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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Respiration Signal Pattern Analysis for Doppler Radar Sensor with Passive Node and Its Application in Occupancy Sensing of a Stationary Subject

Doppler radar node occupancy sensors are promising for applications in smart buildings due to their simple circuits and price advantage compared to quadrature radar sensors. However, single-channel sensitivity limitations may result in low sensitivity and misinterpreted motion rates if the detected subject is at or close to “null” points. We designed and tested a novel method to eliminate such limits, demonstrating that passive nodes can be used to detect a sedentary person regardless of position. This method is based on characteristics of chest motion due to respiration, found via both simulations and experiments based on a sinusoidal model and a more realistic model of cardiorespiratory motion. In addition, respiratory rate variability is considered to distinguish a true human presence from a mechanical target. Sensor node data were collected simultaneously with an infrared camera system, which provided a respiration signal reference, to test the algorithm with 19 human subjects and a mechanical target. The results indicate that a human presence was detected with 100% accuracy and successfully differentiated from a mechanical target in a controlled environment. The developed method can greatly improve the occupancy detection accuracy of single-channel radar-based occupancy sensors and facilitate their adoption in smart building applications.

Song, Chenyan↗
DOE OSTI2020

Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Modeling Adaptive Cruise Control (ACC) vehicles enables the understanding of the impact of these vehicles on traffic flow. In this work, two online methods are used to provide real time system identification of ACC enabled vehicles. The first technique is a recursive least squares (RLS) approach, while the second method solves a nonlinear joint state and parameter estimation problem via particle filtering (PF). We provide a parameter identifiability analysis for both methods to analytically show that the model parameters are not identifiable using equilibrium driving. The accuracy and computational runtime of the online methods are compared to a commonly used offline simulation-based optimization (i.e., batch optimization) approach. The methods are tested on synthetic data as well as on empirical data collected directly from a 2019 model year ACC vehicle using data from sensors that are part of the stock ACC system. The online methods are scalable and provide comparable accuracy to the batch method. RLS runs in real time and is two orders of magnitude faster than the batch method for modest sized (e.g., 15 min) datasets. The particle filter also runs in real- time, and is also suitable in streaming applications in which the datasets can grow arbitrarily large.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1983

The development of a power spectral density processor for C and L band airborne radar scatterometer sensor systems

A real-time signal processor was developed for the NASA/JSC L-and C-band airborne radar scatterometer sensor systems. The purpose of the effort was to reduce ground data processing costs. Conversion of two quadrature channels of data (like and cross polarized) was made to obtain Power Spectral Density (PSD) values. A chirp-z transform (CZT) approach was used to filter the Doppler return signal and improved high frequency and angular resolution was realized. The processors have been tested with record signals and excellent results were obtained. CZT filtering can be readily applied to scatterometers operating at other wavelengths by altering the sample frequency. The design of the hardware and software and the results of the performance tests are described in detail.

Harrison, D. A., III↗
NASA NTRS1982

Working group organizational meeting

Scene radiation and atmospheric effects, mathematical pattern recognition and image analysis, information evaluation and utilization, and electromagnetic measurements and signal handling are considered. Research issues in sensors and signals, including radar (SAR) reflectometry, SAR processing speed, registration, including overlay of SAR and optical imagery, entire system radiance calibration, and lack of requirements for both sensors and systems, etc. were discussed.

Source record↗
NASA NTRS2003

Kinematic analysis of conically scanned environmental properties

A method for determining the velocity of features such as wind. The method preferably includes producing sensor signals and projecting the sensor signals sequentially along lines lying on the surface of a cone. The sensor signals may be in the form of lidar, radar or sonar for example. As the sensor signals are transmitted, the signals contact objects and are backscattered. The backscattered sensor signals are received to determine the location of objects as they pass through the transmission path. The speed and direction the object is moving may be calculated using the backscattered data. The data may be plotted in a two dimensional array with a scan angle on one axis and a scan time on the other axis. The prominent curves that appear in the plot may be analyzed to determine the speed and direction the object is traveling.

