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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

LiDAR-Inertial Based Navigation and Mapping for Precision Landing

Future lander missions will travel to ambitious, scientifically interesting locations near rough and dangerous terrain. They will need to operate with limited prior information about the terrain, and under varying lighting conditions. Landing safely and precisely in the face of these challenges is difficult for existing vision-based landing systems, which require detailed orbital reconnaissance, a priori hazard maps, and impose time-of-day restrictions on landing to ensure similar lighting conditions in orbital and descent imagery. Advanced 3D imaging LiDAR systems currently under development, and originally intended for single-scan hazard detection, have the potential to be operated continuously from altitudes of up to 5 km. Used together with existing inertial measurement units (IMUs), these sensors open a path-to-flight for a full navigation and mapping system, which could replace or augment a traditional landing sensor suite. A landing system based around these sensors can perform accurate altimetry, map-relative localization (MRL), LiDAR-inertial odometry, and map refinement in an illumination-insensitive manner, over unknown or partially known terrain. This paper outlines preliminary work on a LiDAR-inertial landing system that: estimates the spacecraft trajectory during entry, descent, and landing (EDL); and maps the topography of the terrain below, for future use in hazard detection and avoidance. An incremental, factor graph based, smoothing approach is used to solve for the maximum a posteriori trajectory of spacecraft states. Integrated IMU measurements and features tracked in adjacent range and intensity images are used to estimate motion (LiDAR-inertial odometry). LiDAR scans are binned into motion-corrected digital elevation models (DEMs), which are matched to an existing orbital topographic map to provide absolute position information (MRL). The estimated trajectory is then used to project the LiDAR scans into the map frame, creating a variable-resolution quadtree topographic map suitable for hazard detection and avoidance. Existing topographic maps from throughout the solar system (i.e., Earth, the Moon, Mars, Ceres, Vesta, Europa, Enceladus, and Eros) are upsampled for use in EDL simulations. The Mars 2020 Lander Vision System Simulator (LVSS) is extended to simulate LiDAR-inertial data for realistic EDL trajectories. Results of the algorithm operating on the simulated data are presented. Estimated spacecraft trajectory and refined map are compared to ground truth to assess estimation accuracy.

Katake, Anup↗
NASA NTRS2016

Flight Test Overview for UAS Integration in the NAS Project

The National Aeronautics and Space Administration is conducting a series of flight tests intended to support the reduction of barriers that prevent unmanned aircraft from flying without the required waivers from the Federal Aviation Administration. The most recent testing supported two separate test configurations. The first investigated the timing of Detect and Avoid (DAA) alerting thresholds using a radar-equipped unmanned vehicle and multiple live intruders flown at varying encounter geometries. The second configuration included a surrogate unmanned vehicle (flown from a ground control station, with a safety pilot on board) flying a mission in a virtual air traffic control airspace sector using research pilot displays and DAA advisories to maintain separation from live and virtual aircraft. The test was conducted over a seven-week span in the summer of 2015. The data from over 100 encounter sorties will be used to inform the RTCA Phase 1 Detect and Avoid and Command and Control Minimum Operating Performance Standards (MOPS) intended to be completed by the summer of 2016. Follow-on flight-testing is planned for the spring of 2016 to capture remaining encounters and support validation of the MOPS.

UAS↗
NASA NTRS2021

State of the Industry: UAS Sensor Review

This report is a follow on from HF Designworks’ 2018 report on state of the present and state of the art sensor technologies as they related to Ground Based Detect and Avoid (GBDAA) systems for Unmanned Aircraft Systems (UAS). In this update, HF Designworks again looks to UAS test sites, manufacturers, vendors, and users to identify the latest sensor technologies covering not just GBDAA, but additional UAS sensor types; including airborne. For this latest report, the following sensor types were reviewed, as well as a few that don’t quite fit within the following categories: Electro-Optical / Infrared (EO/IR), LiDAR, RADAR, Radiofrequency (RF) scanner, Acoustic, and Other. From our interviews and research with various organizations and individuals, we found both interesting new technologies as well as improvements to many technologies first reviewed in 2018. Compared with our 2018 findings, many of the new technologies have helped produce sensors that are smaller, lighter, require less power, and have better range and resolution than those discussed in 2018. However, challenges still exist. There is no single currently available and FAA approved sensor suite that can adequately provide complete detect and avoid capabilities to meet the needs of UAS beyond visual line of sight (BVLOS) in the civilian airspace.

unmanned aircraft systems↗
NASA NTRS2020

UAS Pilot Assessments of Display and Alerting for the Next Generation Airborne Avoidance System

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback on these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS Xu alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

unmanned aircraft systems↗
NASA NTRSDate not supplied

UAS Pilot Assessments of Display and Alerting for the Next Generation Airborne Collision Avoidance System Xu

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback on these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS Xu alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

unmanned aircraft systems↗
NASA NTRSDate not supplied

UAS Pilot Assessments of Display and Alerting for the Airborne Collision Avoidance System XU

