In general, the information of mass properties is required to control a spacecraft. The mass properties, mass and inertia, are changed by some activities, e.g., consumption of propellant, deployment of solar panel, sloshing, etc. Various estimation methods have been studied to obtain the accurate mass properties. The gyro-based attitude data including noise and bias needs to be compensated for improvement of attitude control accuracy. In this paper, several filtering methods have been investigated for the inertia estimation of STSAT-3 and a new method is suggested for better performance. First, we filter the gyro noise with the extended Kalman filter, and then estimate the inertia using the batch method. The estimated inertia is then fed back to nominal values of the extended Kalman filter. This process is iterated until the estimated properties are converged. The performance of the suggested method has been verified for the case of STSAT-3, Korea Science Technology Satellite.