Poster Special Sessions

2020 IEEE Radar Conference: Special Sessions

Special Sessions are an important feature of leading technology conferences. Special Sessions afford the possibility to truly reflect the current state-of-the-art of modern research fields in the setting of a larger international conference. Through these highly focused sessions, organizers can work with authors to coordinate contributions around a well-defined session narrative.

Submit your proposal!

Prospective Special Session organizers should submit their proposal using this form (PDF) or this form (Word).
Please send the completed form to before December 20, 2019.
The notification of acceptance of a Special Session proposal is January 31, 2020.
Upon acceptance, session organizers must liaise with invited speakers to submit their papers by March 30, 2020 (i.e., invited speakers may need to begin preparing their papers before the Special Session proposal is accepted).


  • Organizers shall be no more than two and they cannot appear as co-authors of more than one paper each.
  • The organizers should make sure that authors are invited prior to submitting Special Session proposals.
  • All papers submitted to a Special Session will undergo the normal peer-review process.
  • Please bear in mind that a strict limit of 5 papers has been set for each session. Therefore, should the organizers invite a larger number of speakers and should all the papers be accepted, they would be compelled to move some of the contributions received to regular sessions.

Oral Special Sessions

SS1 – Quantum radar: real world experiments and new theory

Fred Daum, Bhashyam Balaji

This session covers both recent experiments for X-Band quantum radars as well as new theory to explaintheir performance. Quantum radar actually works in the real world, as shown by two independentexperiments within the last year, both of which are represented at our special session. We show thesuccessful results of these two real world experiments and derive the new theory for ROC curves and SNR forquantum radar. We also cover practical engineering topics such as cost & SWAP for quantum radars vs.classical radars. Quantum radar is very new and very important. Quantum radars depend on entanglementof photons generated by Josephson junction devices cooled by cryogenic dilution refrigerators, and hencethere are significant practical issues of cost and SWAP that we quantify. This topic is inherently difficult tograsp because it is based on quantum mechanics and radar engineering and cryogenic technology. Thespeakers are world class researchers in quantum radar who are carefully chosen to be excellent speakers.We will try very hard to make this topic accessible to normal radar engineers.

SS2 – Topics, Trends and Challenges in Cognitive Radar

Graeme E. Smith, Kristine L. Bell

The field of cognitive radar seeks to create flexible, autonomous radar systems that respond tothe local environment and mission objectives to achieve the best system performance. The fieldhas become highly visible over the last fifteen years and is the subject of much research anddiscussion. There are now many researchers and research groups exploring different aspects ofcognitive radar. This session will provide a focal point for this popular line of radar research atthe conference.

The proposed special session will provide a detailed overview of current topics, trends, andchallenges in cognitive radars with papers and presentations from leaders in the field. Thetopics of the papers in the session were identified by the session chairs–Dr Smith and DrBell–to ensure the flow of the session and to provide broad coverage of topics, applications andviewpoints in a cohesive manner. Based on their personal experience researching cognitiveradar, Dr Smith and Dr Bell identified and approached the leading researchers in the field andrequested they contribute a paper on one of the selected topics. The author group is diverse,with international representatives from industry, academia, and govt research labs.

The response to this more curated approach has been very positive. In some instances, at therequest of the session chairs, researchers who do not normally work together agreed tocollaborate to ensure they give a holistic discussion of the paper topic. As we develop thesession we shall ensure all authors have good visibility of its content. This will enable easy“cross-referencing” during the talks to further increase the session cohesion.

The structure of the session will be as follows. The opening paper will give a definition of thefield and address the question: what is a cognitive radar? It will be followed by a paper exploringcognitive radar architectures and how they facilitate channel/environment estimation andsupport spectral coexistence. There will then be two papers exploring cognitive radarmethodologies. One will address the role of statistical methods for implementing the“perception-action” cycle and the other will examine how neural networks and machine learningcan be used to create cognitive radars. The final paper of the session will explore thepracticalities of implementation and the impact on the user community.