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback on these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS Xu alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

unmanned aircraft systems↗
NASA NTRS2016

FT4 Data Analysis Summary (SSI-ARC)

Standards for Unmanned Aircraft System (UAS) Detect-and-Avoid (DAA) systems are currently being developed under the auspices of the RTCA Special Committee 228 (SC-228). To support the development of these standards, a series of flight tests has been conducted at NASAs Armstrong Flight Research Center (NASA-AFRC). The fourth in this series of flight test activities (Flight Test 4, or simply FT4) was conducted during the Spring and Summer of 2016. FT4 supported the objectives of numerous organizations working toward UAS DAA Minimum Operational Performance Standards (MOPS) and UAS DAA Radar MOPS. The summary provided herein is limited to the objectives, analysis and conclusions of the NASA Ames Research Center (NASA-ARC) SSI team toward the refinement of UAS DAA MOPS. This document provides a high-level overview of FT4 and the SSI-ARC objectives, a summary of the data analysis methodology and recommendations for UAS DAA MOPS refinements based on the data analysis results. A total of 72 encounters were flown to support SSI-ARC objectives. Test results were generally consistent with acceptable UAS DAA system performance and will be considered in broader SC-228 requirements validation efforts. Observed alert lead times indicated acceptable UAS DAA alerting performance. Effective interoperability between the UAS DAA system and the Traffic Alert and Collision Avoidance System (TCAS) was observed with one notable exception: TCAS Resolutions Advisories (RA) were observed in the absence of any DAA alert on two occasions, indicating the need for alert parameter refinement. Findings further indicated the need for continued work in the areas of DAA Well Clear Recovery logic and alert stability for Mode-C-only intruders. Finally, results demonstrated a high level of compliance with a set of evaluation criteria designed to provide anecdotal evidence of acceptable UAS DAA system performance.

UAS Test Flight↗
NASA NTRS1990

Kalman filter based range estimation for autonomous navigation using imaging sensors

Rotorcraft operating in high-threat environments fly close to the surface of the earth to utilize surrounding terrain, vegetation, or man-made objects to minimize the risk of being detected by the enemy. Two basic requirements for obstacle avoidance are detection and range estimation of the object from the current rotorcraft position. There are many approaches to the estimation of range using a sequence of images. The approach used in this analysis differes from previous methods in two significant ways: an attempt is not made to estimate the rotorcraft's motion from the images; and the interest lies in recursive algorithms. The rotorcraft parameters are assumed to be computed using an onboard inertial navigation system. Given a sequence of images, using image-object differential equations, a Kalman filter (Sridhar and Phatak, 1988) can be used to estimate both the relative coordinates and the earth coordinates of the objects on the ground. The Kalman filter can also be used in a predictive mode to track features in the images, leading to a significant reduction of search effort in the feature extraction step of the algorithm. The purpose is to summarize early results obtained in extending the Kalman filter for use with actual image sequences. The experience gained from the application of this algorithm to real images is very valuable and is a necessary step before proceeding to the estimation of range during low-altitude curvilinear flight. A simple recursive method is presented to estimate range to objects using a sequence of images. The method produces good range estimates using real images in a laboratory set up and needs to be evaluated further using several different image sequences to test its robustness. The feature generation part of the algorithm requires further refinement on the strategies to limit the number of features (Sridhar and Phatak, 1989). The extension of the work reported here to curvilinear flight may require the use of the extended Kalman filter.

Sridhar, Banavar↗
DOE OSTI2024

Window obscuration sensors for mobile gas and chemical imaging cameras

An infrared (IR) imaging system for determining a concentration of a target species in an object is disclosed. The imaging system can include an optical system including a focal plane array (FPA) unit behind an optical window. The optical system can have components defining at least two optical channels thereof, said at least two optical channels being spatially and spectrally different from one another. Each of the at least two optical channels can be positioned to transfer IR radiation incident on the optical system towards the optical FPA. The system can include a processing unit containing a processor that can be configured to acquire multispectral optical data representing said target species from the IR radiation received at the optical FPA. One or more of the optical channels may be used in detecting objects on or near the optical window, to avoid false detections of said target species.

Mallery, Ryan↗
NASA NTRS2016

Unmanned Aircraft Systems in the National Airspace System: A Formal Methods Perspective

As the technological and operational capabilities of unmanned aircraft systems (UAS) have grown, so too have international efforts to integrate UAS into civil airspace. However, one of the major concerns that must be addressed in realizing this integration is that of safety. For example, UAS lack an on-board pilot to comply with the legal requirement that pilots see and avoid other aircraft. This requirement has motivated the development of a detect and avoid (DAA) capability for UAS that provides situational awareness and maneuver guidance to UAS operators to aid them in avoiding and remaining well clear of other aircraft in the airspace. The NASA Langley Research Center Formal Methods group has played a fundamental role in the development of this capability. This article gives a selected survey of the formal methods work conducted in support of the development of a DAA concept for UAS. This work includes specification of low-level and high-level functional requirements, formal verification of algorithms, and rigorous validation of software implementations.

