Modern radars have evolved greatly from their origins as providers of blips and blobs to highly trained operators in darkened rooms. Today, all-weather, day and night radars provide clear digital images as detailed and useful as photographs. They also provide digital symbolic representations of multiple types of air, sea, and ground moving targets over wide geographic regions. Today’s state-of-the-art radars can even provide flexible, on-demand sensing services to a large network of users. This tutorial will introduce the student to the concepts, physics, and digital technology underpinning modern coherent radars. The first part of this tutorial will functionally decompose the adaptive agile electronically scanned array radar, and explain how it detects and images objects in its field of view. The second part of the tutorial will describe how radars estimate and predict the behavior of those objects. Prerequisites: students should have a good basic understanding of algebra and geometry. Knowledge of undergraduate electromagnetic field theory, calculus, discrete mathematics, and probability theory would be helpful but are not required.
Dr. David Zasada is a Senior Principal Sensors Systems Engineer in MITRE’s Electronic Systems and Technologies Technical Center. He has over 40 years’ experience in radar systems research, development, maturation, transition, acquisition, and operations. Dave has contributed to the design, development, acquisition, and technical refresh of ground and airborne intelligence, surveillance, reconnaissance, warning, tracking, and fire control radars; airborne and spaceborne moving target indication and synthetic aperture radars; and ballistic missile warning and fire control radars. He is the author of numerous technical publications and radar courses. Dave is a member of the IEEE Aerospace Electronics Systems (AES) Society, Radar Systems Panel, Radar Standards Group, Signal Processing Society, and Phi Beta Kappa. He received his PhD in Electrical Engineering with a concentration in radar signal processing from Syracuse University, 1995, an EE, Electrical Engineering, concentrations in communications and signal processing, Syracuse University, 1983. MS, Physics, concentration in astrophysics, Rensselaer Polytechnic Institute, 1973, and BS, Physics, concentration in low temperature physics, Georgetown University, 1971.
Inverse Synthetic Aperture Radar (ISAR) is a technique used for reconstructing radar images of targets. Modern high-resolution tracking radars implicitly offer the system requirements needed for implementing ISAR imaging. ISAR images are obtained by means of a signal processing that can be enabled both on and off-line. Automatic Target Recognition (ATR) systems are often based on the use of radar images because they provide a 2-D E.M map of the target reflectivity. Therefore, classification features that contain spatial information can be extracted and used to increase the performance of classifiers.
This tutorial aims at providing an introduction to ISAR. The lecture is divided in three parts:, the first part deals with principles of ISAR, the second part concerns ISAR processing and the third part focuses on advanced ISAR systems, such as bistatic, passive and multistatic ISAR systems. The ISAR system is introduced by defining the radar-target geometry and by considering simple radar concepts. The derivation of the ISAR processor is obtained by defining the signal model and by interpreting it in the Fourier domain. Differences between ISAR and SAR are also highlighted in order to better understand ISAR concepts.
Basic and advanced techniques are presented in order to provide an overview of the current methods used for implementing ISAR and improving its performance. In particular, the problem of ISAR image autofocus is analysed in details and several solutions are presented. Bistatic and multistatic ISAR will also be introduced together with suitable ISAR techniques that aim at forming bistatic and multistatic ISAR images.
Several examples with simulations and real data are provided throughout the tutorial in order to demonstrate the effectiveness and potentiality of ISAR imaging.
1.1. Synthetic Aperture Radar (SAR)
1.2. Inverse Synthetic Aperture Radar (ISAR)
1.3. ISAR system
1.4. Examples of applications
2.0 Signal modelling
2.1. Radar-target geometry
2.2. Transmitted signal
2.3. Received signal (Time-Frequency representation)
2.4. Radial motion compensation
2.5. Interpretation of the received signal in the Fourier Domain
3.0 ISAR image reconstruction
3.1. Image formation
3.2. Point Spread Function (PSF)
3.3. Image Resolution
3.4. Analogies and differences with SAR
4.0 ISAR image Autofocus
4.1. Hot Spot (HS) or Prominent Point Processing (PPP)
4.2. Phase Gradient Autofocus (PGA)
4.3. Image Contrast Based Autofocus (ICBA)
4.4. Image Entropy Based Autofocus (IEBA)
5.0 Time window selection
5.1. Max Image Contrast (IC) method
5.2. Ad-hoc techniques for ISAR imaging of ships
6.0 Bistatic and Multistatic ISAR
6.1. Geometry and signal modelling
6.2. Bistatically equivalent monostatic geometry
6.3. Examples: Passive ISAR (P-ISAR) and Emulated Bistatic ISAR
6.4. Multi-channel/Multi-static ISAR (M-ISAR): co-located and distributed M-ISAR
6.5. Multistatic ISAR image autofocus
Dr. Marco Martorella was born in Portoferraio (Italy) in June 1973. He received the Telecommunication Engineering Laurea (cum laude) and Ph.D. degrees from the University of Pisa (Italy) in 1999 and 2003, respectively. He became a Postdoctoral Researcher in 2003, a Researcher/Lecturer in 2005, a permanent Senior Researcher/Lecturer in 2008 and an Associate Professor in 2011 at the Department of Information Engineering of the University of Pisa. He is also a visiting professor at the University of Cape Town where he lectures the course “High Resolution and Imaging Radar” within the International Masters in Radar and Electronic Defence. He has co-authored more than 100 journal and conference papers. He has organised special and invited sessions at international conferences and organised a special issue on Inverse Synthetic Aperture Radar for the Journal of Applied Signal Processing (Hindawi). He has also given lectures and seminars in several research institutions in US, Australia, Asia, South America and Europe and presented tutorials on ISAR at IEEE Radar Conferences. He is the chair of the NATO Task Group on “Multichannel/Multistatic radar imaging of non-cooperative targets”, a member of four other NATO SET Task Groups, an IEEE Senior Member and a member of AFCEA. He received the Australia-Italy award for young researchers in 2008 and the IEEE GRSL Best Reviewer in 2010. His research interests are mainly in the field of radar imaging, including passive, multichannel, multistatic and polarimetric radar imaging.
