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NASA NTRS2023

National Campaign Development Test Executive Summary

NASA’s vision for Advanced Air Mobility (AAM) is to provide safe, sustainable, accessible, and affordable aviation for transformational local and intraregional missions and includes the transportation of passengers and cargo as well as aerial work missions, such as infrastructure inspection or search and rescue operations. NASA’s technical expertise, intergovernmental relationships, and high level of public trust will help this technology come to market concurrent with infrastructure readiness, public acceptance, and constructive regulation. By advising and integrating disparate AAM efforts across the country and working collaboratively with the FAA, the National Campaign (NC) objective is to motivate industry progress and support the development of policy, regulatory, and technical standards in a manner that best ensures public safety and benefit to the American people. NC began with the Dry Run and Developmental Test (NC-DT), which served as a pathfinder for collaboration and direct involvement with industry partners in integrated simulation exercises and flight tests. NC-DT culminated with an acoustics-gathering flight test in September 2021 with industry partner Joby’s prototype S4 2.0 air vehicle, which delivered the first foundational baseline of noise levels present in Electric Vertical Takeoff and Landing (eVTOL) vehicles. Through the DT phase, the NC team built and tested the airspace and range infrastructure while assessing the readiness level of industry partners leading up to future NC events. The purpose of this paper is to provide an overview of NC-DT.

National Campaign↗

NASA NTRS2015

Development and Overview of CPAS Sasquatch Airdrop Landing Location Predictor Software

The Capsule Parachute Assembly System (CPAS) is the parachute system for NASA's Orion spacecraft. CPAS is currently in the Engineering Development Unit (EDU) phase of testing. The test program consists of numerous drop tests, wherein a test article rigged with parachutes is extracted from an aircraft. During such tests, range safety is paramount, as is the recoverability of the parachutes and test article. It is crucial to establish a release point from the aircraft that will ensure that the article and all items released from it during flight will land in a designated safe area. The Sasquatch footprint tool was developed to determine this safe release point and to predict the probable landing locations (footprints) of the payload and all released objects. In 2012, a new version of Sasquatch, called Sasquatch Polygons, was developed that significantly upgraded the capabilities of the footprint tool. Key improvements were an increase in the accuracy of the predictions, and the addition of an interface with the Debris Tool (DT), an in-flight debris avoidance tool for use on the test observation helicopter. Additional enhancements include improved data presentation for communication with test personnel and a streamlined code structure. This paper discusses the development, validation, and performance of Sasquatch Polygons, as well as its differences from the original Sasquatch footprint tool.

Bledsoe, Kristin J.↗

NASA NTRS2016

Combing Visible and Infrared Spectral Tests for Dust Identification

The MODIS Dark Target aerosol algorithm over Ocean (DT-O) uses spectral reflectance in the visible, near-IR and SWIR wavelengths to determine aerosol optical depth (AOD) and Angstrom Exponent (AE). Even though DT-O does have "dust-like" models to choose from, dust is not identified a priori before inversion. The "dust-like" models are not true "dust models" as they are spherical and do not have enough absorption at short wavelengths, so retrieved AOD and AE for dusty regions tends to be biased. The inference of "dust" is based on postprocessing criteria for AOD and AE by users. Dust aerosol has known spectral signatures in the near-UV (Deep blue), visible, and thermal infrared (TIR) wavelength regions. Multiple dust detection algorithms have been developed over the years with varying detection capabilities. Here, we test a few of these dust detection algorithms, to determine whether they can be useful to help inform the choices made by the DT-O algorithm. We evaluate the following methods: The multichannel imager (MCI) algorithm uses spectral threshold tests in (0.47, 0.64, 0.86, 1.38, 2.26, 3.9, 11.0, 12.0 micrometer) channels and spatial uniformity test [Zhao et al., 2010]. The NOAA dust aerosol index (DAI) uses spectral contrast in the blue channels (412nm and 440nm) [Ciren and Kundragunta, 2014]. The MCI is already included as tests within the "Wisconsin" (MOD35) Cloud mask algorithm.

aerosol optical depth↗

NASA NTRS2021

First retrieval of AOD at fine-resolution over shallow and turbid coastal waters from MODIS

The widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Dark-Target (DT) aerosol product fails to accurately retrieve Aerosol Optical Depth (AOD) over shallow and turbid Coastal Waters (CWs). To fill in gaps, and to improve land to ocean AOD continuity, we developed a coastal water retrieval algorithm at a spatial resolution of 1 km (CW-1km). CW-1km relies on observed top-of-atmosphere reflectance at 2.1 μm (ρ2.1), both to derive AOD and to perform a spatial variation test that enhances the existing DT masks for clouds and land. We show that the CW-1km improves spatial continuity of AOD between land, coast, and open ocean, while also increasing AOD product availability by 47.0%. Comparing with 15 years of marine aerosol network measurements, CW-1km AODs are validated to have a normalized mean bias of 1.0%, which is much smaller than 17.6% for the original DT product.