SS3 – Sparse Array Design Techniques for Radar Applications

Xiangrong Wang, Elias Aboutanios

Sampling using a set of spatially distributed antennas finds extensive applications, especially in radarsystems. Sparse arrays are under-sampled antenna arrays, in which several antennas are removed from theoriginal configuration. In addition to the employed signal processing algorithms, the array configurationcharacterizes the structure of spatial filters and affects the underlying radar funtionality. Therefore, sparsearrays may be designed to achieve a desired beampattern and avoid spatial aliasing by optimizing theantenna placements. There are many applications which require different sparse arrays, ranging from DOAestimation to adaptive beamforming.

Different objectives lead to differed sparse array configurations. From the perspective of DOA estimation,structured sparse arrays such as nested arrays and coprime arrays are easy to constrcut by following adeterministic formula to place antennas and enable the estimation of more sources than physical antennas,while they might lead to significantly low signal-to-noise or signal-to-interference ratios in terms ofinterference suppression. Unstructured sparse arrays that optimize antenna placement under a specificcriterion based on the knowledge learned from the sensed environment exhibit situational awareness andobjective pertinence. This special session brings together a number of contributions on both structured andunstructured sparse arrays, which are established as state-of-the-art sparse array design techniques.

SS4 – Progress in radar techniques for detection, tracking, and classification of small drones

Francesco Fioranelli, Carmine Clemente

Small UAVs, commonly known as drones, have been recently used for many applications and newcapabilities in the commercial civilian sector, but there is also significant concern about their potentialmisuses, either involuntarily or for illicit purposes.As radar systems are one of the proposed technologies used for monitoring small UAVs, the aim of thissession at the 2020 IEEE Radar Conference is to provide examples of some of the most recent innovationsand trends in radar research regarding the study, collection, and applications of radar signatures of thisemerging class of targets.

The organizers (together with Dr F. Colone from Roma La Sapienza University) have successfully managed asimilar special session at the 2019 IEEE International Conference in Toulon, with over 10 accepted paperspresented across two sessions and good attendance. This is a sign of the persistent interest of the researchcommunity in the topic of radar signatures of drones, which is promising for organizing a further session inFlorence.Topics of interest will include but not be limited to: classification algorithms for distinguishing differentmodels, payloads, and false targets such as birds; active and passive radar techniques for monitoring andsurveillance; detection algorithms; characterization of RCS.

SS5 – Emerging technologies for Radar Applications: Compressive Sensing meets Machine Learning

Matthias Weiß, Laura Anitori

The detection, estimation and classification of targets in radar signals are fundamental processes. In areaswhere huge volumes of data are available to train neural networks (NN), machine learning (ML) has beenable to achieve tremendous success, for instance in pattern, image, and speech recognition. In parallel,compressive sensing (CS) is an emerging acquisition and signal processing technique that enables targetreconstruction from measurements with missing data or to achieve higher resolution than conventionalmethods using a combination of random sampling and sparse signal reconstruction algorithms. In the pastdecade, a lot of theoretical progress has been made in CS and simulations have demonstrated the potentialof CS methods to improve radar performance. The combination of CS and ML can solve the problem ofmissing data volumes, making these methods complementary in situations where large data volumes arenot available.

The main task of this invited session is to bring together the communities of CS and ML to foster theexchange of ideas and to pave the way for new approaches on both these emerging technologies bycombining the best of both worlds.

SS6 – Dual-function radar/communication systems

Aboulnasr Hassanien, Shannon D. Blunt

In recent years, the demand for wireless connectivity has skyrocketed, leading to an explosive growth inindustrial and wireless communications. The need for a fast and reliable wireless connection necessitatesthe efficient utilization of the limited radio frequency (RF) spectrum resources. Due to this acceleratingdemand, however, the RF spectrum is becoming increasingly crowded. Consequently, the concept of RFspectrum cohabitation has emerged that is based on the notion of allowing communication systems andother RF applications to share spectrum in a variety of new and interesting ways. Competition overbandwidth between radar and communications can be directly alleviated if the radar and communicationsystems are designed jointly and deployed from a single platform. The concept of joint operation of radarand communications leads to low-SWaP (Size, Weight and Power consumption) requirements that anincreasing number of commercial applications demand while facing the spectrum scarcity challenge.

Dual-function radar communication systems represent a timely and relevant research topic due to anumber of factors, including advances in radar signal processing techniques such as waveform design,space-time adaptive processing, and sparse signal processing methods. This special session is proposed inthat spirit and brings together 5 papers by worldly renowned researchers covering both theoretical andpractical work on radar and communications dual functionality.

