Although the field of sparse representations is relatively new, research activities in academic and
industrial research labs are already producing encouraging results. The sparse signal or parameter
model motivated several researchers and practitioners to explore high complexity/wide bandwidth
applications such as Digital TV, MRI processing, and certain defense applications. The potential
signal processing advancements in this area may influence radar technologies. This book presents
the basic mathematical concepts along with a number of usefulMATLAB® examples to emphasize
the practical implementations both inside and outside the radar field.
Author(s): Knee Peter
Series: Synthesis Lectures on Algorithms and Software in Engineering
Publisher: Morgan & Claypool Publishers
Year: 2012
Language: English
Pages: 87
List of Symbols......Page 11
List of Acronyms......Page 13
Acknowledgments......Page 15
History of Radar......Page 17
Current Radar Applications......Page 19
Basic Organization......Page 20
Introduction to Sparse Representations......Page 23
Signal Coding Using Sparse Representations......Page 24
Geometric Interpretation......Page 26
Sparse Recovery Algorithms......Page 27
Greedy Approach......Page 28
Non-Uniform Sampling......Page 31
Image Reconstruction from Fourier Sampling......Page 33
Dimensionality Reduction......Page 37
Principal Component Analysis (PCA) and Multidimensional Scaling (MDS)......Page 38
Linear Discriminant Analysis (LDA)......Page 40
Nonlinear Dimensionality Reduction Techniques......Page 41
ISOMAP......Page 42
Local Linear Embedding (LLE)......Page 43
Random Projections......Page 46
Elements of a Pulsed Radar......Page 49
Range and Angular Resolution......Page 52
Imaging......Page 55
Detection......Page 58
Echo Signal Detection and Image Formation......Page 61
Angle-Doppler-Range Estimation......Page 63
Image Registration (Matching) and Change Detection for SAR......Page 65
Automatic Target Classification......Page 68
Sparse Representation for Target Classification......Page 69
Sparse Representation-Based Spatial Pyramids......Page 70
Non-Uniform Sampling and Signal Reconstruction Code......Page 73
Long-Shepp Phantom Test Image Reconstruction Code......Page 75
Signal Bandwidth Code......Page 77
Bibliography......Page 79
Author's Biography......Page 87
