Abstract Exact prior information is of great importance to both classical Kalman filtering and adaptive filtering. In applications concerned with Kalman filtering, prior model is generally determined arbitrarily and experientially, lacking methodology. Taking the GNSS/INS integrated navigation as an example,the stochastic character of errors, which is subsequently transformed into proper prior information, is obtained from inertial data based on timefrequency analysis. This method avoids the complicated tuning in utilizing Kalman filtering.
Gan Yu ,Sui Lifen ,Zhang Qinghua et al. REFINING PRIOR FILTERING MODEL OF GNSS/INS INTEGRATED NAVIGATION BASED ON TIME-FREQUENCY ANALYSIS[J]. , 2013, 33(1): 108-112.
Gan Yu ,Sui Lifen ,Zhang Qinghua et al. REFINING PRIOR FILTERING MODEL OF GNSS/INS INTEGRATED NAVIGATION BASED ON TIME-FREQUENCY ANALYSIS[J]. jgg, 2013, 33(1): 108-112.