SS7 – Satellite sensing of the atmosphere: radar technologies and methods for advancing atmospheric and climate science

Simone Tanelli, Luca Facheris

The understanding of Earth’s water and energy cycle is a major science challenge to be addressed forunderstanding the changing climate and to make wise decisions that will affect everyday life. Challengesidentified by the World Climate Research Programme (, include"Clouds, Circulation and Climate Sensitivity" and "Understanding and Predicting Weather and ClimateExtremes" call for improved systems for observing clouds and precipitation at global scale. To this purpose,missions based on radars have proven their suitability.The first precipitation radar in orbit (1997-2015) used Ku frequency and was part of the NASA/JAXA TropicalRainfall Measurement Mission (TRMM). A dual frequency radar (DPR) was deployed on the CoreObservatory (CO) of the NASA/JAXA Global Precipitation Measurement (GPM) mission (launched onFebruary 27, 2014). to obtain more accurate precipitation estimation and classification. Higher frequencies(94 GHz) have been used so far by the nadir-looking Cloud Profiling Radar (CPR) of the NASA CloudSat inorbit since 2006. Such approach will be continued by EarthCARE, the next joint mission of European SpaceAgency (ESA) and JAXA EarthCARE, (launch expected in 2022). The recent trend in active remote sensingfrom satellite is to migrate from high cost platforms to a network of small satellite, capable of assuringhigher revisit time and that are relatively easy to launch and to maintain, being built upon standardplatforms, such as CubeSat. Such concept has been demonstrated by recent missions, but more missionsusing these standards are expected. Multi-satellite observatories, including multifrequency radars such asthose fostered in the Aerosol and Cloud, Convection and Precipitation (ACCP) NASA initiative are beingproposed.

This session will summarize the most important efforts ongoing in this field, focusing to the transition fromcurrent satellite borne radar systems and technologies to future architecture, technologies and methods tobe adopted by future missions.

SS8 – Advances in ground based radar remote sensing of clouds and precipitation

Frank S. Marzano, Luca Baldini

Weather radar is one of the most important assets of weather services, which manage networkedradars at S and C frequency to monitor weather and precipitation on country-wide areas. Startingfrom year 2000, most weather radar infrastructures are based on Doppler dual polarization radarsystems. Although such system are based on well consolidated technologies, improving techniquesfor data analysis and interpretation is a field of active research. In particular, methods based onartificial intelligence (AI) have become popular also for weather radar. In the recent years, newtechnologies and methods have emerged in radar weather observations. The paradigm of densenetworks made of smaller X-band dual polarization radars is increasingly adopted to provide highresolution data for sensitive areas such as densely populated metropolitan areas. The use of solidstate amplifiers, in addition to several advantages, poses specific challenges to mitigate the lack ofadequate peak power preserving space resolution. Continuous efforts are devoted to introduceelectronical steering antennas to improve time resolution of 3D structures of thunderstorms.Finally, spectral analysis carried out at different wavelength is shedding lights on cloud propertiesand important precipitation process. The proposed session aim to present examples of cuttingedge research addressing all the above mentioned challenges.

SS9 – Radar for Health Monitoring and Biomedical Applications

Fauzia Ahmad, Francesco Fioranelli

Radar-based remote monitoring of human vital signs and activities is a topic of great research interest dueto its potential applications in health monitoring of patients outside of a hospital setting, rehabilitation, andeldercare. Current research has demonstrated that high accuracy can be achieved, but only under limitedcircumstances. Low signal-to-noise ratio, high aspect angles, obstructions, dynamic environments,discrimination of highly similar activities, non-focal motion, and the wide ranging, time-varying nature ofhuman activities all remain challenges to robustness.At the same time, radar imaging is becoming a promising alternative/complementary technique toexisting imaging modalities for breast cancer detection and treatment response monitoring. Althoughencouraging results have been published, several outstanding challenges, such as low signal-to-clutterratio, tissue heterogeneities, low resolution, and pulse distortions, still exist.Overcoming the challenges in all aforementioned healthcare and biomedical applications requiresadvancing the state-of-the-art in signal processing and machine learning techniques. The proposed sessionwill focus on the advanced signal processing and learning techniques for human activity monitoring andbreast cancer screening with the aim of addressing these outstanding challenges.

