The invention discloses a dual radar modified sequential Gaussian mixture probability hypothesis density (GM-PHD) filtering method. The traditional dual radar GM-PHD is only suitable for the case thata measurement target is located in a common measurement region of two radars, when the target is not in the common measurement region, a target loss problem is prone to occur. The dual radar modifiedsequential GM-PHD filtering method is based on a finite statistical theory, performs prediction, updating, trimming fusion, maintaining fusion and target state extraction on Gaussian components corresponding to each radar measured values, realizes multi-target tracking, cannot loss a target in a non-common measurement region, and expands the application range of sequential GM- PHD. Compared to traditional methods, the computational complexity of the dual radar modified sequential GM-PHD filtering method does not change much.