Kalman Filter based on Matrix Accumulative Algorithm and its Application to Dynamic GPS Positioning
Yuehua Li · Fire Control and Command Control · 2006
Because of the computer word length,filter algorithm is prone to accelerate error.The error covariance will be out of symmetry,as a result,instability will appear in the value calculation.Generally,when the state variable dimension exceeds ten,the probability of result instability in the process of filtering increases.To deal with filter value calculation instability,people put forward and carry out lots of methods in practice such as self-adaptive filter,fixed amplitude filter and square root filter,etc.The disadvantages of these algorithms are fussy calculation and bad efficiency.This paper puts forward a new Kalman filter based on matrix accumulative algorithm.The Kalman filter algorithm is fast,efficient and stable.It decreases the computing volume.Simulation examples for dynamic GPS positioning shows their effectiveness.