【摘要】 本文采用小波变换把毫米波辐射计的目标信号分解为一系列正交子空间上的投影，利用重构矩法分析信号特征在各子空间的分布，依次提取各子空间上的特征，然后融合这些特征，组成特征矢量，采用神经网络对目标信号特征矢量进行建模．用此方法对低信噪比的毫米波辐射计的信号进行仿真试验，结果表明该方法克服了传统方法对噪声和目标信号散布的敏感，取消了对目标和辐射计天线之间距离的限制，与最近邻法相比，该方法大大提高了识别率．更多还原

【Abstract】 The target signal of millimeter wave (MMW) radiometer was decomposed to a series of projections in orthogonal subspaces by wavelet transform. The features of MMW radiometer in each orthogonal subspace were analyzed and characterized by neural network. In addition, the results of simulation show that the target recognition method developed by this paper is effective when the SNR is low.更多还原