Und dann auf "Zum Home-Bildschirm [+]".
Stöbern
genialokal zum Startbildschirm hinzufügen
Installieren Sie die genialokal App auf Ihrem Startbildschirm für einen schnellen Zugriff und eine komfortable Nutzung.
Installieren Sie die genialokal App auf Ihrem Startbildschirm für einen schnellen Zugriff und eine komfortable Nutzung.
Ihr gewünschter Artikel ist in 0 Buchhandlungen vorrätig - wählen Sie hier eine Buchhandlung in Ihrer Nähe aus:
The desire for precise knowledge about the location of a moving object at any time instant has motivated a great deal of scientific research recently. This is owing to a steady expansion of the range of enabling devices and technologies, as well as the need for seamless solutions for location-based services. Besides localization accuracy, a common requirement for emerging solutions is that they are cost-abstemious, both in terms of the financial and computational cost. Hence, development of localization strategies from already deployed technologies, e.g., from different terrestrial radio frequency sources is of great practical interest. Amongst other, these include localization strategies based on received signal strength (RSS), time of arrival, angle of arrival (AoA) or a combination of them. RSS-AoA-based Target Localization and Tracking in Wireless Sensor Networks presents recent advances in developing algorithms for target localization and tracking, reflecting the state-of-the-art algorithms and research achievements in target localization and tracking based on hybrid (RSS-AoA) measurements. Technical topics discussed in the book include:
Centralized RSS-AoA-based Target Localization
Distributed RSS-AoA-based Target Localization
RSS-AoA-based Target Tracking via Maximum A Posteriori Estimator
RSS-AoA-based Target Tracking via Kalman Filter
RSS-AoA-based via Sensor Navigation
This book is of interest for personnel in telecommunications and surveillance industries, military, smart systems, as well as academic staff and postgraduate/research students in telecommunications, signal processing, and non-smooth and convex optimization.
Slavisa Tomic received the M.S. degree in traf-c engineering according to the postal traf-c and telecommunications study program from University of Novi Sad, Serbia in 2010, and the Ph.D. degree in electrical and computer engineering from University Nova of Lisbon, Portugal in 2017. His research interests include target localization in wireless sensor networks and non-linear and convex optimization.
RSS-AoA-based Target Localization and Tracking in Wireless Sensor Networks