This course reviews the principles of waveform design and analysis for radar systems. A primary goal of this course is to present waveform design trade space and choices a designer should make in optimizing the waveform parameters for a given radar sensor application. Several waveform design examples are presented that are suitable for typical radar applications. Waveform design considerations are reviewed and characteristics are compared for selecting an optimal waveform for a given application. Waveform modulations covered in this course include LFM, NLFM, poly-phase codes, Costas codes, Barker codes, shift-register codes, quadratic residue codes, and chaotic codes. Waveform sidelobe suppression techniques are also presented. High Range Resolution (HRR) waveform design and super-resolution concepts are reviewed for wideband processing.
This course will enable you to:
• design baseband signal waveforms for multiple sensors
• understand the waveform characteristics and design trades
• specify the waveform parameters and determine the characteristics
• apply linear system principles in characterizing waveform performance
• compare the characteristics of different waveform modulations
• optimize the waveform selection based on sensor requirements
• understand the concepts and methods for waveform sidelobe suppression
• select waveform parameters for high range resolution (HRR) processing
• understand the concepts of super-resolution
Dr. Rao Nuthalapati is currently a Principal Member of Engineering Staff with Lockheed Martin. For more than 17 years with Lockheed Martin, he developed advanced signal and image processing algorithms for radar systems. He also worked at Honeywell, Analog Devices, and Lucent Technologies in avionics, embedded DSP, and wireless systems. Previously, he taught courses in Radar Systems and Digital Signal Processing for the technical staff of Boeing and Honeywell. He obtained his Ph.D. degree in Electrical Engineering from the University of Ottawa. He is a registered Professional Electrical Engineer.
Through-the-Wall Radar Imaging (TWRI) and Urban Sensing is an emerging technology that provides vision into otherwise obscured areas, thereby, facilitating information-gathering and intelligent decision-making. The objectives of TWRI include the determination of the building layouts, discerning the intent of activities inside the building, or detecting, locating, tracking, and imaging of targets inside enclosed structures. These three areas of attributes are highly desirable for a range of civil and military applications, examples being search and rescue missions, hostage rescue situations, and surveillance and reconnaissance in urban environments. The ultimate goal in these applications is to achieve situational awareness in an efficient and reliable manner. This goal is primarily challenged by growing demand on radar systems to deliver high resolution images and more accurate information. This demand, in turn, results in a significant increase in the number of data samples to be recorded, stored, and subsequently processed. The emerging field of Compressive Sensing (CS), which enables reconstruction of a sparse signal from far fewer non-adaptive measurements, provides a new perspective for data reduction in radar imaging without compromising the image quality. Towards the objective of providing quick turnaround and reliable situational awareness in urban environments, these techniques yield efficient sensing operations that allow super-resolution imaging of sparse scenes. In this tutorial, we present a comprehensive treatment of TWRI under compressive illuminations. More specifically, focus will be on CS based approaches to streamline data acquisition with much fewer space-time samples and to provide high-resolution imaging capability for both stationary and moving target detection and localization under challenging urban environments. The discussed methodologies are an integral part of candidate solutions to pressing problems facing the urban sensing technology.
Dr. Fauzia Ahmad received her Ph.D. Since 2002, she has been with the Center for Advanced Communications, Villanova University, Villanova, PA, where she is now a Research Professor and the Director of the Radar Imaging Lab. Dr. Ahmad’s main research interest is in the areas of radar imaging, waveform design, array signal processing, radar signal processing, compressive sensing, and MIMO radar systems. She has coauthored three book chapters and over 110 journal articles and peer-reviewed conference papers in the aforementioned areas. She has been an invited speaker twice at the NATO SET-100 Task Group meetings on Sensing Through the Walls Technologies. She has organized and co-chaired special sessions on through-the-wall radar imaging and urban sensing in the 2007 IEEE Workshop on Signal Processing Applications for Public Security and Forensics (SAFE07), and the 2008 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP08). She chairs the SPIE Compressive Sensing Conference. Dr. Ahmad has been one of the lead investigators on several contracts and grants related to urban sensing from the US Federal agencies, including ARL, ARO, DARPA, AFRL, ONR, and the NSF. She is a senior member of IEEE and SPIE.
