Aerial target tracking method

Abstract

The invention provides an aerial target tracking method, and relates to the technical field of target tracking. According to the method, multiple target dynamics models are introduced; then the motion state of the target is decomposed to three coordinate axes, model matching is conducted on the motion state of the target on each coordinate axis, conversion between models obeys the time-related Markov process, a matching result is output, the maneuvering state of an aerial target is divided into linear maneuvering, nonlinear maneuvering and nonlinear strong maneuvering, and three types of filters are provided and are respectively a Kalman filter, an extended Kalman filter and an unscented Kalman filter; and next, through target maneuvering state detection, the target can adaptively select a proper filter from the filter set at each moment to carry out filtering processing, a state estimation result is output, finally, the filtering result is decomposed to a three-dimensional coordinate axis again, model probability updating is carried out, and target tracking is completed through iteration of the process.

Description

technical field [0001] The invention relates to the technical field of target tracking, in particular to an air target tracking method. Background technique [0002] The target tracking system is a real-time system with high requirements for complex data processing. The complexity of this data is reflected in the uncertainty in the radar information detection process. The movement status of most targets is unknown, and the number of targets is also Uncertain, the sampling time of the radar data is not a time series with equal intervals. During this period, there are various interferences and the non-Gaussian nature of the observation noise caused by anti-interference means may affect the final tracking accuracy. Therefore, choosing a flexible and accurate dynamic model, a filtering method that can effectively filter noise, and a real-time and reliable tracking algorithm is the key to complete the trajectory estimation of high maneuvering targets in complex environments. [...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the problems existing in the prior art, the present invention provides an air target tracking method, aiming at the problem that the model set in the IMM algorithm is fixed, the number of models is limited and cannot cover all the motion forms of the maneuvering target, and the selection of the filter in the algorithm does not have certain constraints. Rules, the uncertainty of the number of filters, etc. may cause the filter to be single, complex, or the filter does not match the linearization degree of the tracking system, and a target tracking method suitable for three-dimensional space is proposed.

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