为了提升海杂波中小弱目标检测能力,通过研究海杂波在空域和时域上的动态特性,提出基于空时混沌分析的海面小弱目标检测方法.首先,在海杂波混沌动力系统相空间重构的基础上提取海浪序列图像的空域混沌参数和时域混沌参数,验证海杂波在空域与时域具备混沌性;然后,采用径向基函数神经网络学习海杂波的空域混沌重构函数、时域混沌重构函数和空时耦合系数,联合空域和时域混沌特性综合重构海杂波在时间与空间上的传播规律.多种复杂度海面目标检测试验结果表明,与空域混沌和时域混沌方法相比,预测误差可降低10%,检测概率可提高20%,基于空时混沌重构的海杂波抑制能力与小目标检测性都得以显著提升.%To improve the performance of the clutter suppression and small target detection,a detection algorithm for a small target in sea clutter was proposed,based on the spatio-temporal chaos analysis.First,the sea clutter phase space was reconstructed as a chaotic dynamical system,and the chaotic parameters of the sea clutter sequence image were extracted to verify that the sea clutter owns chaotic properties in the spatial and temporal domains. Furthermore, the spatial chaotic reconstruction function,the temporal chaotic reconstruction function,and the space-time coupling coefficient were estimated by the radial basis function neural network.Finally,the spatial and temporal chaotic functions were integrated jointly to reconstruct the spreading regularity of the moving sea clutter.Some experiments were induced on the small target in various fluctuating sea clutter,and the experimental results show that the proposed algorithm,can improve the performance of the sea clutter suppression and enhance the small target detection ability,with the prediction error reduced by 10% and the detection probability increased by 20%.
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