Double-Parameter Ridge-Type Kalman Filter Based on Signal-to-Noise Ratio Test and Its Application in BDS Combined Orbit Determination with Satellite-Ground Observations
Abstract In this paper, the ill-conditioning diagnosis and processing of Kalman filter are combined. First, the ill-conditioning of Kalman filter and the disadvantage of ridge-type Kalman filter are analyzed. Then, the signal-to-noise ratio (SNR) statistic is introduced to measure how much each parameter suffers from the ill-conditioning. Accordingly, all parameters are divided into two parts: involved parameters and non-involved parameters. Then, the two parts of parameters are corrected with two ridge parameters of different sizes. This method is named double-parameter ridge-type Kalman filter and can reduce the bias introduced in ridge-type Kalman filter, while reducing the variance of the state parameter estimation. Finally, in the simulation, the new algorithm is discussed in detail with a specific mixed navigation constellation of 5 GEO, 3 IGSO 24 MEO. The results show that the new algorithm has higher orbit accuracy relative to ridge-type Kalman filter and the common Kalman filter.
LI Hao,GU Yongwei,GUO Shumei et al. Double-Parameter Ridge-Type Kalman Filter Based on Signal-to-Noise Ratio Test and Its Application in BDS Combined Orbit Determination with Satellite-Ground Observations[J]. jgg, 2018, 38(11): 1143-1148.
LI Hao,GU Yongwei,GUO Shumei et al. Double-Parameter Ridge-Type Kalman Filter Based on Signal-to-Noise Ratio Test and Its Application in BDS Combined Orbit Determination with Satellite-Ground Observations[J]. jgg, 2018, 38(11): 1143-1148.
