In order to overcome the disadvantage of the common used filtering algorithms that can not achieve the tracking accuracy and effectiveness at the same time,a finite-difference extending Kalman filter algorithm was proposed for ballistic target tracking problem in the re-entry phase.

Under the background of tracking ballistic missiles by ground-based radar systems, the maneuvering ballistic target tracking, the multi-target tracking algorithm and multi-sensor track fusion method are studied in this thesis.

The trajectory tracking problem was transformed into a trajectory state regulation problem which is a linear time varying(LTV) system.

Trajectory tracking guidance law and trajectory simulation of antiballistic missile;

Test of target tracking ability for radarmen;

Sequential Monte Carlo methods for moving target tracking;

An algorithm for multi-sensor registration and target tracking based on UKF;

Kalman filter based vision predicting and object tracking method and its application;

An object tracking algorithm for TV guiding system of UAV based on particle filter;

Nonlinear object tracking using particle filter;

Multiple objects tracking based on two-stage nonlinear voting

Moving objects tracking in atmosphere turbulence is an important research task, and has broad applications in both military and unmilitary field.

This paper discusses design of target track train simulator based on 3DGRTI technology.

The application to two-dimensional target tracking is studied.

Current statistical model of maneuvering target track is presented to reflect the changes of intensity and scope of maneuvering target,and the adaptive Kalman filtering algorithm based on the current statistical model is built.