MODIS AOD↗

NASA NTRS2017

Optical Testing Using Portable Laser Coordinate Measuring Instruments

High precision, portable coordinate measuring instruments (CMI) such as laser radars (LR) and laser trackers (LT) have been used for optical system alignment and integration. The LRs ability to perform a non-contact scan of surfaces was previously utilized to characterize large spherical and aspheric mirrors. In this paper, we explore the use of a CMI as an accurate, fast, robust, and non-contact tool for prescription characterization of powered optical surfaces. Using Nikons MV-224350 LR and Leicas Absolute Tracker AT401402 instruments, proof of concept measurements were performed to characterize a variety of optical components by measuring the actual and apparent, or equivalently the direct and through (DT), coordinates of calibrated metrology targets. Custom macros in metrology software and other data reduction code were developed to compute surface-ray intercepts and surface slopes from the DT shots. The calculated data is fit to an aspheric surface formula to obtain the optimum prescription. The results were compared to the nominal parameters and were crosschecked using LR scans or other approaches. We discuss potential applications across the fields of optical component fabrication and system alignment and testing.

Khreishi, M.↗

NASA NTRS2020

Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark‐Target Algorithm: 1. Dust Detection

To prepare for implementation of a new aerosol retrieval specifically designed for dust aerosol over ocean in the operational Dark-Target (DT) algorithms for the Moderate-resolution Imaging Spectrometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensors, we focus on the challenge of detecting dust. We first survey the literature on existing dust detection algorithms and then develop an innovative algorithm that combines near-UV (deep blue), visible, and thermal infrared (TIR) wavelength spectral tests. The new detection algorithm is applied to Terra and Aqua MODIS granules and compared with other dust detection possibilities from existing MODIS products. Quantitative evaluation of the new dust detection algorithm is conducted using both a collocated AERONET-MODIS data set and collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-MODIS data set. From comparison with both AERONET and CALIOP measurements, we estimate the new dust detection algorithm detects about 30% of weakly dusty pixels and more than 80% of heavily dusty pixels, with false detections in the range of 1–2%. The very low false detection rate is particularly noteworthy in comparison with existing literature. Compared with the dust flag currently available as part of the MODIS cloud mask product (MOD35/MYD35), and dust classification based on commonly used thresholds with aerosol optical depth (AOD) and Angstrom exponent (AE), the new dust detection algorithm finds more dusty pixels and fewer false detections.

spectral dust detection↗

NASA NTRS2008

Venus Quadrangle Geological Mapping: Use of Geoscience Data Visualization Systems in Mapping and Training

We are currently investigating new technological developments in computer visualization and analysis in order to assess their importance and utility in planetary geological analysis and mapping [1,2]. Last year we reported on the range of technologies available and on our application of these to various problems in planetary mapping [3]. In this contribution we focus on the application of these techniques and tools to Venus geological mapping at the 1:5M quadrangle scale. In our current Venus mapping projects we have utilized and tested the various platforms to understand their capabilities and assess their usefulness in defining units, establishing stratigraphic relationships, mapping structures, reaching consensus on interpretations and producing map products. We are specifically assessing how computer visualization display qualities (e.g., level of immersion, stereoscopic vs. monoscopic viewing, field of view, large vs. small display size, etc.) influence performance on scientific analysis and geological mapping. We have been exploring four different environments: 1) conventional desktops (DT), 2) semi-immersive Fishtank VR (FT) (i.e., a conventional desktop with head-tracked stereo and 6DOF input), 3) tiled wall displays (TW), and 4) fully immersive virtual reality (IVR) (e.g., "Cave Automatic Virtual Environment," or Cave system). Formal studies demonstrate that fully immersive Cave environments are superior to desktop systems for many tasks [e.g., 4].

Head, James W.↗

NASA NTRS2019

NASA IV&V's Cyber Range for Space Systems

A cyber range is a virtual environment that is used for cyberwarfare training and cyber technology development. It provides tools that help strengthen the stability, security and performance of cyber infrastructures and IT systems. NASA IV&V has created an adaptable virtual environment that is representative of a typical NASA mission system of systems environment that serves multiple purposes: Training of network defenders. Ability to perform simulated red vs blue training events. Ability to deploy mission specific technologies in a cyber contested environment. Ability to demonstrate vulnerabilities and their impact to ground and space systemsThe overall system is comprised of more than 70 virtual machines and physical infrastructure to demonstrate real-world cyber attacks against: email users, wireless networks, and physically implanted devices with command and control call-back. The cyber range was built to emulate a NASA precipitation satellite infrastructure.This presentation will give an overview of the virtual cyber range and how it was used to conduct a simulate red vs blue exercise with the goal of compromising the simulated spacecraft that utilizes real NASA flight software.

test and evaluation DT&E↗