Formation target tracking method ET-GM-PHD with unknown new parameters

In order to solve the target tracking problem of multiple formations in the context of unclear nascent target parameters, a formation target tracking algorithm with unknown nascent target-related parameters is proposed, which can effectively improve the tracking performance and thus better meet the demand. By using the Gaussian mixed probability hypothesis density (ET-GM-PHD) filtering framework, the PHD parameters are predicted and then the correlation between each Gaussian component is analyzed to filter out the optimal set of measurements and finally eliminate most of the noise disturbances. Based on the characteristic of dense distribution measured in the movement area of the formation target, the location of the formation target is found and tracked by the target detection method. Finally, the simulation experiments show that the method in this paper can track the formation target quickly and effectively with good tracking performance when the parameters related to the nascent target are unknown.