Wilkerson, Thomas D.↗
NASA NTRS1985

Massively parallel processor

A brief description is given of the Massively Parallel Processor (MPP). Major applications of the MPP are in the area of image processing (where the operands are often very small integers) from very high spatial resolution passive image sensors, signal processing of radar data, and numerical modeling simulations of climate. The system can be programmed in assembly language or a high level language. Information on background, status, architecture, programming, hardware reliability, applications, and the MPP's development as a national resource for parallel algorithm research are presented in outline form.

Source record↗
NASA NTRS2022

TruePAL – An AI Assistant for First Responder Safety

This paper presents the development of an AI assistant, Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL), to provide real-time warning of risks of potential crashes to the first responders. The TruePAL system employs an AI and deep learning technology for saving first responders and roadside crews lives in and around active traffic. A deep neural network (DNN) and a Non-Axiomatic Reasoning System (NARS) are implemented as an AI system. A mobile app with AI interface is developed to perform verbal communication with the first responders. The TruePAL team has developed an explainable AI approach by opening up the DNN blackbox to extract the activation filters of various features and parts of the targeted objects. The combination of DNN and NARS makes the TruePAL system explainable to the users. TruePAL ingests on-board cameras, radar, and other sensor signals, analyzes the environment and traffic patterns to generate timely warning to drivers and roadside crews to avoid crashes. The TruePAL team, in collaboration with the Miami/Dade Police Dept., has designed five use cases and multiple sub-scenarios in a CARLA driving simulator to test the capability of TruePAL in timely warning to the first responder drivers in potential crash scenarios. We have successfully demonstrated its capability of timely warning in over a dozen scenarios based on the use cases. The preliminary test simulation results show that TruePAL could provide the drivers and crew members advanced warning before a crash occurs.

Chow, Edward↗
NASA NTRS2013

High-Speed Data Recorder for Space, Geodesy, and Other High-Speed Recording Applications

A high-speed data recorder and replay equipment has been developed for reliable high-data-rate recording to disk media. It solves problems with slow or faulty disks, multiple disk insertions, high-altitude operation, reliable performance using COTS hardware, and long-term maintenance and upgrade path challenges. The current generation data recor - ders used within the VLBI community are aging, special-purpose machines that are both slow (do not meet today's requirements) and are very expensive to maintain and operate. Furthermore, they are not easily upgraded to take advantage of commercial technology development, and are not scalable to multiple 10s of Gbit/s data rates required by new applications. The innovation provides a softwaredefined, high-speed data recorder that is scalable with technology advances in the commercial space. It maximally utilizes current technologies without being locked to a particular hardware platform. The innovation also provides a cost-effective way of streaming large amounts of data from sensors to disk, enabling many applications to store raw sensor data and perform post and signal processing offline. This recording system will be applicable to many applications needing realworld, high-speed data collection, including electronic warfare, softwaredefined radar, signal history storage of multispectral sensors, development of autonomous vehicles, and more.

Taveniku, Mikael↗
NASA NTRS2017

Detection, Localization, and Tracking of Unauthorized UAS and Jammers

Small unmanned aircraft systems (UASs) are expected to take major roles in future smart cities, for example, by delivering goods and merchandise, potentially serving as mobile hot spots for broadband wireless access, and maintaining surveillance and security. Although they can be used for the betterment of the society, they can also be used by malicious entities to conduct physical and cyber attacks to infrastructure, private/public property, and people. Even for legitimate use-cases of small UASs, air traffic management (ATM) for UASs becomes of critical importance for maintaining safe and collusion-free operation. Therefore, various ways to detect, track, and interdict potentially unauthorized drones carries critical importance for surveillance and ATM applications. In this paper, we will review techniques that rely on ambient radio frequency signals (emitted from UASs), radars, acoustic sensors, and computer vision techniques for detection of malicious UASs. We will present some early experimental and simulation results on radar-based range estimation of UASs, and receding horizon tracking of UASs. Subsequently, we will overview common techniques that are considered for interdiction of UASs.

surveillance↗
NASA NTRS2009

Testing of a Microwave Blade Tip Clearance Sensor at the NASA Glenn Research Center

