Abstract
Owing to their effectiveness in underwater acoustic communication, linear frequency modulation (LFM) signals have been widely used in commercial and military applications. The existing approaches based on the traditional target function can estimate only single-component LFM signal parameters, as these approaches assume that the order of the optimal fractional Fourier transform (FRFT) is one. To overcome this limitation, we developed an LFM signal parameter estimation method that exploits the information entropy in its target function and optimizes the order of the FRFT using search algorithms, such as sequential search, multistage step search, and particle swarm optimization. Unlike existing solutions, the proposed technique can estimate both single and multicomponent LFM signal parameters. Experiments were performed to compare the proposed method with state-of-the-art techniques that rely on the maximum value, high-order cumulants, and fractional broadening target functions. The proposed approach was noted to be computationally more efficient and more accurate. Moreover, the parameter estimation precision of this approach was comparable to that of classic FRFT schemes.
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This work was supported by China’s Postdoctoral Science Foundation under Project no. 2020M673606XB.
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Liu, X., Xiao, B. & Wang, C. Optimal Target Function for the Fractional Fourier Transform of LFM Signals. Circuits Syst Signal Process 41, 4160–4173 (2022). https://doi.org/10.1007/s00034-022-01977-w
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DOI: https://doi.org/10.1007/s00034-022-01977-w