Munoz, Cesar A.↗
NASA NTRS2018

Utility of Visual and Auditory Warning Alerting for Traffic Avoidance During UAS Operations

This presentation covers the results of a human-in-the-loop simulation that examined the effect of caution versus warning-level alerting in the context of Unmanned Aircraft System (UAS) operations in civil airspace. Minimum Operational Performance Standards (MOPS) are currently being developed by RTCA Special Committee 228 for UAS Detect-and-Avoid (DAA) systems. Input from subject matter experts and multiple research studies have informed display requirements for DAA systems aimed at supporting timely and appropriate pilot responses to collision hazards. DAA alerting is designed to inform pilots of potential threats to DAA "well clear"; the two highest alert levels - caution and warning - indicate how soon pilot action is required and whether there is adequate time to coordinate with the air traffic controller (ATC). Additional empirical support is needed to clarify the extent to which warning-level alerting impacts DAA task performance. The present study explores the differential effects of the auditory and visual cues provided by the DAA Warning alert, and performance implications compared to caution-only alerting are discussed.

detect and avoid↗
NASA NTRS2016

NASA UAS Integration into the NAS Project: Human Systems Integration

This presentation provides an overview of the work the Human Systems Integration (HSI) sub-project has done on detect and avoid (DAA) displays while working on the UAS (Unmanned Aircraft System) Integration into the NAS project. The most recent simulation on DAA interoperability with Traffic Collision Avoidance System (TCAS) is discussed in the most detail. The relationship of the work to the larger UAS community and next steps are also detailed.

unmanned aircraft systems↗
NASA NTRS2017

UAS Well Clear Recovery Against Non-Cooperative Intruders Using Vertical Maneuvers

This paper documents a study that drove the development of a mathematical expression in the detect-and-avoid (DAA) minimum operational performance standards (MOPS) for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance should be provided during recovery of DAA well clear separation with a non-cooperative VFR aircraft. Although the original hypothesis was that vertical maneuvers for DAA well clear recovery should only be offered when sensor vertical rate errors are small, this paper suggests that UAS climb and descent performance should be considered-in addition to sensor errors for vertical position and vertical rate-when determining whether to offer vertical guidance. A fast-time simulation study involving 108,000 encounters between a UAS and a non-cooperative visual-flight-rules aircraft was conducted. Results are presented showing that, when vertical maneuver guidance for DAA well clear recovery was suppressed, the minimum vertical separation increased by roughly 50 feet (or horizontal separation by 500 to 800 feet). However, the percentage of encounters that had a risk of collision when performing vertical well clear recovery maneuvers was reduced as UAS vertical rate performance increased and sensor vertical rate errors decreased. A class of encounter is identified for which vertical-rate error had a large effect on the efficacy of horizontal maneuvers due to the difficulty of making the correct left/right turn decision: crossing conflict with intruder changing altitude. Overall, these results support logic that would allow vertical maneuvers when UAS vertical performance is sufficient to avoid the intruder, based on the intruder's estimated vertical position and vertical rate, as well as the vertical rate error of the UAS' sensor.

UAS in the NAS↗
NASA NTRS2015

SSI-ARC Flight Test 3 Data Review

The "Unmanned Aircraft System (UAS) Integration into the National Airspace System (NAS)" Project conducted flight test program, referred to as Flight Test 3, at Armstrong Flight Research Center from June - August 2015. Four flight test days were dedicated to the NASA Ames-developed Detect and Avoid (DAA) System referred to as Autoresolver. The encounter scenarios, which involved NASA's Ikhana UAS and a manned intruder aircraft, were designed to collect data on DAA system performance in real-world conditions and uncertainties with four different surveillance sensor systems. Resulting flight test data and analysis results will be used to evaluate the DAA system performance (e.g., trajectory prediction accuracy, threat detection) and to add fidelity to simulation models used to inform Minimum Operating Performance Standards (MOPS) for integrating UAS into routine NAS operations.

detect and avoid↗
NASA NTRS2017

Modeling and Simulation Plans in Support of Low Cost, Size, Weight, and Power Surveillance Systems for Detecting and Tracking Non-Cooperative Aircraft

RTCA Special Committee (SC) 228 has initiated a second phase for the development of minimum operational performance standards (MOPS) for UAS detect and avoid (DAA) systems. Technologies to enable UAS with less available Size, Weight, and Power (SWaP) will be considered. RTCA SC-228 has established sub-working groups and one of the sub-working groups is focused on aligning modeling and simulations activities across all participating committee members. This briefing will describe NASAs modeling and simulation plans for the development of performance standards for low cost, size, weight, and power (C-SWaP) surveillance systems that detect and track non-cooperative aircraft. The briefing will also describe the simulation platform NASA intends to use to support end-to-end verification and validation for these DAA systems. Lastly, the briefing will highlight the experiment plan for our first simulation study, and provide a high-level description of our future flight test plans. This briefing does not contain any results or data.

surveillance↗