[The study of baseline estimated in digital XRF analyzer]

For the digital X-ray fluorescence analyzer, the voltage of the instability baseline will directly affect the performance of the instrument, resulting in decreased energy resolution. In order to solve this problem, Kalman filtering algorithm was used for pulse signal baseline estimate in the digital X-ray fluorescence. Whether using the classic Kalman filter, or the simplified sage-husa, or the improved sage-husa, their baseline filtering effects were all poor. So, it is necessary to improve and optimize existing algorithms. The method of Double-Forgotten was put forward to establish a new model of adaptive Kalman filter algorithm based on the sage-husa. The experiment results show that a very good filtering effect was obtained using the mathematical model of the baseline filter. The algorithm solved the problem of filtering divergence, avoided slow convergence of baseline and realized the pulse baseline restoration, and improved the instrumental energy resolution.