The development of new active tip clearance control and structural health monitoring schemes in turbine engines and other types of rotating machinery requires sensors that are highly accurate and can operate in a high temperature environment. The use of a microwave sensor to acquire blade tip clearance and tip timing measurements is being explored at the NASA Glenn Research Center. The microwave blade tip clearance sensor works on principles that are very similar to a short range radar system. The sensor sends a continuous microwave signal towards a target and measures the reflected signal. The phase difference of the reflected signal is directly proportional to the distance between the sensor and the target being measured. This type of sensor is beneficial in that it has the ability to operate at extremely high temperatures and is unaffected by contaminants that may be present in turbine engines. The use of microwave sensors for this application is a new concept. Techniques on calibrating the sensors along with installation effects are not well quantified as they are for other sensor technologies. Developing calibration techniques and evaluating installation effects are essential in using these sensors to make tip clearance and tip timing measurements. As a means of better understanding these issues, the microwave sensors were used on a bench top calibration rig, a large axial vane fan, and a turbofan. Background on the microwave tip clearance sensor, an overview of their calibration, and the results from their use on the axial vane fan and the turbofan will be presented in this paper.

Woike, Mark R.↗
NASA NTRS2009

Testing of a Microwave Blade Tip Clearance Sensor at the NASA Glenn Research Center

The development of new active tip clearance control and structural health monitoring schemes in turbine engines and other types of rotating machinery requires sensors that are highly accurate and can operate in a high-temperature environment. The use of a microwave sensor to acquire blade tip clearance and tip timing measurements is being explored at the NASA Glenn Research Center. The microwave blade tip clearance sensor works on principles that are very similar to a short-range radar system. The sensor sends a continuous microwave signal towards a target and measures the reflected signal. The phase difference of the reflected signal is directly proportional to the distance between the sensor and the target being measured. This type of sensor is beneficial in that it has the ability to operate at extremely high temperatures and is unaffected by contaminants that may be present in turbine engines. The use of microwave sensors for this application is a new concept. Techniques on calibrating the sensors along with installation effects are not well quantified as they are for other sensor technologies. Developing calibration techniques and evaluating installation effects are essential in using these sensors to make tip clearance and tip timing measurements. As a means of better understanding these issues, the microwave sensors were used on a benchtop calibration rig, a large axial vane fan, and a turbofan. Background on the microwave tip clearance sensor, an overview of their calibration, and the results from their use on the axial vane fan and the turbofan will be presented in this paper.

Woike, Mark R.↗
DOE OSTI2023

Sensor Fusion-Based Vehicle Detection and Tracking Using a Single Camera and Radar at a Traffic Intersection

Recent advancements in sensor technologies, in conjunction with signal processing and machine learning, have enabled real-time traffic control systems to adapt to varying traffic conditions. This paper introduces a new sensor fusion approach that combines data from a single camera and radar to achieve cost-effective and efficient vehicle detection and tracking. Initially, vehicles are independently detected and classified using the camera and radar. Then, the constant-velocity model within a Kalman filter is employed to predict vehicle locations, while the Hungarian algorithm is used to associate these predictions with sensor measurements. Finally, vehicle tracking is accomplished by merging kinematic information from predictions and measurements through the Kalman filter. A case study conducted at an intersection demonstrates the effectiveness of the proposed sensor fusion method for traffic detection and tracking, including performance comparisons with individual sensors.

47 OTHER INSTRUMENTATION↗
NASA NTRS2018

(GO)2-SIM: a GCM-Oriented Ground-Observation Forward-Simulator Framework for Objective Evaluation of Cloud and Precipitation Phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO)2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise.Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40%. So, while hydrometeor-phase maps determined in forward space are very different from model "reality" they capture the information sensors can provide and thereby enable objective model evaluation.