SS10 – Urban remote sensing using SAR

Paolo Gamba, Fabio Dell’Acqua

This session will address some of the latest results in urban remote sensing using SAR, and includes some ofthe most renewed international experts in SAR data processing, modeling, interferometry and tomographyapplied to urban areas.

SS11 – Multi-Function Spectral System Co-Design

Daniel Bliss, Athina Petropoulu

In the proposed session, we explore the concepts of co-designed multi-function spectral systems. Weinvestigate the joint development of radar, communications, and other sensing systems. We bring togetherexperts on these joint systems to present advances concepts, theory, signal processing, and experimentalexamples.

SS12 – Multitemporal SAR image processing and analysis

Sebastiano Bruno Serpico, Emmanuel Trouvé

The availability of several satellite missions worldwide that regularly acquire SAR images and the possibilityof SAR sensors to view the Earth surface even in presence of cloud coverage make of SAR an ideal source ofdynamical information about our planet. However, extracting information from SAR images is not a trivialtask at all, as SAR image interpretation (less intuitive with respect to optical image interpretation) requiresthe knowledge of physical interaction phenomena occurring between EM waves and scattering surfaces; inaddition, the presence of “speckle” causes the typical noisy appearance of SAR images, which makesaccurate information extraction more difficult. In particular, when considering multitemporal SAR images,two important information extraction tasks are the analysis of couples of multitemporal images and theanalysis of image time series. The purpose of the analysis may be the detection of changes on the groundbetween the two acquisition dates or during the observation period of the time series; the challenge in thiscase is to separate significant changes from other sources of variability (random noise, difference inacquisition modalities, seasonal variations, etc.). Another important objective of the analysis may be theuse of the dynamical information (extracted by identification of temporal patterns, seasonal evolutions,etc.) to better distinguish and/or characterize the different portions of the viewed area. The applicationsmay be of scientific, societal, or economic interest, such as environmental studies, urban monitoring,natural disaster recovery, precision agriculture, etc. Some of the most important methodologies involvedwill be dealt with by the articles presented in the special session, whose experimental results will coverseveral real-world applications. To this end, a variety of SAR multitemporal data will be considered(acquired by a single SAR sensor, by different SAR sensors, or even by a SAR and an optical sensors; singlepolarization or multi-polarization images), which call for specific analysis methods.

SS13 – SAR meets AI

Mario Costantini, Giuseppe Scarpa

Moving from the computer vision domain, artificial intelligence (AI) and, in particular, deep learning (DL)methods have rapidly spread to many nearby research fields, including remote sensing. Classical tasks suchas land cover classification, target detection, resolution enhancement, segmentation, and so forth, in fact,have been already successfully addressed for applications dealing with passive imaging systems. Lessobvious is the DL impact on radar-based applications such as those using synthetic aperture radar (SAR)images, due to the complex nature of the relationship between radar signals and ground objects, and, inparticular, to the unavailability of big labeled SAR datasets. However, early attempts have shownencouraging results. Examples are despeckling, target detection, forests mapping, land cover classification,to mention a few.With these premises, the aim of this special session is to provide a picture about the paradigm shift frommodel-based to data-driven approaches (specifically, DL or other modern AI methods) for extraction ofinformation from SAR data. Papers falling in this picture, of either theoretical or application nature, arewelcome.

SS14 – Coexistence of radar and communication systems

Stefano Buzzi, Stefano Fortunati

Radar technology has been evolving towards higher resolution and higher precision detection instrumentswith an ever-increasing list of functionalities. A modern radar system should be able to change transmit-waveform and operating frequency band on-the-fly, depending on the specific function to be implemented,and the perceived operating environment. Clearly, such an ample flexibility demands radars having accessto a sizeable portion of the electromagnetic spectrum. On the other hand, the rapid growth of high-quality/high-rate wireless communications (4G and 5G) has rendered the scarcity of radio frequency (RF)spectrum increasingly critical.

Therefore, coexistence between radar and communication systems using overlapping bandwidths has cometo be a primary investigation field in recent years.The goal of this special section is then to gather together renewed experts from both the radar and thecommunications communities and facilitate a fruitful exchange of views on coexistence between radar andcommunication systems.

Topics include, but are not limited to:

  • Radar and communications signal models,
  • Joint co-design
  • Cognitive systems,
  • Waveform design,
  • MIMO radar and communication systems,
  • Signal processing techniques.

