This book guides animal ecologists, biologists and wildlife and data managers through a step-by-step procedure to build their own advanced software platforms to manage and process wildlife tracking data. This unique, problem-solving-oriented guide focuses on how to extract the most from GPS animal tracking data, while preventing error propagation and optimizing analysis performance. Based on the open source PostgreSQL/PostGIS spatial database, the software platform will allow researchers and managers to integrate and harmonize GPS tracking data together with animal characteristics, environmental data sets, including remote sensing image time series, and other bio-logged data, such as acceleration data. Moreover, the book shows how the powerful R statistical environment can be integrated into the software platform, either connecting the database with R, or embedding the same tools in the database through the PostgreSQL extension Pl/R. The client/server architecture allows users to remotely connect a number of software applications that can be used as a database front end, including GIS software and WebGIS. Each chapter offers a real-world data management and processing problem that is discussed in its biological context; solutions are proposed and exemplified through ad hoc SQL code, progressively exploring the potential of spatial database functions applied to the respective wildlife tracking case. Finally, wildlife tracking management issues are discussed in the increasingly widespread framework of collaborative science and data sharing. GPS animal telemetry data from a real study, freely available online, are used to demonstrate the proposed examples. This book is also suitable for undergraduate and graduate students, if accompanied by the basics of databases.
Satellite navigation receivers are used to receive, process, and decode space-based navigation signals, such as those provided by the GPS constellation of satellites. There is an increasing need for a unified open platform that will enable enhanced receiver development and design, as well as cost-effective testing procedures for various applications. This book and companion DVD provide hands-on exploration of new technologies in this rapidly growing field.
One of the unique features of the work is the interactive approach used, giving readers the ability to construct their own Global Navigation Satellite Systems (GNSS) receivers. To construct such a reconfigurable receiver with a wide range of applications, the authors discuss receiver architecture based on software-defined radio (SDR) techniques. The presentation unfolds in a systematic, user-friendly style and goes from the basics to cutting-edge research.
Additional features and topics include:
* Presentation of basic signal structures used in GPS and Galileo, the European satellite navigation system
* Design and implementation of a GPS signal generator
* Presentation and analysis of different methods of signal acquisition-serial search; parallel-frequency space search; and parallel-code phase search-as well as code/carrier tracking and navigation data decoding
* A complete GPS software receiver implemented using MATLAB code as well as GPS and GIOVE-A signal records-available on the companion cross-platform DVD-allowing readers to change various parameters and immediately see their effects
* MATLAB-based exercises
* A hands-on method of testing the material covered in the book: supplementary front-end hardware equipment-which may be purchased at http: //ccar.colorado.edu/gnss-enables readers working on a Windows or LINUX system to generate real-world data by converting analog signals to digital signals
* Supplementary course material for instructors available at http: //gps.aau.dk/softgps
* Bibliography of recent results and comprehensive index
The book is aimed at applied mathematicians, electrical engineers, geodesists, and graduate students. It may be used as a textbook in various GPS technology and signal processing courses, or as a self-study reference for anyone working with satellite navigation receivers.
Using the Bayesian inference framework, this book enables the reader to design and develop mathematically sound algorithms for dealing with tracking problems involving multiple targets, multiple sensors, and multiple platforms. It shows how non-linear Multiple Hypothesis Tracking and the Theory of United Tracking are successful methods when multiple target tracking must be performed without contacts or association. With detailed examples illustrating the developed concepts, algorithms, and approaches, the book helps the reader track when observations are non-linear functions of target site, when the target state distributions or measurements error distributions are not Gaussian, when notions of contact and association are merged or unresolved among more than one target, and in low data rate and low signal to noise ratio situations.
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