Random hypersurface-based progressive Bayesian extension target tracking method and system

The invention relates to a progressive Bayesian extension target tracking method and system based on a random hypersurface, and the method and system are used for researching the tracking of a star convex type extension target, and the method comprises the steps: building a measurement source model of the star convex type extension target; performing state initialization of the star convex type expansion target based on the measurement source model of the star convex type expansion target, and obtaining an initial state vector of the star convex type expansion target; collecting measurement information sets of the target at different moments by using a radar device; performing LCD sampling on the state vector of the star convex type expansion target to obtain state prediction of the star convex type expansion target; and based on the measurement information set, utilizing a progressive Bayesian filter to progressively update the predicted state of the star convex type expansion target, extracting the motion s