Radar Detection Theory of Sliding Window Processes

Constant false alarm rate detection processes are important in radar signal processing. Such detection strategies are used as an alternative to optimal Neyman-Pearson based decision rules, since they can be implemented as a sliding window process running on a radar range-Doppler map. This book examines the development of such detectors in a modern framework. With a particular focus on high resolution X-band maritime surveillance radar, recent approaches are outlined and examined. Performance is assessed when the detectors are run in real X-band radar clutter. The book introduces relevant mathematical tools to allow the reader to understand the development, and follow its implementation.

Introduction to Non-coherent Detection. Statistical Structures for Radar Detection. Developed Detection Theory. Constant False Alarm Rate Detection. Advances in X-Band Application. Examples of Performance.

Graham V. Weinberg completed his B.S. and Ph.D. degrees at the University of Melbourne, Australia. His doctoral thesis examined distributional approximations of stochastic processes using the Stein-Chen method. After a short period in telecommunications research at the University of Adelaide, he joined Defence Science and Technology Group, Australia. In the capacity of a scientist, he has undertaken research into radar detection issues arising from airborne high resolution X-band maritime surveillance platforms. To further continue his professional development, he has also completed a Master’s degree in signal and information processing through the University of Adelaide, Australia. His research interests include CFAR, coherent multi-look radar detection and the mathematics of radar signal processing. He has published extensively and is a member of the Institution of Engineering and Technology (IET), UK.