Koch W. Tracking and Sensor Data Fusion: Methodological Framework and Selected Applications

Springer, 2014. — 261 p. — (Mathematical Engineering) — ISBN: 9783642392702.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. Appropriate collection, registration, and alignment, stochastic filtering, logical analysis, spacetime integration, exploitation of redundancies, quantitative evaluation, and appropriate display are part of Sensor Data Fusion as well as the integration of related context information. The technical term ‘‘Sensor Data Fusion’’ was created in George Orwell’s very year 1984 in the US defence domain, but the applications and scientific topics in this area have much deeper roots. Today, Sensor Data
Fusion is evolving at a rapid pace and present in countless everyday systems and civilian products.Notion and Structure of Sensor Data Fusion
Sensor Data Fusion: Methodological Framework
Characterizing Objects and Sensors
Bayesian Knowledge Propagation
Sequential Track Extraction
On Recursive Batch Processing
Aspects of Track-to-Track Fusion
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