该文研究了海杂波在分数阶Fourier变换(FRFT)域的分形特征,提出了一种基于分形特征差异的联合动目标检测方法.首先,分析了海杂波数据在FRFT域的统计特性,通过对不同极化方式下分形曲线的仿真分析,得到海杂波在FRFT域满足自相似性.其次,给出了分形参数的提取方法和无标度区间,并分析了变换阶数对分形参数估计的影响.最后,利用临近距离单元或临近时刻的雷达回波信号在FRFT域的分形维数和斜距的差值作为检测统计量,经不同极化方式下的海杂波数据验证,表明算法不仅具有良好的微弱动目标检测能力,而且能够准确估计目标的运动状态.%A new moving target detection algorithm is proposed based on the joint fractal properties discriminant of sea clutter in FRactional Fourier Transform (FRFT) domain. At first, statistical characteristic of sea clutter data in FRFT domain is analyzed and simulations of fractal curves in different polarizations are conducted, which indicates the self-similarity feature. Then, determination method of fractal parameters and scale-invariant interval is given and influence of transform order on the estimation of fractal parameters is also discussed. Finally,differences of fractal dimension and intercept in FRFT domain, which are calculated from adjacent range bin or time series of radar echo, can be used as test statistic. Real sea clutter in different polarizations is used for verification and the results present that the proposed algorithm has good performance for weak moving target detection and can also give high estimation accuracy of moving conditions.
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