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Graded index dielectric superstrate for phased array scan compensation

July 5, 2020
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Conference Paper
Author:
Roberto G. Rojas-Teran
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Published in:
2020 IEEE Intl. Symp. on Antennas and Propagation and North American Radio Science Meeting, 5-10 July 2020.
Topic:
RF systems
R&D area:
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Summary

This paper presents the use of additively manufactured graded index materials to improve the scan impedance variation of phased arrays. Solvent-based extrusion permits the programmatically controlled printing of chosen material properties with relative permittivity ranging from 2 to 24.5. This low-loss material shows promise for improvement of scan impedance variation for high scan angles in a smaller footprint than discrete layers.
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Summary

This paper presents the use of additively manufactured graded index materials to improve the scan impedance variation of phased arrays. Solvent-based extrusion permits the programmatically controlled printing of chosen material properties with relative permittivity ranging from 2 to 24.5. This low-loss material shows promise for improvement of scan impedance variation...

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Graded index dielectric superstrate for phased array scan compensation

Adjoint analysis of guidance systems for time-series inputs using Fourier analysis

July 1, 2020
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Journal Article
Author:
Joel Alpert
Published in:
J. Guid., Control, Dyn., Vol. 43, No. 7, July 2020.
Topic:
missile defense
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Summary

The adjoint technique is a proven technique for analysis of linear time-varying systems and is widely used in the missile design community. It is a very efficient technique that can solve for both deterministic and stochastic disturbances and can develop a miss distance budget in a single computer solution of the differential equations without use of time-consuming Monte Carlo simulations. The adjoint technique is very valuable in both preliminary and more advanced missile design stages and is based upon the mathematical adjoint of the system dynamics matrix of the homing loop. Zarchan [1,2] describes extensive use of the technique for a variety of disturbances for homing missiles, and this author has developed its use for command guided missiles [3]. For adjoint analysis, the usual method of modeling maneuver disturbances to a missile guidance system starts by modeling the maneuver in the forward-time system as a delta function input into a transfer function with the same second-order statistics as the maneuver, and its output is input into the guidance system; then the system is converted into its adjoint system [1]. Bucco and Weiss [4] show that a set of nonstandard time-varying inputs cannot be treated in the normal fashion [2,5,6], and they present a new technique that enables these nonstandard inputs to be analyzed using adjoint analysis. This paper was inspired by and extends the results of the paper by Bucco and Weiss [4]. This paper shows that the use of the complex digital Fourier amplitude spectrums of both the maneuver and the adjoint impulse response at the maneuver point allows adjoint analysis to address another type of nonstandard input, namely, an arbitrary time-series inputs such as specific target maneuvers that are not representable by an impulse input into a transfer function; heretofore, these time-series inputs have not been treatable with adjoint analysis. Additionally, if there are several sets of arbitrary time series of target maneuvers, each with an associated probability of occurrence, the root-mean-square (rms) value of the set of probabilistic maneuvers can be calculated, another significant new capability introduced in this paper.
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Summary

The adjoint technique is a proven technique for analysis of linear time-varying systems and is widely used in the missile design community. It is a very efficient technique that can solve for both deterministic and stochastic disturbances and can develop a miss distance budget in a single computer solution of...

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Adjoint analysis of guidance systems for time-series inputs using Fourier analysis

A hands-on middle-school robotics software program at MIT

March 28, 2020
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Conference Paper
Author:
Sabina W. Chen
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Published in:
IEEE Integrated STEM Education Conf., 28 March 2020.
Topic:
robotics
R&D area:
R&D group:

Summary

Robotics competitions at the high school level attract a large number of students across the world. However, there is little emphasis on leveraging robotics to get middle school students excited about pursuing STEM education. In this paper, we describe a new program that targets middle school students in a local, four-week setting at the Massachusetts Institute of Technology (MIT). It aims to excite students by teaching the very basics of computer vision and robotics. The students program mini car-like robots, equipped with state-of-the-art computers, to navigate autonomously in a mock race track. We describe the hardware and software infrastructure that enables the program, the details of our curriculum, and the results of a short assessment. In addition, we describe four short programs, as well as a session where we teach high school teachers how to teach similar courses at their schools to their own students. The self-assessment indicates that the students feel more confident in programming and robotics after leaving the program, which we hope will enable them to pursue STEM education and robotics initiatives at school.
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Summary

Robotics competitions at the high school level attract a large number of students across the world. However, there is little emphasis on leveraging robotics to get middle school students excited about pursuing STEM education. In this paper, we describe a new program that targets middle school students in a local...

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A hands-on middle-school robotics software program at MIT

Safe predictors for enforcing input-output specifications [e-print]

January 29, 2020
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Journal Article
Author:
Stephen Mell
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Published in:
https://arxiv.org/abs/2001.11062
Topic:
machine learning
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Summary

We present an approach for designing correct-by-construction neural networks (and other machine learning models) that are guaranteed to be consistent with a collection of input-output specifications before, during, and after algorithm training. Our method involves designing a constrained predictor for each set of compatible constraints, and combining them safely via a convex combination of their predictions. We demonstrate our approach on synthetic datasets and an aircraft collision avoidance problem.
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Summary

We present an approach for designing correct-by-construction neural networks (and other machine learning models) that are guaranteed to be consistent with a collection of input-output specifications before, during, and after algorithm training. Our method involves designing a constrained predictor for each set of compatible constraints, and combining them safely via...

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Safe predictors for enforcing input-output specifications [e-print]

AI enabling technologies: a survey

May 8, 2019
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Journal Article
Author:
Vijay N. Gadepally
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Published in:
https://arxiv.org/abs/1905.03592
Topic:
artificial intelligence
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Summary

Artificial Intelligence (AI) has the opportunity to revolutionize the way the United States Department of Defense (DoD) and Intelligence Community (IC) address the challenges of evolving threats, data deluge, and rapid courses of action. Developing an end-to-end artificial intelligence system involves parallel development of different pieces that must work together in order to provide capabilities that can be used by decision makers, warfighters and analysts. These pieces include data collection, data conditioning, algorithms, computing, robust artificial intelligence, and human-machine teaming. While much of the popular press today surrounds advances in algorithms and computing, most modern AI systems leverage advances across numerous different fields. Further, while certain components may not be as visible to end-users as others, our experience has shown that each of these interrelated components play a major role in the success or failure of an AI system. This article is meant to highlight many of these technologies that are involved in an end-to-end AI system. The goal of this article is to provide readers with an overview of terminology, technical details and recent highlights from academia, industry and government. Where possible, we indicate relevant resources that can be used for further reading and understanding.
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Summary

Artificial Intelligence (AI) has the opportunity to revolutionize the way the United States Department of Defense (DoD) and Intelligence Community (IC) address the challenges of evolving threats, data deluge, and rapid courses of action. Developing an end-to-end artificial intelligence system involves parallel development of different pieces that must work together...

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AI enabling technologies: a survey

CW radar operation in the focused near-field

April 14, 2019
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Conference Paper
Author:
Kristan A. Tuttle
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Published in:
2019 Intl. Applied Computational Electromagnetics Society Symp., ACES, 14-19 April 2019.
Topic:
antennas
R&D area:
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Summary

In this paper we will show by computer simulation and by measurements that the horn antennas of a bi-static radar operating in the near-field have a distinct maximum at a non-zero range. By focusing the antennas on this hot spot a low-powered, continuous-wave Ku-band radar could detect flying mosquitoes at very short range.
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Summary

In this paper we will show by computer simulation and by measurements that the horn antennas of a bi-static radar operating in the near-field have a distinct maximum at a non-zero range. By focusing the antennas on this hot spot a low-powered, continuous-wave Ku-band radar could detect flying mosquitoes at...

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CW radar operation in the focused near-field

Simulation approach to sensor placement using Unity3D

September 25, 2018
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Conference Paper
Author:
Kimberlee Chestnut Chang
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Published in:
IEEE High Performance Extreme Computing Conf., HPEC, 25-27 September 2018.
Topic:
high performance computing
R&D area:
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Summary

3D game simulation engines have demonstrated utility in the areas of training, scientific analysis, and knowledge solicitation. This paper will make the case for the use of 3D game simulation engines in the field of sensor placement optimization. Our study used a series of parallel simulations in the Unity3D simulation framework to answer the questions: how many sensors of various modalities are required and where they should be placed to meet a desired threat detection threshold? The result is a framework that not only answers this sensor placement question, but can be easily expanded to differing optimization criteria as well as answer how a particular configuration responds to differing crowd flows or informed/non-informed adversaries. Additionally, we demonstrate the scalability of this framework by running parallel instances on a supercomputing grid and illustrate the processing speed gained.
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Summary

3D game simulation engines have demonstrated utility in the areas of training, scientific analysis, and knowledge solicitation. This paper will make the case for the use of 3D game simulation engines in the field of sensor placement optimization. Our study used a series of parallel simulations in the Unity3D simulation...

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Simulation approach to sensor placement using Unity3D

Human-machine collaborative optimization via apprenticeship scheduling

September 1, 2018
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Journal Article
Author:
Matthew C. Gombolay
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Published in:
J. Artif. Intell. Res., Vol. 63, 2018, pp. 1-49.
Topic:
artificial intelligence
R&D area:
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Summary

Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale beyond the "single-expert, single-trainee" apprenticeship model. However, human domain experts often have difficulty describing their decision-making processes. We propose a new approach for capturing this decision-making process through counterfactual reasoning in pairwise comparisons. Our approach is model-free and does not require iterating through the state space. We demonstrate that this approach accurately learns multifaceted heuristics on a synthetic and real world data sets. We also demonstrate that policies learned from human scheduling demonstration via apprenticeship learning can substantially improve the efficiency of schedule optimization. We employ this human-machine collaborative optimization technique on a variant of the weapon-to-target assignment problem. We demonstrate that this technique generates optimal solutions up to 9.5 times faster than a state-of-the-art optimization algorithm.
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Summary

Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale...

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Human-machine collaborative optimization via apprenticeship scheduling

Modeling and validation of a mm-wave shaped dielectric lens antenna

July 29, 2018
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Conference Paper
Author:
David C. Mooradd
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Published in:
2018 Int. Applied Computational Electromagnetics Society Symp., ACES, 29 July - 1 August 2018.
Topic:
antennas
R&D area:
R&D group:

Summary

The modeling and validation of a 33 GHz shaped dielectric antenna design is investigated. The electromagnetic modeling was performed in both WIPL-D and FEKO, and was used to validate the antenna design prior to fabrication of the lens. It is shown that both WIPL-D and FEKO yield similarly accurate results as compared to measured far-field gain radiation patterns.
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Summary

The modeling and validation of a 33 GHz shaped dielectric antenna design is investigated. The electromagnetic modeling was performed in both WIPL-D and FEKO, and was used to validate the antenna design prior to fabrication of the lens. It is shown that both WIPL-D and FEKO yield similarly accurate results...

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Modeling and validation of a mm-wave shaped dielectric lens antenna

Peregrine: 3-D network localization and navigation

November 8, 2017
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Conference Paper
Author:
Bryan A. Teague
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Published in:
IEEE 9th Latin-American Conf. on Communications, LATINCOM, 8-10 November 2017.
Topic:
algorithms
R&D area:
R&D group:

Summary

Location-aware devices will create new services and applications in emerging fields such as autonomous driving, smart cities, and the Internet of Things. Many existing localization systems rely on anchors such as satellites at known positions which broadcast radio signals. However, such signals may be blocked by obstacles, corrupted by multipath propagation, or provide insufficient localization accuracy. Therefore, ubiquitous localization remains an extremely challenging problem. This paper introduces Peregrine, a 3-D cooperative network localization and navigation (NLN) system. Peregrine nodes are low-cost business-card-sized devices, consisting of a microprocessor, a commercially available ultra-wideband (UWB) radio module, and a small battery. Recently developed distributed algorithms are used in Peregrine to solve the highly interrelated problems of node inference and node activation in real-time, enabling resource efficiency, scalability, and accuracy for NLN. Node inference – based on the recently introduced sigma point belief propagation (SPBP) algorithm – enables spatiotemporal cooperation in realtime and estimates the nodes' positions accurately from UWB distance measurements. A distributed node activation algorithm controls channel access to improve the efficiency and reduce the localization error of the network. Contributions of each algorithmic component to overall system performance are validated through indoor localization experiments. Our results show that Peregrine achieves decimeter-level 3-D position accuracy in a challenging propagation environment.
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Summary

Location-aware devices will create new services and applications in emerging fields such as autonomous driving, smart cities, and the Internet of Things. Many existing localization systems rely on anchors such as satellites at known positions which broadcast radio signals. However, such signals may be blocked by obstacles, corrupted by multipath...

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Peregrine: 3-D network localization and navigation
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