When the electronic equipment works, the electromagnetic property is greatly affected by temperature. How to reconstruct the three-dimensional temperature field of electronic equipment with sparse sensor measurement data in real time is the key problem to realize health monitoring and electromagnetic property control. Aiming at this problem, taking active phased array antenna (APAA) as the research object, a temperature field temporal spatial reconstruction method is proposed based on proper orthogonal decompositionregularized least square-Kalman filter (POD-RLS-KF), which fuses simulation data and sparse sensor measurement data. Firstly, POD is used to separate the simulated transient temperature field data into temporal mode coefficients ( TMC) and spatial basis functions ( SBF). Secondly, the data collected by sparse sensors are used to carry out the optimal estimation of the TMC in real time with RLS and KF methods. Finally, the temperature field is reconstructed in real time combining the SBF and updated TMC. The simulation and experiment results show that when the simulation state is different from the actual state, the method can calculate the three-dimensional temperature field of the antenna in real time according to a small amount of data provided by sparse sensors. Compared with existing reconstruction methods, the proposed method shows better reconstruction accuracy and noise suppression ability, and the average of the root mean square error of the reconstruction temperature field is 7. 18% of that of Kalman filter-linear stochastic estimation (KF-LSE) method and 1. 53% of that of the Gappy method.