In the traditional single particle fault injection experiments (SPFIE), when the target configuration register for fault injection is selected, the state of the configuration register is inverted directly without considering the actual operating environment of the target design, such as the distribution of particles around the orbit, the crash frequency of particles on the target design and the electronic characteristics of the design itself. So, the soft failure rate obtained based on this method cannot properly reflect the actual situation of the target design in a specific space environment. To address this issue, this work presents a fault injection signal generation method considering both particle distribution in space and the circuit electronic characteristics. Because the real particle distribution data is less and the information contained is single, a novel data expansion method based on the Gaussian cloud model is proposed. This method makes full use of small sample information and the expanded data using this method maintain the same distribution as the original sample data with more information. We take the particle data collected by the detector mounted on Tiangong-1 as the simulation scenario to validate this novel expansion method. Simulation results demonstrate the feasibility and effectiveness of the proposed expansion method. The SPFIE using the proposed fault injection signal generation method improves the authenticity of the experiment results and the SRAM FPGA design soft failure rate estimated according to experiment result is closer to the real situation in the space environment.

在传统的单粒子故障注射实验（SPFIE）中，选择用于故障注射的目标配置寄存器时，配置寄存器的状态直接反转，而不考虑目标设计的实际操作环境，例如周围的粒子的分布轨道，目标设计上粒子的碰撞频率以及设计本身的电子特性。因此，基于这种方法获得的软故障率无法正确反映目标设计在特定空间环境中的实际情况。为了解决这个问题，这项工作提出了一种故障注入信号产生方法，该方法考虑了空间中的粒子分布和电路的电子特性。由于实际的粒子分布数据较少，且包含的信息单一，因此提出了一种基于高斯云模型的数据扩展新方法。该方法充分利用了少量样本信息，使用该方法扩展的数据与具有更多信息的原始样本数据保持相同的分布。我们以安装在天宫一号上的探测器收集的粒子数据为模拟场景，以验证这种新颖的扩展方法。仿真结果证明了该扩展方法的可行性和有效性。使用提出的故障注入信号生成方法的SPFIE提高了实验结果的真实性，并且根据实验结果估计的SRAM FPGA设计软故障率更接近于空间环境中的实际情况。