SS15 – Millimeter-Wave Synthetic Aperture Radar

Kumar Vijay Mishra, Lam H. Nguyen

Millimeter-wave (mm-Wave) remote sensing has become increasingly popular today because the very wide,unlicensed bandwidth available at mm-Wave band has potential for very high-resolution applications. Inaddition, the mm-Wave components have reduced dimensions thereby enabling fine cross-range resolutionlimits with moderate size apertures. Further, the frequencies are human-safe and, at close-ranges, thesignal experiences little attenuation. At present, mm-Wave radars are employed for short-range targetdetection and high-resolution imaging in applications such as automotive target sensing, body scanners,through-wall imaging, 3D holographic and millimeter wave tomography, and scanned interferometrictomography. In this context, mm-Wave synthetic aperture radar (SAR) has captured significant researchinterest lately. The high-resolution image reconstruction hardware, unique bi-static and polarimetricphenomenology, and advanced data-driven processing are some of the features that distinguish mm-WaveSAR from other similar systems.

These challenges are driving recent growth and opening new frontiers in research on signal processingmodels and algorithms, hardware implementations and platforms to enable mm-Wave SAR. In past fewyears, publications such as IEEE Transactions on Microwave Theory and Techniques, Elsevier Journal ofInfrared, Millimeter, and Terahertz Waves, Proceedings of SPIE, and IEEE Transactions on Terahertz Scienceand Technology have regularly reported breakthroughs in this area. The Passive and Active Millimeter WaveImaging session of 2019 SPIE Defense + Commercial Sensing conference featured quite a few contributionson mm-Wave SAR.

Some recent novel applications of mm-Wave SAR include airborne forward-looking SAR (FLoSAR) andautomotive SAR. Such devices employ SAR for zero-visibility landing, self-navigation and driver assistance.For example, the downward motion of FLoSAR is similarly useful in extracting the height or elevationinformation for 3-D imaging. Similarly, azimuth resolution of the automotive radar is improved by a side-looking SAR by exploiting the movement of the vehicle.

While mm-Wave imaging has been adequately addressed in the literature, mm-Wave (and even sub-millimeter or THz) SAR is an emerging research frontier. Enhancements in resolution, appropriate scanstrategies, unsuitability of GPS in platform motion compensation, and development of deployableprototypes are some of the aspects that mm-Wave SAR need to address. It is our intention to use this specialsession to highlight the latest developments in mm-Wave SAR and so demonstrate both the depth andbreadth of this emerging field.

Our objective is to highlight the challenges and opportunities in SAR aspects such as signal processing,scanning, phenomenology, guidance in deteriorated vision environment, and polarimetry. We believe that aspecial session in the 2020 IEEE Radar Conference (RadarConf) is ideally suited to reach wider community ofradar practitioners.

SS16 – Emerging Technologies in Automotive Radars

M. R. BhavaniShankar, Marina Gashinova

We are witnessing an autonomy race to get the first fully self-driving car on the road. This boom inautomotive research is driving many technological, socio-political, economic, and environmental policiesaround the world. The radar community has emerged at the forefront of fulfilling the promise of a self-driving car. As the automotive community inches closer to accomplishing this goal, more and newerproblems get identified. This cycle is leading to emergence of new technologies in automotive radar. As aresult, current sophisticated automotive radars have much less in common with the radars developed just afew years ago.For example, there has been a quantum leap in automotive imaging radars with the development ofsynthetic aperture processing for identifying objects from a moving vehicle. The developments in machinelearning have inevitably penetrated automotive research. Many signal processing algorithms earlier appliedto only conventional radars are now increasingly re-interpreted and adapted for automotive radars. Giventhe rapid pace of developments in this area, a technology becomes outdated and outperformed within thesame year.The IEEE Signal Processing Magazine published a two-part series on modern radar signal processingtechniques in 2019, wherein a number of articles dealt with automotive radar technologies highlighting theexplosive growth in research in this area. The IET Radar, Sonar & Navigation published a similar special issuein 2018. Recently, a number of other leading conferences such as Asilomar 2019, ICASSP 2020, CAMSAP2019, Radar 2020 have either featured a special session on new automotive radar technologies or includeda tutorial on the same topic. This series of activities not only highlight the diversity and importance of thistopic but also a need to keep involving leading researchers on the dynamically changing automotive radarresearch.Our objective is to highlight the challenges and opportunities in these new radar technologies covering thephenomenology, system architecture, circuit technology, imaging, signal processing, scanning, and learningfor self-driving. We believe that a special session in the 2020 IEEE Radar Conference (RadarConf) is ideallysuited to reach wider community of radar practitioners.