Lamer, K.↗
NASA NTRS2010

Solid-State, High Energy 2-Micron Laser Development for Space-Based Remote Sensing

Lidar (light detection and ranging) remote sensing enjoys the advantages of excellent vertical and horizontal resolution; pointing capability; a signal source independent from natural light; and control and knowledge of transmitted wavelength, pulse shape, and polarization and received polarization. Lidar in space is an emerging technology now being developing to fit applications where passive sensors cannot meet current measurement requirements. Technical requirements for space lidar are more demanding than for ground-based or airborne systems. Perhaps the most distinguishing characteristics of space lidars are the environmental requirements. Space lidar systems must be specially designed to survive the mechanical vibration loads of launch and operate in the vacuum of space where exposure to ionizing radiation limits the electronic components available. Finally, space lidars must be designed to be highly reliable because they must operate without the need for repair or adjustment. Lifetime requirements tend to be important drivers of the overall system design. The maturity of the required technologies is a key to the development of any space lidar system. NASA entered a new era in the 1990 s with the approval of several space-based remote sensing missions employing laser radar (lidar) techniques. Following the steps of passive remote sensing and then active radar remote sensing, lidar sensors were a logical next step, providing independence from natural light sources, and better spatial resolution and smaller sensor size than radar sensors. The shorter electromagnetic wavelengths of laser light also allowed signal reflectance from air molecules and aerosol particles. The smaller receiver apertures allowed the concept of scanning the sensor field of view. However, technical problems with several space-based lidar missions during that decade led to concern at NASA about the risk of lidar missions. An external panel was convened to make recommendations to NASA. Their report in 2000 strongly advocated that NASA maintain in-house laser and lidar capability, and that NASA should work to lower the technology risk for all future lidar missions. A multi-Center NASA team formulated an integrated NASA strategy to provide the technology and maturity of systems necessary to make Lidar/Laser systems viable for space-based study and monitoring of the Earth's atmosphere. In 2002 the NASA Earth Science Enterprise (ESE) and Office of Aerospace Technology (OAT) created the Laser Risk Reduction Program (LRRP) and directed NASA Langley Research Center (LaRC) and Goddard Space Flight Center to carry out synergistic and complementary research towards solid-state lasers/lidars developments for space-based remote sensing applications.

Singh, Upendra N.↗
DOE OSTI2023

Optimal Traffic Signal Control Using Priority Metric Based on Real-Time Measured Traffic Information

Optimizing traffic control systems at traffic intersections can reduce network-wide fuel consumption as well as improve traffic flow. While traffic signals have conventionally been controlled based on predetermined schedules, various adaptive control systems have been developed recently using advanced sensors such as cameras, radars, and LiDARs. By utilizing rich traffic information enabled by the advanced sensors, more efficient or optimal traffic signal control is possible in response to varying traffic conditions. This paper proposes an optimal traffic signal control method to minimize network-wide fuel consumption utilizing real-time traffic information provided by advanced sensors. This new method employs a priority metric calculated by a weighted sum of various factors, including the total number of vehicles, total vehicle speed, vehicle waiting time, and road preference. Genetic Algorithm (GA) is used as a global optimization method to determine the optimal weights in the priority metric. In order to evaluate the effectiveness of the proposed method, a traffic simulation model is developed in a high-fidelity traffic simulation environment called SUMO, based on a real-world traffic network. The traffic flow within this model is simulated using actual measured traffic data from the traffic network, enabling a comprehensive assessment of the novel optimal traffic signal control method in realistic conditions. The simulation results show that the proposed priority metric-based real-time traffic signal control algorithm can significantly reduce network-wide fuel consumption compared to the conventional fixed-time control and coordinated actuated control methods that are currently used in the modeled network. Additionally, incorporating truck priority in the priority metric leads to further improvements in fuel consumption reduction.

47 OTHER INSTRUMENTATION↗
NASA NTRS1980

Considerations on real-time processing of spaceborne synthetic aperture radar data

This paper comprises a description of Synthetic Aperture Radar (SAR) processing approaches and a discussion on the processor complexity measures. The objective of the paper is to provide basic system knowledge on the design of a real-time signal processor for spaceborne synthetic aperture radar. A review of SAR sensor performance capability and general electronic processing approaches will be given first. The discussion of SAR processor complexity is divided into two areas: the arithmetic complexity and the control complexity. A generalized treatment of these subjects is provided. The results could be readily extended to special cases.

Wu, C.↗