MIMO (multiple-input multiple-output) radar refers to the use of multiple transmitters and receivers, for sensing the environment and the targets present in this environment. Basically MIMO radar uses multiple antennas that transmit correlated or uncorrelated waveforms. For the last ten years MIMO has led to extensive research and publications, both in communications and Radar domains. Why such interest for MIMO in radar? Beside the prolific amount of publications, how to assess the interest of MIMO to overcome the current limitations of conventional radar? The tutorial attempts to answer these questions, as well as to provide the tools to understand the link between theoretical considerations and radar system design. After a summary of the state of art – we may notice that MIMO was invented more than 25 years ago – the course will provide the fundamentals of MIMO radar, how to define a MIMO radar configuration, introduce the signal model, waveform design, signal processing, detection and localization. A particular emphasis will be put on the coherent MIMO in conjunction with the unique properties of the MIMO steering vector. A large part of the course will be focused on applications, including MIMO-STAP for GMTI, low frequency radar for coastal maritime surveillance.
State of art, MIMO system in navigation, communication and radar domain;
Flashback to the first MIMO radar, RIAS (SIAR), its advantages and drawbacks.
Definition of MIMO; MIMO and radar diversity;
Coherent, statistical and hybrid MIMO;
Examples of application;
Benefit of MIMO over conventional radar systems.
Signal model and performances:
Power budget of MIMO
Fast or slow time coding, which code for which application?;
MIMO and antenna coupling in physical arrays
Properties of the transmitted pattern.
MIMO waveform design for radar applications:
Waveform schemes: fast time CDMA, FDMA, TDMA, DDMA,..;
Examples of codes: sub-carriers, OFDM codes, PN (pseudo-noise), Hadamard codes.
MIMO signal chain; mathematic formulation;
Estimation of the steering vector;
Impact of the Doppler shift on signal processing;
Detection scheme (Gaussian / non Gaussian noise).
Properties of the MIMO steering vector:
Virtual array / Combined transmit and receive array directivity;
MIMO and high resolution techniques.
Some relevant applications of MIMO to radar:
Bistatic / Multistatic GMTI/STAP;
Low frequency HF radar and application to maritime surveillance (HFSWR).
Marc Lesturgie obtained the Engineering degree in 1985 from ENSAE in France (Ecole Nationale Supérieure de l’Aéronautique et de l’Espace), and a Master degree in Electronic & Microwave from University of Toulouse in 1986. In 2005 he obtained a Research Directorship Habilitation thesis from the University of Paris VI. He joined the French Aerospace Lab (ONERA) in 1987 and worked in a wide range of low frequency and new radar concepts, covering bistatic, multistatic and distributed radars. From 1996 to 2000 he is the head of the “New radar concepts” team in ONERA. In 2006, Marc Lesturgie is appointed as Director of SONDRA (Supelec-ONERA-NUS-DSTA Research Alliance) – a joint laboratory between France and Singapore. In 2007 he is the head of the Electromagnetics department in Supelec.
In 2008, still Director of the SONDRA laboratory, Marc Lesturgie is also Deputy Director at the Electromagnetics and Radar Department of ONERA. Since 2005, he has been also an Adjunct Principle Research Scientist with the Temasek Laboratories, at the Nanyang Technological University in Singapore. Chairman of the SEE/Committee 23 (radio-location and navigation) between 2000 and 2006, he has organized several International conferences, acted as the Technical Chairman of the International Conference on Radar Systems in 2004 (Toulouse) and 2009(Bordeaux), and is the General Chair of the upcoming Radar 2014 International Conference in Lille. Marc Lesturgie is senior member of the IEEE, Fellow and Emeritus member of SEE and lectures regularly on radar topics in French and overseas Universities.
Skywave over-the-horizon (OTH) radars operating in the HF band (3-30 MHz) exploit signal reflection from the ionosphere to detect and track airborne and surface targets at ranges an order of magnitude greater than microwave radars. The ability of OTH radar to persistently monitor remote geographical regions where microwave radar coverage is not feasible or convenient represents the chief advantage of such systems, which are used to provide cost-effective early-warning surveillance over very wide areas at distances of up to 3000 km.
The tutorial provides an introduction to the key principles that underpin OTH radar system design and operation in skywave and surface-wave applications. The unique challenges of operating in the HF environment are described and connected to motivate and explain the architecture of modern operational OTH radar systems. This includes the most influential characteristics of the propagation medium and HF signal environment. The essential properties of various OTH radar subsystems, including antenna arrays, transmit and receive systems, as well as adjunct sensors used for frequency management are also covered in detail.
