LAUSR

There may exist many high-energy particles in spacecraft, so the FPGA circuits design needs corresponding sensitivity analysis and security reinforcement of anti-SEE (Single-event effects). However, it may be impractical to perform such measures to all modules of FGPA circuits due to limited resources. To identify the key modules which have a vital impact on the design and operation of FPGA circuits in spacecraft, this paper presents a novel scheme based on complex network for modeling the modules considering both the circuit functional structure and signal interaction relationship between modules. First, complex networks like MSN (Module Structure Network) and SFN (Signal Flow Network) are established to identify modules by treating each module as a node, and indicators including degree centrality (DC), betweenness centrality (BC), clustering coefficient (CC), etc., are calculated. Then, an entropy-weight method (EWM) is utilized to calculate the indicators comprehensively for identifying key modules. Next, network efficiency and sensitivity analysis are performed for failure modes. Finally, a case study is carried out, demonstrating the effectiveness of the proposed scheme for the key module identification. This work provides useful technical support for engineers in spacecraft FPGA circuits design and performance enhancement.