INS/CNS integrated navigation is widely used in high-precision autonomous navigation systems for aircrafts, missiles and other space vehicles, which has many advantages such as high autonomy, strong anti-jamming ability and high accuracy. However, since it is relatively difficult to validate the star sensors often used in celestial navigation on the ground, with high cost, limited by the test environment and other problems, it is not suitable for the rapid validation of INS/CNS integrated navigation algorithms. Therefore, this paper designs a scalable automated simulation framework for the testing and validation of INS/CNS integrated navigation algorithms, generates simulation data based on the motion path, and carries out automated testing and evaluation of the algorithms through the simulation data. Based on the framework design, new types of sensors can be freely added to the simulation framework. The simulation framework does not require sensor hardware, which effectively improves the verification speed and reduces the testing cost of the INS/CNS integrated navigation algorithms.