This is followed by an in-depth description of the core elements of conventional and adaptive signal processing methods used in OTH radar and their application to real-world systems. In addition to theoretical considerations, a highlight of the tutorial is the large number of practical examples illustrating experimental results obtained from processing real data collected by actual HF radar systems. The tutorial also provides insights for the way ahead, and a comprehensive list of references. For these reasons, it is expected to benefit scientists, engineers and students, either starting out in this field, or those wishing to gain a broader understanding of the most important OTH radar concepts.
1. Fundamental OTH Radar Principles
- • Concept of Operation
- • Mission Objectives & Target Types
2. HF Propagation Medium
- • Skywave and Surface-wave Modes
- • Characteristics of the Ionosphere
- • Multipath Propagation
- • Mechanisms causing Signal Distortion
3. HF Signal Environment
- • Clutter from Land and Sea Surfaces
- • Target Echoes
- • Natural Noise Sources & Anthropogenic Interference
- • Mathematical Models
4. Frequency Selection and Waveform Design
- • Aircraft and Ship Detection
- • Challenges in the HF Environment
- • System Design, Nominal Capabilities, Practical Applications
- • SNR and SCR Performance Criteria
- • Resolution, Sidelobes, Ambiguities
5. OTH Radar Subsystems
- • Antenna Arrays
- • Transmitter and Receiver
- • Electronic Beam Steering
- • Frequency Management System
6. Conventional and Adaptive Processing
- • Azimuth, Range and Doppler processing
- • CFAR and Tracking
- • Adaptive Beamforming
- • Space-Time Adaptive Processing (STAP)
- • Live Data Processing Results
Giuseppe Aureliano Fabrizio received his B.E. with honors and Ph.D. degrees from the Department of Electrical and Electronic Engineering at Adelaide University, Australia, in 1992 and 2000. Since 1993, Dr Fabrizio has been with the Defence Science and Technology Organization (DSTO), Australia, where he leads the EW and adaptive signal processing section of the high frequency radar branch. Dr Fabrizio is responsible for the development and practical implementation of innovative and robust adaptive signal processing techniques to enhance the operational performance of modern OTH radar systems. Dr Fabrizio is the main author of over 50 peer-reviewed journal and conference publications, and is a co-recipient of the prestigious M. Barry Carlton Award for the best paper published in the IEEE Transactions on Aerospace and Electronic Systems (AES) on two occasions – 2003 and 2004. In 2007, he received the DSTO Science Excellence award recognizing his contributions to adaptive signal processing for the JORN OTH radar system. In the same year, he was granted a DSTO Defence Science Fellowship to pursue collaborative research at La Sapienza University in Rome, Italy. Dr Fabrizio has delivered OTH radar tutorials at the 2008 IEEE Radar Conference, held in Rome, and at the 2010 IEEE International Radar Conference in Washington DC. He is an Australian representative on the IEEE International Radar Systems Panel, and is currently the VP for Education on the AESS Board of Governors. Dr. Fabrizio was selected as the recipient of the distinguished IEEE Fred Nathanson Memorial Radar Award in 2011 for his contributions to OTH radar and radar signal processing. He is the author of a text book “Over-the-Horizon Radar – Physical Principles, Signal Processing, Practical Applications”, to be published by McGraw-Hill Professional (First Edition, July 2013).
Passive Bistatic Radar is now a mainstream subject, as shown by the large number of publications at conferences and in journals. Such systems have a number of potential advantages. The receiver is passive and so potentially undetectable. There are many illumination sources that can be used, many of them of high power and favorably sited. PBR receiver systems can often be rather simple and low cost, and there is no need for any licence for the transmitter. However, since the waveforms are not explicitly designed for radar use they may be far from optimum for radar purposes. It is therefore necessary to understand the effect of the waveform on the performance of the passive bistatic radar, so as to be able to choose the most appropriate illuminator, and to process the waveform in the optimal way. The tutorial is divided into two parts:
The first part will cover the fundamentals of bistatic radar, including the bistatic geometry and its consequences in the configuration of PBR systems, the bistatic radar equation, its interpretation for PBR and in performance prediction, and the properties of targets and of clutter at PBR frequencies. Emphasis will be placed on the effect of the geometry on the waveform ambiguity function, and on the characterization of urban clutter.
2. Processing and Results
The key aspects of the second part are those which are basically related to the passive features, namely the exploitation of non-cooperative transmitters. Modern digital broadcast waveforms like DAB+ and DVB-T build the focus of processing schemes for passive radars, which are not only of military interest because of their covertness and anti-stealth potential but also of interest for the civilian world, where radar surveillance is needed but additional electromagnetic emissions are not acceptable. The properties of potential illuminators are analysed and processing schemes are proposed. Theoretical approaches and system concepts will be supported by a wide range of measurement experiences with a variety of experimental systems of customized development. An overview of existing experimental systems, demonstrator systems and future trends will conclude the work.
