:methodological framework and selected applications
/ Wolfgang Koch
Heidelberg
: Springer,
, 2013?.
(Mathematical engineering)
Electronic
Includes bibliographical references..
Summary: Sensor Data Fusion is the process of combining incomplete and imperfect pieces of mutually complementary sensor information in such a way that a better understanding of an underlying real-world phenomenon is achieved. Typically, this insight is either unobtainable otherwise or a fusion result exceeds what can be produced from a single sensor output in accuracy, reliability, or cost. This book provides an introduction Sensor Data Fusion, as an information technology as well as a branch of engineering science and informatics. Part I presents a coherent methodological framework, thus providing the prerequisites for discussing selected applications in Part II of the book. The presentation mirrors the author's views on the subject and emphasizes his own contributions to the development of particular aspects. With some delay, Sensor Data Fusion is likely to develop along lines similar to the evolution of another modern key technology whose origin is in the military domain, the Internet. It is the author's firm conviction that until now, scientists and engineers have only scratched the surface of the vast range of opportunities for research, engineering, and product development that still waits to be explored: the Internet of the Sensors.
Notion and Structure of Sensor Data Fusion -- Part I. Sensor Data Fusion: Methodological Framework -- Objects and Sensors -- Bayesian Knowledge Propagation -- Sequential Track Extraction -- On Recursive Batch Processing -- Aspects of Track-to-Track Fusion -- Part II. Sensor Data Fusion: Selected Applications -- Integration of Advanced Sensor Properties -- Integration of Advanced Object Properties -- Integration of Topographical Information -- Feed-back to Acquisition: Sensor Management.
Mathematical engineering
Multisensor data fusion
Sensor networks
Engineering
Signal, Image and Speech Processing
Artificial Intelligence (incl. Robotics)
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences