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RF/Microwave Front-End and Component Design: Emphasis on Air-Suspended Filters

Radar 2021: Next-Generation SAR Architectures and Integrated RF Technologies (National Security Campus)

Development of a new fully-board embedded air cavity technology called Suspended Integrated Stripline (SISL). Highlight of this technology was the design and implementation of a continuous 2-18 GHz bandpass filter with less than 1 dB of passband insertion loss and greater than 10 dB of return loss across the passband. SISL research is currently focused on expanding its implementation to allow for surface mountability allowing for the first-ever SMT capable package of an air suspended technology. Additional research  is the investigation of cavity embedded varactors for frequency agile filter design and frequency scaling of the technology to provide extremely low loss filtering solutions for 77 GHz automotive radar.

Air-Suspended Tunable Resonators for Observing Systems [ASTROS] (Office of Naval Research)

Modern-day digital-at-every-element radar systems are continuously demanding more flex­ibility while simultaneously satisfying challenging size, weight, and power constraints. Moreover, these demands are being placed on top of moving to higher frequencies without sacrificing any RF system-level performance. While there is an immense amount of on-going research at the system level, there is still a plethora of exciting component-level technical challenges.

The analog front-end filter remains a primary area of research as it is continuously being tasked with increased functionality and integration with ever-increasing demands on improved performance. For all-digital radar systems, the ideal front-end filter can be integrated directly behind every antenna element, have frequency and bandwidth tunability, sharp roll-off with large stopband attenuation to suppress near-band jammers, and achieve low pass-band insertion loss to maintain high-performance system-level demands. This is an exceedingly difficult challenge as these design parameters are commonly trade-offs in realizable filter designs.

This research effort is focusing on the development of a surface-mount, tunable, and air suspended filter solution to meet the demands of modern and next-generation systems. Air suspended technologies are well-known for their low-loss and excellent filtering characteristics; yet, have traditionally been limited to connectorized implementation methods. However, a fully-board integrated, and air suspended filter, would allow for tunable and surface mount implementations for the first-time. The outcome of this 3-year project will be a complete proof-of-concept and design methodology for a tunable, surface mount, air-suspended band-pass filter designs with measured results validating theory and simulations.

Electromagnetic Modeling and Simulation

Radar 2021: Next-Generation SAR Architectures and Integrated RF Technologies (National Security Campus)

Development of a vertical via transition circuit model for multi-layer printed circuit board stack-ups. Also developed the mathematics to calculate the parasitic inductances and capacitances. Circuit simulations and finite-element-method simulations show excellent agreement up to 20 GHz. Investigation of ground-defected structures in multi-layer stack-ups to implement bandstop filters for higher order mode suppression. Mathematical models have been developed and designs have been used to suppress the second mode in substrate integrated waveguide filter designs.

Synthetic Aperture Radar & All-Digital Phased Array Systems

Radar 2021: Next-Generation SAR Architectures and Integrated RF Technologies (National Security Campus)

Development of a Ku-band synthetic aperture radar with direct digital conversion using strictly COTs components. The MMG team is in charge of the entire system architecture including the RF front-end, digital back-end, FPGA, and navigation as well as the digital pipe-lining and back-projection signal processing. This system has gone through rigorous loop-back testing, range-Doppler measurements in a anechoic chamber and field test, and recently generated a SAR image. This system is currently undergoing a slight redesign that can be integrated onto a custom printed circuit board currently being design by the MMG radar team.

Miniaturized SAR Hardware for Airborne Applications (Sandia National Laboratories)

The MMG team has recently partnered with Sandia National Labs to develop a highly integrated Ku-Band SAR system. The goal is to implement the digital back-end with a SDR and integrate the RF front-end into a compact module based on the X-microwave LEGO design. This will all be integrated into a single module for airborne flight testing. If successful, a prototype time-multiplexed pulse-Doppler/FMCW system will be developed to demonstrate multi-architecture mode operation in complex maneuvering flight systems.

Fusion-Based State Estimation for Precise Position, Navigation, and Timing (PNT) and Distributed Coherent Radar (DCR) Networks

Fine Resolution Position Estimation Using Multi-IMU Fusion Techniques (Sandia National Laboratories)

The MMG team has recently submitted a pro-visionary patent on the idea of multi-IMU particle filter fusion for fine-resolution position estimation. The idea is to use the independent sampling of several IMUs and a fusion process to extract "truth" position for a moving platform. The novel up-sampled particle filter algorithm developed will allow for the system's position to be known on a pulse-by-pulse basis so phase realignment can accurately be done in SAR back-projection to create a highly-focused image. This technology will have profound implications in unlocking the frequency barrier of current mm- Wave SAR systems and will allow for a much smaller cost, size, weight, and power (C-SWaP) design that can allow for true UAV based  position, navigation, and timing (PNT) solutions.

Fusion-Based State Estimation for Localization and Synchronization of Distributed Radar Sensor Networks (Office of Naval Research)

Distributed radar systems are networks of radar sensors that are spatially separated from one another. They are superior in terms of system survivability as they do not have a single point of failure and provide many advantages in terms of performance, such as increasing target localization accuracy, mitigating the blind velocities caused by Doppler aliasing, providing three-dimensional velocity estimation, and improving the power gain and directivity of beamforming (BF) missions. Moreover, synthetic aperture radar (SAR) imaging modalities stand to improve by enabling quicker updating of scene images, providing multi-look angle measurements of a scene from multiple angles, and increasing the synthetic aperture size. The effort will develop solutions using current state-of-the-art fusion methodologies and novel estimation techniques to synchronize and localize moving radar sensors. Given the close relationship between the time, phase, and frequency synchronization and the estimation of relative distances between nodes, time-of-flight (TOF) measurements can be utilized to validate the accuracy of position estimates made by an IMU. Because the position estimates are assumed to have some error, determining an optimal position estimate, TOF between all nodes, and the phase, time, and frequency offsets between all the network sensors is well-suited for a state estimator. Thus, this proposal will investigate the fundamental mathematics, algorithm development, and system-of-systems architecture needed for distributed, mobile radar system synchronization, localization, and navigation.

Airborne Remote Sensing

CAREER: UAV-Based Radar Suite for Bulk-Snow Characterization and Risk Management (National Science Foundation)

Snow is a crucial component of the earth’s climate system due to its extensive surface coverage and the critical role it plays as part of the cryosphere. Seasonal snowpack runoff profoundly influences the distribution of meltwater in watersheds, which constitutes roughly one-sixth of the freshwater needs globally, and the majority of water resources in mountainous regions. Moreover, snow acts as a thermal blanket between the atmosphere and underlying ice, that leads to impacts on freshwater lake ecosystems and has socioeconomic implications given its critical role in transportation (e.g., ice-road duration) and ice-jam flooding. Therefore, studying this hydrological cycle is crucial, especially with model projections suggesting a low-to-no snow future due to persistent emissions of greenhouse gases and globally rising temperatures. However, there are large uncertainties in capturing the fine details of this cycle and the hydrological consequences. This is partly because there are not enough measurements of distributed bulk-snow characteristics in important areas such as inaccessible mountainous regions. These observational gaps limit our ability to accurately develop robust modeling and forecasting techniques for improved risk management and hazard mitigation proposes. This CAREER project addresses this data need by equipping a small unmanned aerial vehicle (UAV) with an advanced radar suite to produce fine spatial and temporal resolution measurements of snowpack properties such as snow depth, snow water equivalent, relative density, and liquid water content. The integrated research and education project also involves preparing, training, and exciting the next generation of remote sensing engineers to engage in multi-disciplinary careers. Beyond providing research opportunities to undergraduate and graduate students, this project will integrate research concepts into the teaching and laboratory curriculum, providing academic and experiential learning opportunities.

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