Dr. Hugh Griffiths holds the THALES/Royal Academy Chair of RF Sensors in the Department of Electronic and Electrical Engineering at University College London, England. From 2006–2008 he was Principal of the Defence Academy of Management and Technology. He received the MA degree in Physics from Oxford University in 1975, then spent three years working in industry, before joining University College London, where he received the PhD degree in 1986 and the DSc(Eng) degree in 2000, and served as Head of Department from 2001 – 2006.
His research interests include radar and sonar systems and signal processing (particularly synthetic aperture radar and bistatic and multistatic radar), and antenna measurement techniques. He has published over four hundred papers and technical articles in the fields of radar, antennas and sonar. In 1996 he received the IEEE AESS Fred Nathanson Award (Radar Systems Panel Award), and in 2012 he was awarded the IET A.F. Harvey Prize for his work on bistatic radar. He has also received the Brabazon Premium of the IERE and the Mountbatten and Maxwell Premium Awards of the IEE. He is a Fellow of the IET (previously IEE), Fellow of the IEEE, and in 1997 he was elected to Fellowship of the Royal Academy of Engineering. He serves as President of the IEEE Aerospace and Electronic Systems Society for 2012/2013, and he is an IEEE AES Distinguished Lecturer. He has been a member of the IEEE AES Radar Systems Panel since 1989, serving as Chair from 2007 – 2009, and chaired the Working Group which revised the IEEE Radar Definitions Standard P686 and reaffirmed the Radar Letter Band Standard.
Dr. Heiner Kuschel was born in Cologne in Germany in 1955. In 1980, he received the Diploma in Electrical Engineering from the Technische Hochschule Aachen with emphasis on HF-techniques. Since 1981 he works as a Scientist with the FHP, Forschungsinstitut für Hochfrequenzphysik (Research Institute for High Frequency Physics), since 1999 FHR, Research Institute for High Frequency Physics and Radar Techniques of FGAN (Forschungsgesellschaft für angewandte Naturwissenschaften e.V.) in Werthhoven. The primary subjects of his work are: VHF-Radar, propagation prediction modelling, RCS, and radar systems. This also includes consultancy to the German ministry of defence on industry projects. He has been managing the experimental low frequency radar projects LARA and LARISSA of FGAN and is now leading the passive covert radar team of Fraunhofer FHR. He is leading the passive radar team at FHR and is responsible for the research project ‘semi-active radar for low level coverage’ and the mobile experimental radar projects CORA, DELIA and PETRA. He has been working in NATO research study groups of DRG panel X since 1984 and has been leading several SET technical teams. He is currently the team leader of the NATO task group SET195 on DMPAR verification (deployable multi-band passive/active radar for air defence).
Foliage Penetration (FOPEN) Radar is a technical approach to find and characterize man-made objections under dense foliage, as well as characterizing the foliage itself. It has applications in both military surveillance and civilian geospatial imaging. This Tutorial is divided into three parts.
- • The early history of FOPEN Radar: battlefield surveillance and the early experiments in foliage penetration radar are covered. There were some very interesting developments in radar technology that enabled our ability to detect fixed and moving objects under dense foliage. The most important part of that technology was the widespread awareness of the benefits of coherent radar and the advent of digital processing. Almost as important was the quantification of the radar propagation through foliage, and its scattering and loss effects.
- • FOPEN synthetic aperture radar (SAR) with concentration on development results from several systems. These systems were developed for both military and commercial applications, and during a time of rapid awareness of the need and ability to operate in a dense signal environment. A brief description of each radar system will be provided along with illustrations of the SAR image and fixed object detection capability. The next section will quantify the benefits of polarization diversity in detecting and characterizing both man made and natural objects. There is a clear benefit for use of polarization in the target characterization and false alarm mitigation. Finally the techniques developed for ultra wideband and ultra wide angle image formation will be presented.
- • New research in Multi-mode Ultra-Wideband Radar, with the design of both SAR and moving target indication (MTI) FOPEN systems. Particular note will be taken on the benefits and difficulties in designing these ultra-wideband (UWB) systems, and operation in real world electromagnetic environments. At common FOPEN frequencies, the systems have generally been either SAR or MTI due to the difficulties of obtaining either bandwidth or aperture characteristics for efficient operation. The last two sections of the tutorial will illustrate new technologies that are appearing in the literature that have promise for future multimode operation: the need to detect low minimum discernable velocity movement; and the operation of bistatic SAR in concert with a stationary GMTI illumination waveform.
Dr. Mark E. Davis has over 40 years experience in Radar technology and systems development. He has held senior management positions in the Defense Advanced Research Projects Agency (DARPA), Air Force Research Laboratory, and General Electric Aerospace. At DARPA, he was the program manager on both the foliage penetration (FOPEN) radar advanced development program and the GeoSAR foliage penetration mapping radar. Dr Davis wrote the text”Foliage Penetration Radar – Detection and Characterization of Objects Under Trees”, published by SciTech Raleigh NC in March 2011.
