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Authors of various books published with Artech House Publishing blog about current topics in microwave technology that are covered in their recent books.

Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach, Second Edition, a Review

July 27, 2020

The Artech House community is comprised of experts in a variety of technical fields. Read on for a glowing endorsement of Joseph Guerci's book, Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach, Second Edition, by Alfonso Farina, Selex ES (Retired), Consultant to Leonardo Land & Naval Defence Electronics, Italy:

The book of PhD Joe GUERCI is an authoritative, highly professional, rich, comprehensive, visionary and pleasant guided tour across modern radar signal processing algorithms and architectures showing and paving the way to real operational cognitive radar.

A guided tour: I am living in the historic and magnificent city of Roma and frequently, with exception of the last three months (vis maior, major force), I walk across the city and I enjoy it very much. Every time it is pleasant, restoring, new cultural experience: a joy for the day. At times, I play the role of a - though modest but - enthusiastic touristic guide in my beloved city of Rome for friends, colleagues.

Dr Guerci's contributions to advanced, fully adaptive radar systems and real-time knowledge-aided and cognitive radar processing architectures have been widely recognised by the international radar community with the highest IEEE honours. Joe is indeed an architect of modern radar systems in the true etymology of the word: from Ancient Greek arkhitéktōn, “architect”, literally “chief builder, principal craftsman”. The Reader enjoys the highly professional and so-authoritative guide of Dr Guerci with his book along the radar signal processing algorithms (from the old French & Medieval Latin ‘algorismus’; from the name of the mathematician, astronomer and geographer, a scholar in the House of Wisdom of Baghdad from old Persia of IX century (c.a. 780-850), Abu Jàfar inb Musa al-Khowarizmi. He found the first systematic solution of linear and quadratic equations; he is considered the founder of algebra, a credit he shares with Diophantus.) and architectures avenue. There are six milestones (Coming to Roma and along the consular streets, the Visitor can see the Miliarium- stone obelisks): Why “Cognitive” Radar and book organization, Optimum Multi-Input Multioutput Radar (MIMO), Adaptive MIMO Radar, Introduction to KA (Knowledge Aided) Adaptive Radar, Putting it All Together: CoFAR (cognitive fully adaptive radar), Cognitive Radar and Artificial Intelligence.

The Reader will appreciate the “real-world radar experience” suitably blended with refined math of the Author. I resonate with the recognition of the multitude of real-world effects to be suitably singled out, modelled and compensated for with engineering work in live radar systems. In addition, the Reader will appreciate take away messages like, “Importantly, it is wise to remember always: as goes radar channel knowledge, so goes performance!” that comes from hands-on experience of the Author. Quantifying and ensuring system performance is one of the major duty of engineers. Rich: with 150 math equations, over 80 figures, over twenty fully developed technical examples also related to recorded live data, and a comprehensive list of references (Farina, A., and F. A. Studer, “Detection with High Resolution Radar: Great Promise, Big Challenge,” Microwave Journal, May 1991, which brings me to good memories) accompanying each chapter (milestone), the book is a precious daily reference for radar scientists, engineers, agency expert’s work and students.

Comprehensive: It is appreciated the plain narration of key breakthrough that has allowed for the actualization of knowledge aided performance gains in real-time systems, precisely the approach adopted by the DARPA/AFRL KASSPER project, just to use the same words of Dr Guerci.

Visionary: the topic of Cognitive Radar and Artificial Intelligence (AI) is tackled with a cautionary perspective, as Dr Guerci says. I share this caution to approach the topic. The fashion of changing paradigm from model based to data driven/Machine Learning (ML) algorithm is also motivated by the so-called big data (though a commodity not easily available) and the increasing computing power (entangled in Moore’s law, e.g. computer power recent developments in multi-core CPU and GPU). Wide band link is another technology and infrastructure asset to consider on stage. Hybrid approaches may have a suitable role.

What is big data? A scientific insight can be found in [2], where topology is the suggested conceptual guideline to link to big data. In addition, correlation is not to be confused with causality (or cause and effect) [3], [4]. In big data, one should pay attention also to the so-called spurious correlations. The CoFAR mission computer, radar controller and scheduler is the place where to unleash and test the powerfulness of modern AI. Radar needs to operate in an opaque, deceiving and - at times - threatening environment. Mimicking Nature and biological strategies of evolution seem a way to pursue, to overcome the operational challenges, and thus ensure system robustness and reliability.

Pleasant: Reading the book of Dr Guerci is how to drink a glass of fresh water when you are thirsty. Dear Reader, have a good read.

[1] A. Farina, “Looking for an Algorithm to Print on A T-Shirt: Part 1”, Paperback – August 10, 2016, now, the
essence of knowledge, Editor Mikey Casey
[2] Xiang-Gen Xia, “Small Data, Mid Data, and Big Data Versus Algebra, Analysis, and Topology”, IEEE Signal
Processing Magazine, January 2017, pp. 48-51.
[3] R. Streit, “INTRODUCTION TO THE ISSUE, Perspectives Magazine”, ISIF Perspectives On Information
Fusion, vol. 3, 2020, p. 3.
[4] A. Farina, “Causal Inference in Statistics. An attempt at some reflection.” ISIF Perspectives On Information
Fusion, vol. 3, 2020, pp. 36-39.


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