Strong maneuver-based target tracking method

Abstract

A strong maneuver-based target tracking method comprises the following steps: initializing parameters, interactively inputting models, judging the covariance matrix, filtering in parallel, updating the model probabilities, interactively outputting the models, filtering in a fixed-delay smoothing manner, and judging whether the state updating is completed; on the basis of the IMM algorithm, the IMM algorithm for recalculating the weight is used, that is, RIMM. The method not only uses the model probabilities, but also takes full advantage of the filtering covariance matrix, so that the tracking accuracy is higher. In addition, an SRCK method is used in the filter forecasting stage, and adopts the spherical integrating criterion and the radial integrating criterion. Compared with a wide UKF algorithm in nonlinear filtering, the target tracking method optimizes the sigma point sampling strategy and the weight distribution in the UKF. Meanwhile, QR factorization is introduced in SRCKF, so that the matrix squiring operation is avoided, and the filtering stability is improved. On the basis, the filtering in a fixed-delay smoothing manner is also introduced, so that the real-time property and the accuracy of target tracking are further improved.

Description

technical field [0001] The invention belongs to the technical field of control science and engineering, and relates to model matching and nonlinear filtering technology for maneuvering target tracking, which is used to realize the tracking of strong maneuvering targets, and to improve the stability of tracking and the tracking robustness against state mutations. In particular, it relates to a method of target tracking based on strong maneuvering. Background technique [0002] Maneuvering target tracking is one of the research hotspots and difficulties in the fields of state estimation, information fusion and target tracking. The target tracking problem is actually the tracking and filtering problem of the target state, that is, to accurately estimate the target state according to the target measurement data obtained by the sensor. Target tracking has a wide range of applications. In the field of national defense, it can be used for ballistic missile defense, air and space e...

AI Technical Summary

Problems solved by technology

However, in the recursive process of CKF, there are shortcomings such as large amount of calculation and numerical instability. For this reason, a volumetric Kalman filter method based on square root filtering is proposed based on the idea of ​​square root filtering, that is, SRCKF

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