His education includes a PhD in Physics from The Ohio State University, and Bachelor and Master’s Degrees in Electrical Engineering from Syracuse University. He is a Fellow of both the IEEE and Military Sensing Symposia, and a member of the IEEE Aerospace Electronics Systems Society Board of Governors and chairs the Radar Systems Panel.
We cover an advanced Radar detection method called Space-Time Adaptive Processing (STAP). STAP is an advanced signal processing methodology for the Ground Moving Target Indication (GMTI) mode of airborne and space-borne surveillance radar systems. It is used to mitigate the radar’s motion-induced spread-Doppler clutter that interferes with the echo from moving ground targets, in addition to mitigating jamming interference. The tutorial will develop and clearly illustrate the GMTI problem from first principles, showing the need for STAP processing, including the STAP radar signal environment and its mathematical model. Traditional STAP processing solutions will be derived from a detection probabilistic perspective, the most pertinent metric for radar. The course covers state-of-the-art STAP techniques that address many of the limitations of traditional (ideal) STAP solutions, offering insight into future research trends. Additionally, we cover applications of advanced detection algorithms including super-resolution spectral estimation.
Dr. Scott Goldstein is the Chief Technologist for Dynetics, Inc., and the Manager of the Advanced Missions Solutions Group in Chantilly, VA. He has over 30 years of operational, engineering, leadership and management experience. He has performed fundamental research and development in Radar detection and estimation theory, Space Time Adaptive Processing, as well as in advanced systems concepts involving intelligence sensors, ISR, space superiority capabilities and cyber exploitation. He is a Fellow of the IEEE (for contributions to adaptive detection in radar and communications), a Fellow of the Washington Academy of Sciences and a member of the IEEE Radar Systems Panel. He received the 2002 IEEE Fred Nathanson Radar Engineer of the Year Award.
Dr. Mike Picciolo is the Associate Chief Technologist for Dynetics and Chief Engineer of the Advanced Missions Solutions Group in Chantilly, VA. He has in-depth expertise in Radar, ISR systems, Space Time Adaptive Processing and conducts research in advanced technology development programs. He served as Engineering Director and Director of Advanced Programs at QinetiQ North America. Previously, he served as a Chief Technology Officer within ManTech and as a Chief Scientist at SAIC. He has over 26 years of experience working for the Dept. of Defense (DoD), Intelligence Community (IC), and the Department of Homeland Security (DHS). He has deep domain expertise in SAR/GMTI radar, communications theory, waveform diversity, wireless communications, hyperspectral imagery, IMINT, SIGINT, and MASINT intelligence disciplines.
Dr. Jacob Griesbach is the technical director at Applied Defense Solutions (ADS). He specializes in radar and sonar signal processing, astrodynamics, GPS signal processing, STAP, adaptive beamforming, statistical signal processing, filterbank design, and adaptive systems. Dr. Griesbach earned his BSEE, MSEE, and PhD degrees from the University of Colorado in Boulder in 1995, 1997, and 2000, respectively.
Dr. Wil Myrick is currently a Principal Engineer at Dynetics. He is recognized as a world leader in MASINT in addition to having over 18 years of experience in STAP, SIGINT, communications, and anti-jamming for GPS. He was awarded the U.S. Black Engineer of the Year Award for Career Achievement in Industry for his outstanding contributions to the MASINT community. Dr. Myrick holds MS and PhD degrees in Electrical Engineering from Purdue University and a BS in Electronics Engineering from Norfolk State University.
This course provides a broad overview of traditional and current antenna array topics with emphasis on design and practical implementations. The course begins with an overview and historical development of antenna arrays. Next, array factor analysis and synthesis are covered. A large part of the course is dedicated to more practical issues such as the array architecture and mutual coupling. Tradeoffs on various designs will be presented. Arrays in the time domain is becoming an increasingly important topic. Wideband arrays transmit very narrow pulses that cover a broad frequency spectrum. These arrays must be analyzed in the time domain instead of the traditional narrowband frequency domain. In addition, adaptive and reconfigurable arrays are important for modifying an array’s performance in order to adaptive null interference, change frequency bands, or switch beams.
- Introduction (~30 min)
- a. History of Phased Arrays – from the first phased arrays to the complex monstrosities of today and those of the future.
- b. Arrays of Point Sources – concepts of a phase center and far field.
- Array Analysis and Synthesis (~40 min)
- a. Fourier analysis and rules of thumb – mathematical representations, simple formulas for performance, element spacing, Linear, planar, and conformal arrays are considered.
- b. Techniques for low sidelobe and null synthesis – the z-transform, low sidelobe synthesis, null placement, difference patterns.
- Array Design (~70 min)
- a. Antenna elements – narrow band to wideband, big to small, the element pattern, concept of the unit cell.
