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This paper focuses on the inverse synthetic aperture radar (ISAR) imaging of nonuniformly rotating targets under low signal-to-noise ratio (SNR) environment, and an effective ISAR imaging algorithm based on a novel parameter estimation method is proposed. For nonuniformly rotating targets, the received signals in a range cell can be modeled as multicomponent cubic phase signals (CPSs) after the migration compensation and translation-induced phase error correction. For the CPS model, the chirp rate (CR) and quadratic chirp rate (QCR) will induce image defocus. To estimate the CR and QCR of CPS, a novel parameter method is presented. The basic idea of this method is to design a third order autocorrelation function (TOAF) which enable coherent accumulation of the signal energy in both of the time and lag-time domain. Compared with several state-of-the-art algorithms, the proposed method has a significant anti-noise performance improvement, while offering a proper computational complexity. The effectiveness and the superiority of the proposed ISAR imaging algorithm have been demonstrated through several simulation results.