Improved H∞ Filtering Method for Pulsar Position Error Estimation

Considering that under the influence of cosmic rays, the statistical characteristics of noise in the pulsar position error estimation model are unknown, not Gaussian white noise. Therefore, in order to estimate the pulsar position error more accurately, the noise in this model is set to colored noise. The conventional method of processing colored noise is to use the \( H_{\infty } \) filtering algorithm, but the filtering parameter of the algorithm is artificially set to a fixed value, which makes the filtering to have a large conservative problem. Therefore, in order to balance the accuracy and robustness of the system, this paper analyzes the existence condition of the \( H_{\infty } \) filter and uses the matrix inequality theory to set the filter parameter \( \upgamma \) as the function of filtering the new interest, so that the filter parameter \( \upgamma \) can be adjusted and improved between the filtering precision and the robustness, and better realize the estimation of the pulsar position error. Through simulation verification, under the influence of colored noise, the algorithm proposed in this paper is superior to Kalman filtering and \( H_{\infty } \) filtering in estimating the pulsar position error.