海杂波环境中基于混沌的目标检测

Target detection in sea clutter environment based on chaos

介绍了基于混沌理论的海杂波分析方法,计算了加拿大McMaster大学IPIX雷达实测海杂波数据的各种混沌特征量,分析了该数据的混沌特性。分析结果表明,该数据在一定程度上具有混沌特性。设计了混沌检测器,该检测器采用径向基函数神经网络来重建海杂波的混沌动力结构,即建立海杂波的精确预测模型,并通过设定合适的预测误差门限来检测掩埋在海杂波中的微弱目标。计算结果验证了该检测器的可行性。

The method to analyze sea clutter based on chaos theory is presented. Chaotic characteristic invariants of the sea clutter data from the IPIX radar of McMaster University, Canada, are computed and analyzed. The results show that the sea clutter can be considered to be chaotic in some extent. A chaos based-detector is designed. The detector utilizes radial basis function neural network to reconstruct the chaotic dynamic system, namely, to build a precise prediction model, then set an appropriate threshold of the prediction errors to detect the targets buried in the sea clutter. The results show the feasibility of the detector.