SS17 – Interference in Automotive Radars

Kumar Vijay Mishra, M. R. Bhavani Shankar

The automotive radar community is at the forefront of technologies that hold the promise of delivering fullyself-driving cars. As the number of vehicles equipped with such sensors rise, automotive developers areconcerned about the inevitable problem of mutual interference among different radars. The problem is sosevere and specific to automotive radars that a single effective solution is yet to be identified. The low-costcircuitry of automotive radars imposes additional challenges in importing existing solutions from otherapplications.Another undesired and unavoidable signal in automotive radars is the presence of weather clutter. Somegroups (e.g. FZI, Germany) have turned this challenge in to a useful application, e.g. opportunisticestimation of rainfall rate using automotive radar sensors. However, effective removal of rain, drizzle, snowand graupel remans an active topic of research in automotive radars.Apart from the coexistence of multiple radars in a crowded traffic environment, the spectrum sharing withcommunications systems is also a major concern. However, this topic has been dealt in multiple specialsessions in different conferences in the past. Therefore, we omit this topic here and focus on only new formsof interference in automotive radars.Major players in the automotive sensor market, like Volvo and Veoneer, are pursuing studies on the nextgeneration of “interference-free automotive radars”. Several international studies – the EU MOSARIM,ENABLE-S3, and IMIKO RADAR are devoted to identifying various aspects of this problem. There has beenscattered but increasing literature on automotive radar interference in recent conferences and journals. TheIEEE Signal Processing Magazine special issue on radar techniques (September 2019) published acomprehensive review article on existing interference mitigation techniques (Alland et al.: “Interference inAutomotive Radar Systems: Characteristics, mitigation techniques, and current and future research”). Theautomotive radar special sessions in IEEE RadarConf 2019 and 2018 also featured at least one talk on thistopic. Given the rapidly development in automotive research, these activities highlight only a fraction ofongoing efforts in interference mitigation.Our objective is to highlight the breadth and depth in modeling, estimating, and processing various radarinterferences by bringing together leading researchers in automotive radars. We believe that a specialsession in the 2020 IEEE Radar Conference (RadarConf) will be a topical contribution and beneficial forawider automotive radar community.

SS18 – Distributed SAR Systems and Missions

Alberto Moreira, Gerhard Krieger

SS19 – Multisensor multitarget tracking in surveillance applications

Paolo Braca, Ba-Ngu Vo

Multitarget tracking (MTT), throughout its over-50 years-long history, tackles the problem of estimating atime-varying number of moving objects and their kinematic states from sensor data such as radar, sonar,and cameras. Nowadays, MTT is a key element in various situation-aware systems including intelligence,surveillance, and reconnaissance (ISR), air traffic control, space and maritime domain awareness, computervision, remote sensing, autonomous vehicles and robotics. The MTT problem presents many technicalchallenges, such as the treatment of false alarms, missed detections, measurement origin uncertainty ordata association, object appearance and disappearance, as well as real-time operation requirements usingresource-limited devices, and the assimilation of heterogeneous data. Recent developments in MTTmethods, along with sensing and computing technologies, have opened up a variety of research directionsand application fields. The aim of this special session is to explore recent advances in the theory andimplementation of MTT for solving emerging challenges posed by real-world surveillance systems.

Poster Special Sessions

PSS1 – Resource management for cognitive radar systems

Junkun Yan, Wei Yi

Cognitive radar, which may either be monostatic or multistatic case, is a radar system that perceivesknowledge of its surrounding environment by online estimation and learning or from the preserved contextinformation. One of the significant applications of cognitive radar systems is to enhance the performance ofdifferent task objectives, such as the detection probability, positioning precision and tracking accuracythrough managing their limited system resources. Due to the varieties of the task requirements andenvironmental factors, it is still an open issue to obtain optimal scheduled schemes of system resources inpractical scenarios. This special session aims to present the most recent progresses in terms of techniquesand applications of resource aware management for cognitive radar systems.

