{"product_id":"modern-radar-detection-theory-9781613531990","title":"Modern Radar Detection Theory","description":"\u003cp\u003eRecently, various algorithms for radar signal detection that rely heavily upon complicated processing and\/or antenna architectures have been the subject of much interest. These techniques owe their genesis to several factors. One is revolutionary technological advances in high-speed signal processing hardware and digital array radar technology. Another is the stress on requirements often imposed by defence applications in areas such as airborne early warning and homeland security.\u003c\/p\u003e\u003cp\u003eThis book explores these emerging research thrusts in radar detection with advanced radar systems capable of operating in challenging scenarios with a plurality of interference sources, both man-made and natural. Topics covered include: adaptive radar detection in Gaussian interference with unknown spectral properties; invariance theory as an instrument to force the Constant False Alarm Rate (CFAR) property at the design stage; one- and two-stage detectors and their performances; operating scenarios where a small number of training data for spectral estimation is available; Bayesian radar detection to account for prior information in the interference covariance matrix; and radar detection in the presence of non-Gaussian interference. Detector design techniques based on a variety of criteria are thoroughly presented and CFAR issues are discussed. Performance analyses representative of practical airborne, as well as ground-based and shipborne, radar situations are shown.\u003c\/p\u003e\u003cp\u003eResults on real radar data are also discussed. \u003ci\u003eModern Radar Detection Theory\u003c\/i\u003e provides a comprehensive reference on the latest developments in adaptive radar detection for researchers, advanced students and engineers working on statistical signal processing and its applications to radar systems.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003e\u003ci\u003eGreco, Maria Sabrina:\u003c\/i\u003e\u003c\/b\u003e - \u003cp\u003eMaria Sabrina Greco is a Professor at the University of Pisa, Department of Information Engineering, where her research interests include radar clutter models, coherent and incoherent detection in non-Gaussian clutter, passive radars, multistatic and cognitive radars. She serves on the editorial boards of \u003ci\u003eIET Radar, Sonar and Navigation\u003c\/i\u003e and \u003ci\u003eJournal of Advances in Signal Processing\u003c\/i\u003e, and she is the Editor-in-Chief of the \u003ci\u003eIEEE Aerospace and Electronic Systems Magazine\u003c\/i\u003e. She is a member of the IEEE Sensor Array Processing Technical Committees, of the IEEE AESS and of SP Boards of Governors, and Chair of the IEEE AESS Radar Panel.\u003c\/p\u003e\u003cb\u003e\u003ci\u003ede Maio, Antonio:\u003c\/i\u003e\u003c\/b\u003e - \u003cp\u003eAntonio De Maio is a Professor at the University of Naples Federico II, Department of Electrical Engineering and Information Technology, where his research interests lie in the field of statistical signal processing, with emphasis on radar detection and convex optimization applied to radar signal processing. He is a Senior Area Editor of \u003ci\u003eIEEE Transactions on Signal Processing\u003c\/i\u003e, a member of the IEEE AESS Radar Panel and of the IEEE Sensor Array Processing Technical Committee, and has published more than 200 technical papers in international journals or proceedings of international conferences.\u003c\/p\u003e","brand":"SciTech Publishing","offers":[{"title":"Default Title","offer_id":50856039022866,"sku":"9781613531990","price":124.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_40933b5c-af13-4f20-b3d0-8fc2e205a815.jpg?v=1737493477","url":"https:\/\/surprise-castle.myshopify.com\/products\/modern-radar-detection-theory-9781613531990","provider":"Surprise Castle","version":"1.0","type":"link"}