Based on extended incremental Kalman filter (EIKF) and adaptive incremental Kalman filter (AIKF)

the adaptive extended incremental Kalman filter (AEIKF) and analysis method were put forward

the key calculative steps were established. The measurement equations have many uncertainties and can't obtain precision parameters in actual environment(such as deep space exploration). Due to environmental factors and the instability of measurement equipments

the measurement data have unknown time-varying system errors in actual engineering

which leads to greater Kalman filtering error. Ultimately

the convergence of Kalman filter were reduced. The presented adaptive extended incremental Kalman filter method can successfully eliminate these unknown system errors. The method can estimate statistical characteristics of noise in real time and greatly improve the accuracy of filter. The method is simple to calculate and easy to apply in engineering.