This book develops the concepts underlying the design of adaptive arrays from first principles and is directed at research workers and designers whose mathematical background requires refurbishment in the special techniques which have accumulated around the field, often to the obscuration of the simple basic ideas.
This book develops the concepts underlying the design of adaptive arrays from first principles and is directed at research workers and designers whose mathematical background requires refurbishment in the special techniques which have accumulated around the field, often to the obscuration of the simple basic ideas.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
J.E. Hudson graduated from the University of Birmingham in 1964 and was awarded the Ph.D. degree in 1968 for research in spatial coherence of waves in inhomogeneous media and digital signal processing. He then worked at MSDS, Stanmore, on sonar systems and was a research fellow at Birmingham working on mutual coupling, pattern recognition and transducer design. He took up a post as lecturer at the Department of Electronic & Electrical Engineering, University of Loughborough, in 1972. Interest in adaptive array processing began in 1973 with the award to the department of an MOD contract to investigate passive sonar applications, and has continued with the field widening to include HF arrays, microwave communications and radar. Hudson has prepared a large number of research reports in the field and has published some of the more interesting results in the literature. Other interests include spectral analysis, parameter estimation, signal processing and general techniques applied to these and field problems.
Inhaltsangabe
Chapter 1: Introductory ideas Chapter 2: Vector and matrix techniques Chapter 3: Optimal antennas Chapter 4: Adaptive solutions of optimal antennas Chapter 5: Performance of optimal antennas Chapter 6: Main-lobe constraints Chapter 7: Suboptimal arrays and other modified systems Appendix 1: Basic vectors, matrices and statistics Appendix 2: Differentiation of WHNRW Appendix 3: Minimum norm property of projections Appendix 4: Eigenvalue solution for norm-bounded power minimisation