- b. Feed network – getting signals to and from the elements, corporate feeds, space feeds, digital beamforming, subarrays.
- c. Components – phase shifters, TR modules, time delay units, etc.
- d. Mutual coupling – element pattern effects, Floquet modes, scan blindness, finite vs. infinite arrays.
- Timed Arrays (~70 min)
- a. Signals and arrays – time representations, signals, bandwidth, impact on arrays.
- b. Wideband issues – signal dispersion, time delay units and phase shifters, grating lobes.
- c. Adaptive arrays – overview of adaptive signal processing for antenna arrays.
Randy L. Haupt received the BSEE from the USAF Academy (1978), the MS in Engineering Management from Western New England College (1982), the MSEE from Northeastern University (1983), and the PhD in EE from The University of Michigan (1987). He is Professor and Department Head of EECS at the Colorado School of Mines. Prior to that, he was an RF Staff Consultant at Ball Aerospace & Technologies, Corp., Senior Scientist and Department Head at the Applied Research Laboratory of Penn State, Professor and Department Head of ECE at Utah State, Professor and Chair of EE at the University of Nevada Reno, and Professor of EE at the USAF Academy. He was a project engineer for the OTH-B radar and a research antenna engineer for Rome Air Development Center early in his career. He is co-author of the books Practical Genetic Algorithms, 2 ed., John Wiley & Sons, 2004, Genetic Algorithms in Electromagnetics, John Wiley & Sons, 2007, and Introduction to Adaptive Antennas, SciTech, 2010, as well as author of Antenna Arrays a Computation Approach, John Wiley & Sons, 2010. Dr. Haupt was the Federal Engineer of the Year in 1993 and is a Fellow of the IEEE and Applied Computational Electromagnetics Society (ACES). He serves as an Associate Editor for the “Ethically Speaking” column in the IEEE AP-S Magazine.
When radar systems are discussed in the literature, it is in the context of a sensor providing observations of the environment. While some of those measurements are responses from coherent waveforms of finite duration, the environment is treated as stationary with at most linear motion on the targets. Target tracking addresses the integration of measurements into a longer term picture. Target tracking is separated into two parts: track filtering and measurement-to-track data association. Track filtering is the process of estimating the trajectory (i.e., position, velocity, and possibly acceleration) of a track from measurements that have been assigned to that track. Measurement-to-track data association (or data association) is the process of assigning a measurement to an existing track or as a detection of newly found target or false signal. This tutorial will give a survey of the target tracking concepts associated with the development and implementation of target tracking algorithms in radar systems. Students will gain exposure to the concepts associated with radar tracking, a familiarity with the basic mathematics and notation used in target tracking, and an appreciation of the role of tracking in radar systems. It is intended primarily for engineers and scientists with prior familiarity with radar systems.
|Hour 1||Introduction to Target Tracking|
|Hour 2||Target Track Filtering|
|Hour 3||Radar Track Filtering|
|Hour 3.5||Multiple Target Tracking|
|Hour 4.5||Performance Assessment of MTT Algorithms|
William Dale Blair, Ph.D., is a principal research engineer with GTRI and currently serves as the Technical Director for the C2BMC Knowledge Center of the Missile Defense Agency (MDA). Since joining GTRI in 1997, Dr. Blair has led a multiorganizational team in the development of multiplatform-multisensor-multitarget benchmarks to both air defense and ballistic missile defense. His projects at GTRI focus mostly the modeling and simulation and algorithm assessment associated with the sensor netting for the battle management, command, and control for the ballistic missile defense system. Dr. Blair’s research is reported in over two hundred articles which include 38 refereed journal articles. Dr. Blair served as the Editor for Radar Systems for IEEE Transactions on Aerospace and Electronic Systems (T-AES) 1996-99 and Editor-In-Chief (EIC) for IEEE T-AES from 1999-2005. Dr. Blair is a Fellow of the IEEE and recipient of the 2001 IEEE Nathanson Award for Outstanding Young Radar Engineer. He originated and coordinates four short courses, Target Tracking in Sensor Systems, Target Tracking Concepts, Advanced Target Tracking for Air Defense and Advanced Target Tracking for Ballistic Missile Defense, for the Professional Education Department of the GIT. Dr. Blair is coeditor and coauthor of the book, Multitarget-Multisensor Tracking: Advances and Applications III, and the author of chapter 19 “Radar Tracking Algorithms” and coauthor of chapter 18 “Radar Measurements” of the new edition of Principles of Modern Radar. He has also served as the coordinator of the ONR/GTRI Workshop on Target Tracking and Sensor Fusion for 1998 through 2011. He was recently elected to the Board of Governors (BoG) for the IEEE Aerospace and Electronics Systems Society (AESS) for 2012-2015. Dr. Blair was elected by an open vote of the members of AESS. He previously served on the BOG of IEEE AESS from 1998-2003 and 2005-2010.
