An adaptive incremental particle filter (AIPF) model was put forward

and its concept

model

basic equations and key calculative steps were given. For the measurement data with unknown system errors in many actual engineering (such as deep space exploration) and the considerable filter errors

accurate measurement model cannot be established. The presented AIPF method applied the accurate incremental particle filter model to automatically conduct adaptive adjustment of the number of particles

so the effects of these unknown measurement system errors and the lack of particles were eliminated. This method can automatically adjust the particles (sample points) and finally improve the nonlinear filtering accuracy. In simulation

the mean and covariance of filtering error decrease by 3.8% and 19.6%

respectively. The method can effectively improve the performance of filter

so it can be easily applied to engineering with simple calculation process.