopping speed estimation. Numerical simulations demonstrate that the algorithm proposed in this paper can precisely estimate the parameters of multi-FH signals at low signal-to-noise ratio (SNR) and can significantly reduce the algorithm complexity. (c) 2019 Elsevier B.V. All rights reserved.