Two dimensional high-resolution radar imaging is fundamental to many civilian and military radar applications and today is utilized in a very wide variety of applications. Map like imagery provides detailed and real time information about the surface of the earth, objects located on the surface and can also enable imaging of airborne targets. High resolution radar imaging provides data for climate change modeling, crop growth, de-forestation and erosion estimation as well as being a key military surveillance tool. It is true to say that in many domains it has become an indispensable remote sensing tool that is becoming more and more important and more and more widely deployed as the need for wide-area and all-weather coverage grows.
This tutorial will introduce the key concepts that underpin high resolution imaging using radar sensors. Particular emphasis will be given to Synthetic Aperture Radar (SAR) that has become the workhorse tool of the remote sensing and military surveillance communities. In addition, its natural counterpart, Inverse Synthetic Aperture Radar (ISAR) used for imaging moving objects will be described along with emerging methods that include tomography, Doppler beam sharpening, bistatic imaging and Doppler SAR. The tutorial will go on to explore image interpretation and information extraction and will conclude by exploring cognitive imaging techniques that have potential to lead to vastly superior performance.
This tutorial is suitable for PhD and early career postgraduates working in research and/or development as well as the more experienced radar professional seeking to work in radar imaging and image exploitation or those who wish to broaden their knowledge of radar sensing.
Professor Chris Baker is the Ohio State Research Scholar in Integrated Sensor Systems at The Ohio State University. Until June 2011 he was the Dean and Director of the College of Engineering and Computer Science at the Australian National University (ANU). Prior to this he held the Thales-Royal Academy of Engineering Chair of intelligent radar systems based at University College London. He has been actively engaged in radar system research since 1984 and is the author of over two hundred publications. His research interests include, Coherent radar techniques, radar signal processing, radar signal interpretation, Electronically scanned radar systems, natural echo locating systems and radar imaging. He is the recipient of the IEE Mountbatten premium (twice), the IEE Institute premium and is a Fellow of the IET. He is a visiting Professor at the University of Cape Town, Cranfield University, University College London, Adelaide University, Wright State University, and Nagyang Technology University, Singapore.
The idea of cognitive radar originated in 2006 with the publication of a paper entitled “Cognitive radar: a way of the future” authored by Simon Haykin, which appeared in the IEEE Signal Processing magazine. It has come a long way in the last 7 years. To be specific, it has already proven itself to be a way of the future and not only that, we are beginning to look beyond cognitive radar in the traditional sense. In this tutorial, I will cover the following topics.
- First and foremost, cognitive radar (of the monostatic kind) is built in a way that it can make effective use of the human brain in a ground‐breaking manner. This being so, in the first part of the tutorial, I will describe fundamental principles of human cognition. In particular, following Fuster’s paradigm, the principles are as follows:
- a. The perception‐action cycle
- b. Memory
- c. Attention
- d. Intelligence
- e. Language
When you get to learn these principles, you begin to realize that they constitute the perfect engineering basis for designing a cognitive radar.
- Except for language, I will describe each of these principles, their functions, and how they can be individually implemented.
- Next, I will address mathematical aspects of cognitive radar, namely:
- a. Bayesian estimation, which includes the Kalman filter as a special case.
- b. Dynamic programming, which includes reinforcement learning as an approximation.
- The most significant discovery made in our Cognitive Systems Laboratory is the two‐state model, which embodies the following:
- a. Deterministic target model.
- b. Dynamical entropic‐state model.
Both of them change from one perception‐action cycle to the next in accordance with environmental variations. The first model relates directly to the well‐known state‐space model of the environment. As for the dynamical entropic‐state, that is defined in terms of Shannon’s entropy, it relates to environmental uncertainties. Most importantly, it provides the needed feedback information of the right kind from the receiver to the transmitter. It is on account of this new model that we are enabled to see cognitive radar mimicking the brain for the first time ever so closely. But above all, by minimizing the information gap between relevant information contained in the radar returns and the sufficient information, we begin to tackle the most important issue of them all: Risk Management, which lies at the heart of what cognitive radar is all about.
- With all this material at hand, the stage is finally set for presenting experimental results that will demonstrate the information‐processing power of cognitive radar.
- I will conclude the tutorial by briefly discussing Cognitive Networks, which is really where we begin to see the emergence of not only a new of thinking about radar but start to think of the kind of innovative applications that are beyond the scope of what we are currently able to do.
Simon Haykin is Distinguished University Professor in the Department of Electrical and Computer Engineering at McMaster University, Canada. He is Fellow of the IEEE, Fellow of the Royal Society of Canada, recipient of the URSI Henry Booker Gold Medal for his contributions to wireless communications and radar, and recipient of the Honorary Degree of Technical Sciences from ETH, Zurich. Switzerland. Professor Haykin’s research program is focused on Cognitive Dynamic Systems, with particular emphasis on a new generation of engineering systems exemplified by cognitive radio, cognitive radar, cognitive control, and lately, cognitive networks.