Multiple-target tracking is a canonical application of sensor networks as it exhibits different aspects of sensor networks such as event detection, sensor information fusion, multi-hop communication, sensor management and decision making. The task of tracking multiple objects in a sensor network is challenging due to constraints on a sensor node such as short communication and sensing ranges, a limited amount of memory and limited computational power. In addition, since a sensor network surveillance system needs to operate autonomously without human operators, it requires an autonomous tracking algorithm which can track an unknown number of targets. In this paper, we develop a scalable hierarchical multiple-target tracking algorithm that is autonomous and robust against transmission failures, communication delays and sensor localization error.