With the rapid development of near space hypersonic vehicle,tracking and prediction technology of near space target has attracted wide attention.The main tracking and prediction technologies of near space target are discussed,such as the model of near space hypersonic maneuvering target,the design method of multi-model filter,the trajectory prediction method of near space hypersonic maneuvering target,etc.The main problems of existing methods are pointed out,and the main research directions are given.

Aiming at the characteristics of fuzziness and uncertainty in the information of threat factors of air combat, an unmanned combat aerial vehicle (UCAV) threat assessment model is established based on the interval number and fuzzy comprehensive evaluation. The interval number is used to express the weight value of each threat factor and to establish the fuzzy relationship between the enemy unit and the threat factor by fuzzy comprehensive judging method, which can effectively overcome the defect that the threat weight value of the constant vector type determined by the traditional method cannot reflect the ambiguity of the threat degree for the air combat threat, the insufficient uncertainty, and the error that the expert assignment of the expert in the determination weight can be compensated. Simulation results demonstrate the effectiveness of the proposed model.

To locate airborne synthetic aperture radar (SAR) image with high accuracy, a fast inertial navigation error estimation method is proposed by using advantage of sub image back projection (BP) imaging. The relationship between inertial navigation error in position, velocity and positioning error under BP imaging model is investigated. The observation equation of positioning error is obtained by approximating the relationship in linear. Estimations of inertial navigation error in position and velocity can be obtained by least square method. Monte Carlo tests are processed under Gauss observation errors with the same mean and variance. It is illustrated that the proposed method possesses a lesser error of mean square compared with the conventional range-Doppler (R-D) model based estimation method.