Description |
1 online resource (ix, 74 pages : illustrations |
Series |
Synthesis lectures on algorithms and software in engineering, 1938-1735 ; # 2 |
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Synthesis lectures on algorithms and software in engineering (Online) ; 2.
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Contents |
Introduction -- Waveform-agile sensing -- Waveform adaptation for tracking: a review -- Organization -- Waveform-agile target tracking application formulation -- Filtering overview -- The particle filter -- The unscented particle filter -- Tracking problem formulation -- Target dynamics -- Transmitted waveform structure -- Observations model -- Measurement noise covariance -- Waveform selection problem statement -- Dynamic waveform selection with application to narrowband and wideband environments -- Prediction of the MSE -- Stochastic approximation -- Calculation of the gradient -- Simultaneous perturbation stochastic approximation -- Stochastic gradient descent algorithm -- Drawbacks -- Unscented transform based approximation -- Algorithm for waveform selection -- Narrowband environment -- Waveform structure -- CRLB for GFM pulses -- Simulation -- Discussion -- Wideband environment -- Wideband signal model -- Waveform structure -- Simulation -- Discussion -- Dynamic waveform selection for tracking in clutter -- Single target -- Observations model -- Clutter model -- Target tracking with probabilistic data association -- Waveform selection in the presence of clutter -- Simulation -- Discussion -- Performance under different choices of the weighting matrix -- Multiple targets -- Target dynamics -- Measurement model -- Clutter model -- Multiple target tracking with joint probabilistic data association -- Dynamic waveform selection and configuration -- Simulation -- Discussion -- Conclusions -- Summary of findings -- CRLB evaluation for Gaussian Envelope GFM Chirp from the ambiguity function -- CRLB evaluation from the complex envelope -- Sample code for a simple particle filter -- Sample code for an unscented particle filter |
Summary |
Recent advances in sensor technology and information processing afford a new flexibility in the design of waveforms for agile sensing. Sensors are now developed with the ability to dynamically choose their transmit or receive waveforms in order to optimize an objective cost function. This has exposed a new paradigm of significant performance improvements in active sensing: dynamic waveform adaptation to environment conditions, target structures, or information features. The manuscript provides a review of recent advances in waveform-agile sensing for target tracking applications. A dynamic waveform selection and configuration scheme is developed for two active sensors that track one or multiple mobile targets. A detailed description of two sequential Monte Carlo algorithms for agile tracking are presented, together with relevant Matlab code and simulation studies, to demonstrate the benefits of dynamic waveform adaptation. The work will be of interest not only to practitioners of radar and sonar, but also other applications where waveforms can be dynamically designed, such as communications and biosensing |
Bibliography |
Includes bibliographical references (pages 69-73) |
Notes |
English |
Subject |
Sensor networks -- Mathematical models
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Wave functions -- Mathematical models
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TECHNOLOGY & ENGINEERING -- Sensors.
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Form |
Electronic book
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Author |
Papandreou-Suppappola, Antonia.
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Morrell, Darryl.
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ISBN |
9781598296723 |
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1598296728 |
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9783031015113 |
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3031015118 |
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