Abstract:Person tracking problem under the indoor environment often face light

occlusion and similar color interference

in order to enhance the tracking stability and accuracy in the situation

this paper proposes a root mean square (RMS) unscented H-infinity filtering method in Considering interference noise perturbation. First of all

Unscented transformation is used to replace the complex Jacobi matrix calculation under the framework of extended H-infinity filter. The method

which using Gaussian density approximating filter distribution

reduce the linear approximation error

and reduce the interference of system model noise to the estimation values. Second

the Cauchy decomposition to the state covariance matrix RMS

which uses diagonal elements to calculate

reduce the disturbance of observation noise error and filter calculation consumption. Video tracking experiments showed that compared with the EKF、UKF and PF algorithm

the proposed algorithm can effectively improve the pedestrian tracking accuracy in mutation

and reduce the time consumption.