The purpose of this chapter is to give a brief overview of the principles of CS and to show how CS may be applied in a radar system to support automatic target recognition. The chapter is organised as follows. Section 8.2 gives an introduction of the basic principles of CS. Section 8.3 presents an overview of some of the main algorithms for reconstruction of sparse signals. The application of CS to target recognition based on jet engine modulation (JEM) is described in section 8.4. Section 8.5 shows how CS may be applied to high resolution imaging of targets using inverse synthetic aperture radar (ISAR). Finally, section 8.6 gives conclusions.

Chapter Contents:

• 8.1 Introduction
• 8.2 Principles of compressive sensing
• 8.2.1 Sparse and compressible signals
• 8.2.2 Restricted isometric property and coherence
• 8.2.3 Signal reconstruction
• 8.2.3.1 Minimum l 2 norm reconstruction
• 8.2.3.2 Minimum l 0 norm reconstruction
• 8.2.3.3 Minimum l 1 norm reconstruction
• 8.2.3.4 Example of l 1 norm versus l 2 norm reconstruction
• 8.3 Reconstruction algorithms
• 8.3.1 Convex optimisation
• 8.3.1.1 Basis pursuit
• 8.3.1.2 Basis pursuit de-noising
• 8.3.1.3 Least absolute shrinkage and selection operator
• 8.3.2 Greedy constructive algorithms
• 8.3.2.1 Matching pursuit
• 8.3.2.2 Orthogonal matching pursuit
• 8.3.2.3 Stage-wise orthogonal matching pursuit
• 8.3.3 Iterative thresholding algorithms
• 8.3.3.1 Iterative hard thresholding
• 8.3.3.2 Iterative shrinkage and thresholding
• 8.4 Jet engine modulation
• 8.4.1 Introduction
• 8.4.2 Jet engine model
• 8.4.3 Simulation results of JEM compressive sensing
• 8.5 Inverse synthetic aperture radar
• 8.5.1 Introduction
• 8.5.2 Simulation model
• 8.6 Conclusions
• Acknowledgements
• References

Inspec keywords: radar imaging; radar target recognition; signal reconstruction; compressed sensing; radar applications; radar resolution; synthetic aperture radar

Other keywords: radar applications; sparse signal reconstruction; radar system; automatic target recognition; JEM; jet engine modulation; compressive sensing; inverse synthetic aperture radar; high resolution imaging; ISAR; CS principles

Subjects: Radar equipment, systems and applications; Signal processing and detection