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海杂波的奇异谱分析不仅能从理论上揭示海洋表面的动力学机理,同时也是对海探测雷达的关键技术之一.本文提出基于小波leaders的海杂波时变奇异谱分析方法,将时间信息引入海杂波的奇异谱分析之中,从而实现动态的解析描述海杂波随时间变化的奇异谱特性.在理论上,通过信号自身加窗,将时间信息引入传统的奇异谱(或称多重分形谱),实现了对海杂波时变奇异谱分布分析;在算法上,充分利用了小波leaders技术对于多种奇异性的提取能力(包括chirp奇异性和cusp奇异性),通过对时变奇异性指数和时变尺度函数的Legendre变换,实现对海杂波时变奇异谱分布的计算;在应用部分,采用经典的多重分形模型——随机小波序列(RWC)以及三级海态条件下连续波多普勒体制雷达海杂波进行仿真分析,实验结果表明:1)基于小波leaders的奇异谱分布能跟踪海杂波的时变尺度特性,有效展示其时变奇异性谱分布;2)算法具有较好的负矩特性和统计收敛性.该方法能为复杂非线性系统及随机多重分形信号分析提供参考.
The singular spectrum analysis of sea clutter can not only theoretically reveal the dynamic mechanism of ocean surface but also one of the key technologies for sea detection radar.In this paper, we propose a sea clutter-based singular spectrum analysis method based on wavelet leaders, The information is introduced into the singular spectrum analysis of the sea clutter to realize the dynamic analysis of the singular spectrum characteristics of the sea clutter over time.In theory, the signal is introduced into the traditional singular spectrum Multifractal spectrum), to achieve the analysis of singular spectral distribution of the sea clutter; in the algorithm, take full advantage of the ability of wavelet leaders for a variety of singularity extraction capabilities (including chirp singularity and cusp singularity) Legendre transform of singularity index and time-varying scale function is used to calculate the singular spectrum distribution of sea clutter. In the application part, the classical multifractal model - random wavelet sequence (RWC) and the third-order sea state condition The simulation results show that: 1) the singular spectral distribution based on wavelet leaders can track the time-varying scale characteristics of sea clutter, Singularity varying the spectral distribution of the time; 2) algorithm has good negative torque characteristics and convergence of the statistical method can be complex and nonlinear systems multifractal random reference signal analysis.