Under the conditions of strong sea clutter and complex moving targets, it is extremely difficult to detect moving targets in the maritime surface. This paper proposes a new algorithm named improved tunable Q-factor wavelet transform (TQWT) for moving target detection. Firstly, this paper establishes a moving target model and sparsely compensates the Doppler migration of the moving target in the fractional Fourier transform (FRFT) domain. Then, TQWT is adopted to decompose the signal based on the discrimination between the sea clutter and the target's oscillation characteristics, using the basis pursuit denoising (BPDN) algorithm to get the wavelet coefficients. Furthermore, an energy selection method based on the optimal distribution of sub-bands energy is proposed to sparse the coefficients and reconstruct the target. Finally, experiments on the Council for Scientific and Industrial Research (CSIR) dataset indicate the performance of the proposed method and provide the basis for subsequent target detection.

中文翻译：

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改进的 TQWT 用于海洋运动目标检测

在强海杂波和复杂运动目标的条件下，探测海面运动目标极其困难。本文提出了一种新的运动目标检测算法——改进的可调Q因子小波变换(TQWT)。首先，本文建立了运动目标模型，并在分数阶傅里叶变换（FRFT）域中对运动目标的多普勒偏移进行了稀疏补偿。然后，基于海杂波和目标振荡特性的判别，采用TQWT对信号进行分解，利用BPDN算法得到小波系数。此外，提出了一种基于子带能量最优分布的能量选择方法来稀疏系数和重构目标。最后，