中文摘要：

针对复杂电磁环境定性分析和定量分级问题，提出基于广义S变换与PNN（概率神经网络）的电磁环境复杂度评估方法．应用广义S变换对电磁环境中受干扰的样本信号进行时频分析，同步提取时频域时域占用度，频域占用度和能量占用度评估参数，分析了各参数的物理意义，并给出了各评估参数的计算公式．同时增加频率重合度、调制格式相似度和背景噪声强度等评估参数，利用获取的参数训练PNN，并进行分类．仿真实验证明基于广义S变换与PNN的电磁环境复杂度评估方法在背景噪声大、训练样本数少的条件下能有效提取评估参数，并对电磁环境复杂度进行有效合理评估．

英文摘要：

For electromagnetic environment complex evaluation, a novel evaluation method was proposed based on S-transform and probabilistic neural network （PNN）. S-transform was applied to perform time-frequency analysis on the electromagnetic environment disturbance samples, the evaluation parameters such as time occupation,frequency occupation and energy occupation of the samples were extracted synchronously, physical interpretation of each parameter was analyzed, and the calculation formulas of them were shown. At the same time, frequency coincidence, modulation similarity and background noise intensity were selected as important evaluation indicators. These parameters were then used to train a PNN which was adopted to evaluate environmental complexity. The simulation results show that the proposed method has integrity of parameter extraction and relatively high evaluation accuracy, and it can also give excellent evaluation for high level noises hackground and small training set.