2020•Unpublished venueRequires access

Overview of Volume 2

John F. Raquet

Open publisher page 4 citations

Abstract

The extreme success of global navigation satellite systems (GNSS) has, ironically, led to a desire to complement GNSS with other types of sensors for situations in which GNSS is not available, in order to guarantee the ability to determine time or position. This chapter looks at the big picture of what is really happening within navigation systems, in order to better understand how the various approaches relate to each other. To do this, it is helpful to develop a “navigation framework.” For GPS, perhaps the system observes the range to a satellite. Typical GPS applications use a Kalman filter to perform the predict–observe–compare cycle. At a basic level, any physical sensor that measures something which changes when the sensor is moved is a potential navigation sensor. The chapter also presents an overview of the key concepts discussed in this book.

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What this paper is about

The extreme success of global navigation satellite systems (GNSS) has, ironically, led to a desire to complement GNSS with other types of sensors for situations in which GNSS is not available, in order to guarantee the ability to determine time or position. This chapter looks at the big picture of what is really happening within navigation systems, in order to better understand how the various approaches relate to each other. To do this, it is helpful to develop a “navigation framework.” For GPS, perhaps the system observes the range to a satellite. Typical GPS applications use a Kalman filter to perform the predict–observe–compare cycle. At a basic level, any physical sensor that measures something which changes when the sensor is moved is a potential navigation sensor. The chapter also presents an overview of the key concepts discussed in this book.

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Available abstract

The extreme success of global navigation satellite systems (GNSS) has, ironically, led to a desire to complement GNSS with other types of sensors for situations in which GNSS is not available, in order to guarantee the ability to determine time or position. This chapter looks at the big picture of what is really happening within navigation systems, in order to better understand how the various approaches relate to each other. To do this, it is helpful to develop a “navigation framework.” For GPS, perhaps the system observes the range to a satellite. Typical GPS applications use a Kalman filter to perform the predict–observe–compare cycle. At a basic level, any physical sensor that measures something which changes when the sensor is moved is a potential navigation sensor. The chapter also presents an overview of the key concepts discussed in this book.

Key concepts: GNSS applications, Global Positioning System, Computer science, GNSS augmentation, Kalman filter, Satellite navigation, Key (lock), Real-time computing

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