Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network | EURASIP Journal on Applied Signal Processing 2003 4 371-377 2003 Hindawi Publishing Corporation Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network David Friedlander Applied Research Laboratory The Pennsylvania State University P O. Box 30 State College PA 16801-0030 USA Email dsf10@ Christopher Griffin Applied Research Laboratory The Pennsylvania State University P O. Box 30 State College PA 16801-0030 USA Email cgriffin@ Noah Jacobson Applied Research Laboratory The Pennsylvania State University P O. Box 30 State College PA 16801-0030 USA Email ncj102@ Shashi Phoha Applied Research Laboratory The Pennsylvania State University . Box 30 State College PA 16801-0030 USA Email sxp26@ Richard R. Brooks Applied Research Laboratory The Pennsylvania State University P O. Box 30 State College PA 16801-0030 USA Email rrb5@ Received 12 December 2001 and in revised form 5 October 2002 Autonomous networks of sensor platforms can be designed to interact in dynamic and noisy environments to determine the occurrence of specified transient events that define the dynamic process of interest. For example a sensor network may be used for battlefield surveillance with the purpose of detecting identifying and tracking enemy activity. When the number of nodes is large human oversight and control of low-level operations is not feasible. Coordination and self-organization of multiple autonomous nodes is necessary to maintain connectivity and sensor coverage and to combine information for better understanding the dynamics of the environment. Resource conservation requires adaptive clustering in the vicinity of the event. This paper presents methods for dynamic distributed signal processing using an ad hoc mobile network of microsensors to detect identity and track targets in noisy environments. They seamlessly integrate data from fixed and mobile platforms and dynamically organize platforms into clusters to process
