Aiming at complicated computing and difficulty of being realized when extending single sensor PHD filtering to the multi-sensor case by means of probability generating function, a multi-sensor multi-target sequential particle-PHD tracking algorithm is proposed based on the thought of sequential filtering for a centralized fusion system. The algorithm chooses the importance density function with regard to every sensor, and updates sample particle of every sensor layer by layer. Finally, the multi-sensor multi-target sequential PHD tracking is realized. Experimental results show, when multi-target is tracked only using single sensor, some particles can deviate true trajectories of target, which causes the error of estimated numbers of targets. However, the multi-sensor multi-target sequential particle-PHD tracking algorithm can reduce distance error and improve tracking accuracy effectively.