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Terrain Relative Navigation for Sensor-limited Systems with Application to Underwater Vehicles
  • Language: en
  • Pages: 183

Terrain Relative Navigation for Sensor-limited Systems with Application to Underwater Vehicles

Terrain Relative Navigation (TRN) provides bounded-error localization relative to an environment by matching range measurements of local terrain against an a priori map. The environment-relative and onboard sensing characteristics of TRN make it a powerful tool for return-to-site missions in GPS-denied environments, with potential applications ranging from underwater and space robotic exploration to pedestrian indoor navigation. For many of these applications, available sensors may be limited by mission power/weight constraints, cost restrictions, and environmental effects (e.g. inability to use a magnetic compass in space). Such limitations not only degrade the accuracy of traditional navig...

Performance and Implementation Aspects of Nonlinear Filtering
  • Language: en
  • Pages: 213

Performance and Implementation Aspects of Nonlinear Filtering

Nonlinear filtering is an important standard tool for information and sensor fusion applications, e.g., localization, navigation, and tracking. It is an essential component in surveillance systems and of increasing importance for standard consumer products, such as cellular phones with localization, car navigation systems, and augmented reality. This thesis addresses several issues related to nonlinear filtering, including performance analysis of filtering and detection, algorithm analysis, and various implementation details. The most commonly used measure of filtering performance is the root mean square error (RMSE), which is bounded from below by the Cramér-Rao lower bound (CRLB). This th...

Sequential Monte Carlo Methods in Practice
  • Language: en
  • Pages: 590

Sequential Monte Carlo Methods in Practice

Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques.

Discrete-time Stochastic Systems
  • Language: en
  • Pages: 387

Discrete-time Stochastic Systems

This comprehensive introduction to the estimation and control of dynamic stochastic systems provides complete derivations of key results. The second edition includes improved and updated material, and a new presentation of polynomial control and new derivation of linear-quadratic-Gaussian control.

Human Motion Capture and Identification for Assistive Systems Design in Rehabilitation
  • Language: en
  • Pages: 244

Human Motion Capture and Identification for Assistive Systems Design in Rehabilitation

HUMAN MOTION CAPTURE AND IDENTIFICATION FOR ASSISTIVE SYSTEMS DESIGN IN REHABILITATION A guide to the core ideas of human motion capture in a rapidly changing technological landscape Human Motion Capture and Identification for Assistive Systems Design in Rehabilitation aims to fill a gap in the literature by providing a link between sensing, data analytics, and signal processing through the characterisation of movements of clinical significance. As noted experts on the topic, the authors apply an application-focused approach in offering an essential guide that explores various affordable and readily available technologies for sensing human motion. The book attempts to offer a fundamental app...

Gaussian Processes for Positioning Using Radio Signal Strength Measurements
  • Language: en
  • Pages: 74

Gaussian Processes for Positioning Using Radio Signal Strength Measurements

Estimation of unknown parameters is considered as one of the major research areas in statistical signal processing. In the most recent decades, approaches in estimation theory have become more and more attractive in practical applications. Examples of such applications may include, but are not limited to, positioning using various measurable radio signals in indoor environments, self-navigation for autonomous cars, image processing, radar tracking and so on. One issue that is usually encountered when solving an estimation problem is to identify a good system model, which may have great impacts on the estimation performance. In this thesis, we are interested in studying estimation problems pa...

Indoor Geolocation Science and Technology
  • Language: en
  • Pages: 492

Indoor Geolocation Science and Technology

  • Type: Book
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  • Published: 2022-09-01
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  • Publisher: CRC Press

Precise and accurate localization is one of the fundamental scientific and engineering technologies needed for the applications enabling the emergence of the Smart World and the Internet of Things (IoT). Popularity of localization technology began when the GPS became open for commercial applications in early 1990's. Since most commercial localization applications are for indoors and GPS does not work indoors, the discovery of opportunistic indoor geolocation technologies began in mid-1990's. Because of complexity and diversity of science and technology involved in indoor Geolocation, this area has emerged as its own discipline over the past two decades. At the time of this writing, received ...

Choice
  • Language: en
  • Pages: 660

Choice

  • Type: Book
  • -
  • Published: 2003
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  • Publisher: Unknown

None

Beyond the Kalman Filter: Particle Filters for Tracking Applications
  • Language: en
  • Pages: 328

Beyond the Kalman Filter: Particle Filters for Tracking Applications

  • Type: Book
  • -
  • Published: 2003-12-01
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  • Publisher: Artech House

For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. To solve problems beyond this restricted class, particle filters are proving to be dependable methods for stochastic dynamic estimation. Packed with 867 equations, this cutting-edge book introduces the latest advances in particle filter theory, discusses their relevance to defense surveillance systems, and examines defense-related applications of particle filters to nonlinear and non-Gaussian problems. With this hands-on guide, you can develop more accurate and reliable nonlinear filter designs and more precisely predict the performance of these designs. You can also apply particle filters to tracking a ballistic object, detection and tracking of stealthy targets, tracking through the blind Doppler zone, bi-static radar tracking, passive ranging (bearings-only tracking) of maneuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.

Adaptive Filtering and Change Detection
  • Language: en
  • Pages: 520

Adaptive Filtering and Change Detection

Adaptive filtering is a branch of digital signal processing which enables the selective enhancement of desired elements of a signal and the reduction of undesired elements. Change detection is another kind of adaptive filtering for non-stationary signals, and is the basic tool in fault detection and diagnosis. This text takes the unique approach that change detection is a natural extension of adaptive filtering, and the broad coverage encompasses both the mathematical tools needed for adaptive filtering and change detection and the applications of the technology. Real engineering applications covered include aircraft, automotive, communication systems, signal processing and automatic control...