In the modern information society, high-precision clocks are particularly important in the fields of electric power, communications, aviation, and finance, and have very strict objective requirements in terms of frequency accuracy. Currently, the technology of using GPS satellite clock sources to synchronize local clocks has become one of the mainstream methods for generating high-precision clocks at home and abroad. The core idea of this technology is to use the satellite clock to tame the local clock. Due to the development and application of 5G, the accuracy of the system's punctuality have higher requirements, Through analysis, it is found that the combination of BP neural network and PID control can be used to optimize the control of the constant temperature crystal oscillator and improve the precision of punctuality. Finally, the simulation results show that the method has a significant effect in improving the accuracy of punctuality.

Because the received signal strength indication (RSSI) ranging technology has problems with line-of-sight and multipath effects in indoor environments, the actual received RSSI value is unstable. In order to reduce the influence of RSSI value volatility on ranging accuracy, according to the fluctuation characteristics of the signal itself, a combined filtering method of Gaussian, median and mean is proposed to process the collected RSSI values, and the least squares method is used to fit and optimize the ranging parameter. Experiments show that using the RSSI intensity value processed by the combined filtering method to establish a model to achieve ranging, the maximum absolute error is about 2 m, and the absolute average error is about 0.763 m. The accuracy of the ranging has been significantly improved, and the ranging model has been optimized.