Chee-Yee Chong

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This book covers one of the most important applications of estimation theory - multiple object tracking or multi-target tracking. It contains 16 chapters and an extensive bibliography. Additions to the 1995 version of this book include a more thorough treatment of multisensor fusion and multiple hypothesis tracking, attribute-aide tracking, tracking with(More)
A distributed sensor network (DSN) consists of a set of processing nodes collecting data from sensors. When the nodes communicate, each node fuses the information received from other nodes with the local information to update its estimate on the state of the world. Previous papers have dealt with the theoretic algorithms for tracking multiple targets using(More)
In a distributed estimation or tracking system, local estimates are first generated from individual sensors. The state estimates of associated objects are then fused to generate the global estimates. The fusion algorithm has to deal with correlated estimation errors due to common past information or common process noise. Most approaches to estimation fusion(More)
We report here on our effort to investigate the types of hard/soft information that can be realistically collected in an urban operational environment and to generate a data set that can be used for the development of hard/soft data fusion algorithms. Specifically, we discuss: 1) sources of ldquohard informationldquo (i.e. information from physics-based(More)
Target tracking using multiple sensors can provide better performance than using a single sensor. One approach to multiple target tracking with multiple sensors is to first perform single sensor tracking and then fuse the tracks from the different sensors. Two processing architectures for track fusion are presented: sensor to sensor track fusion, and sensor(More)
Target tracking is an important application for putation and thus the processing has to be distributed, with Abrelsstract ho T etsor t ngtworks. i eas e an i a th a nfrgy nodes communicating processed data instead of sensor data. wireless ad hoc sensor networks. Because of the energy Distributed tracking for sensor networks was first invesand communication(More)
A distributed multitarget tracking problem is considered. The Joint Probabilistic Data Association (JPDA) algorithm has been applied successfully for tracking under the multiple-target and clutter environment. However, it assumes a centralized processing architecture in which all the sensors' measurements are transmitted to a single processor and processed.(More)
The theoretical fundamentals of distributed information fusion have been developed over the past two decades and are now fairly well established. However, practical applications of these theoretical results to dynamic sensor networks have remained a challenge. There has been a great deal of work in developing distributed fusion algorithms applicable to a(More)