PSS2 – Advanced radar waveform design strategies

Mohammad Alaee-Kerahroodi, Augusto Aubry

Waveform design and diversity is a recent paradigm that has been attracting a lot of research interest inradar and signal processing communities during the last decade. It refers to the radar waveform adaptationin several domains, such as spatial, temporal, spectral, and polarization, aimed at dynamically improvingthe radar performance for the particular scenario and tasks. This advanced and powerful feature is enabledby the new computing architectures, high-speed and off-the-shelf processors, arbitrary digital waveformgenerators, solid-state transmitters, modern phased array with multiple transmit and receive channels etc.,and provides unique capabilities to optimize radar detection, classification, identification, localization, andtracking performance over classical systems. In this context optimization theory plays a pivotal rule beingthe radar waveform synthesis obtained as the solution to a constrained optimization problem where theconstraints are dictated by both endogenous and exogenous information. Many problems still remainunsolved representing current challenges for radar scientists and in this special section some advancedwaveform design techniques based on innovative optimization tools as well as their comprehensiveperformance assessment are provided aimed at filling some gaps still present in the open literature.The main goal of this special session is to highlight the challenges in radar waveform design and describerecent methodologies to overcome them. To this end, a variety of recognized authors from the differentplaces in the world are invited to introduce new optimization methods and techniques to deal withchallenging radar waveform design involving practical constraints, such as, just list a few, constant-modulus, spectral constraints, waveform similarity, and finite or discrete-phase alphabet.

PSS3 – Multi-target tracking algorithms for radar network systems

Giorgio Battistelli, Suqi Li

Recently, motivated by their remarkable features, such as spatial, frequency and polarization diversities etc.,radar network systems have gained increasing attention from the radar community. As one of the key partsof radar signal processing, a fundamental issue is how to redesign multi-target tracking (MTT) algorithms soas to fit the new features of these emerging radar systems. This special session is aimed to feature recentworks on techniques and applications of MTT methods in radar network systems. The tackled problemsinclude joint self-localization and MTT with MIMO radar, multi-sensor fusion with asynchronous radarsystems, target tracking for over-the-horizon radar networks, etc.

PSS4 – Multisensor multitarget tracking in surveillance applications

Nicola Forti, Peter Willett

Multitarget tracking (MTT), throughout its over-50 years-long history, tackles the problem of estimating atime-varying number of moving objects and their kinematic states from sensor data such as radar, sonar,and cameras. Nowadays, MTT is a key element in various situation-aware systems including intelligence,surveillance, and reconnaissance (ISR), air traffic control, space and maritime domain awareness, computervision, remote sensing, autonomous vehicles and robotics. The MTT problem presents many technicalchallenges, such as the treatment of false alarms, missed detections, measurement origin uncertainty ordata association, object appearance and disappearance, as well as real-time operation requirements usingresource-limited devices, and the assimilation of heterogeneous data. Recent developments in MTTmethods, along with sensing and computing technologies, have opened up a variety of research directionsand application fields. The aim of this special session is to explore recent advances in the theory andimplementation of MTT for solving emerging challenges posed by real-world surveillance systems.

PSS5 – Radar & radar net for weather/climate monitoring and forecast

Stefano Turso, Frank Gekat

Recent technological advancements in the fields of microelectronics and processing hardware have madepossible breakthroughs to assemble commercially available chipsets at X-band comprising the entire radarfront-end (transmit/receive modules) and beamforming functions (AESA core controllers). Sustained by anumber of radar applications at X-band, the existence of these chipsets implies a significant cost reductionfor civilian AESA applications, finally supporting the feasibility of new micro-radar concepts for weathermonitoring.Especially for hybrid electronic and mechanical beam steering solutions, dual-polarized phased-arrayweather radars can provide definite advantages over mechanically steered long-range units (improvedevents detection and classification, reduced revisit time and operational cost).The aim of the session is to show how the decades-old vision of micro-radar networks for improved weathermonitoring (high spatial and temporal resolution, minimization of shielding effects, consistent sounding ofthe lower troposphere) can integrate well with legacy solutions and move from bold but earlyimplementations (e.g. the US CASA experimental network) to economically sustainable and competitivesolutions.