Research on Modeling of Air Target Motion Characteristics and Track Identification Method
Zewen Wang, Hongmin Zhang, Ke Jin · 2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP) · 2019
The track is an important basis for the classification and identification of radar air targets. In this paper, the equations of the aircraft motion model, including the horizontal straight, the horizontal arc and the vertical arc, are firstly derived. Then, by taking the Earth-fixed coordinate system as a bridge, the coordinate transformations are used to obtain the radar target parameters, i.e., the range, azimuth and pitch angle. The influence of the Earth curvature in long-distance conditions is compensated. The track recognition method based on radial basis function (RBF) neural network is further designed. Finally, this paper established four flight situations of the target track on the basis of three models above, aiming to obtain radar measured data. The necessity of coordinate transformation is verified by quantitative analysis of long-distance effects. A large number of track recognition tests are performed to analyze the influence of track fluctuations on the recognition rate. Experiments show that, when the track initial position and initial velocity fluctuations are in a certain area, this paper can achieve a high target recognition rate, which verifies the correctness and effectiveness of the proposed method.