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At least 217 records · Page 12

Terminal area automatic navigation, guidance, and control research using the Microwave Landing System (MLS). Part 4: Transition path reconstruction along a straight line path containing a glideslope change waypoint

The necessary algorithms to reconstruct the glideslope change waypoint along a straight line in the event the aircraft encounters a valid MLS update and transition in the terminal approach area are presented. Results of a simulation of the Langley B737 aircraft utilizing these algorithms are presented. The method is shown to reconstruct the necessary flight path during MLS transition resulting in zero cross track error, zero track angle error, and zero altitude error, thus requiring minimal aircraft response.

Pines, S.↗

Terminal area automatic navigation, guidance and control research using the Microwave Landing System (MLS). Part 5: Design and development of a Digital Integrated Automatic Landing System (DIALS) for steep final approach using modern control techniques

The design and development of a 3-D Digital Integrated Automatic Landing System (DIALS) for the Terminal Configured Vehicle (TCV) Research Aircraft, a B-737-100 is described. The system was designed using sampled data Linear Quadratic Gaussian (LOG) methods, resulting in a direct digital design with a modern control structure which consists of a Kalman filter followed by a control gain matrix, all operating at 10 Hz. DIALS uses Microwave Landing System (MLS) position, body-mounted accelerometers, as well as on-board sensors usually available on commercial aircraft, but does not use inertial platforms. The phases of the final approach considered are the localizer and glideslope capture which may be performed simultaneously, localizer and steep glideslope track or hold, crab/decrab and flare to touchdown. DIALS captures, tracks and flares from steep glideslopes ranging from 2.5 deg to 5.5 deg, selected prior to glideslope capture. Digital Integrated Automatic Landing System is the first modern control design automatic landing system successfully flight tested. The results of an initial nonlinear simulation are presented here.

Halyo, N.↗

Analysis of Navigation Doppler Lidar performance for Moon and Mars Landing

The operation of a coherent Doppler lidar, developed by NASA for missions to planetary bodies, is analyzed and its projected performance is described. The lidar transmits three laser beams at different but fixed directions and measures line-of-sight range and velocity along each beam. The three line-of-sight measurements are then combined in order to determine the three components of the vehicle velocity vector and its altitude relative to the ground. Operating from over five kilometers altitude, the NDL provides velocity and range data with a few cm/sec and a few meters precision, respectively, depending on the vehicle dynamics. This paper explains the sources of measurement error and analyzes the impact of vehicle dynamics on the lidar performance.

Farzin Amzajerdian↗

Data management of Shuttle radiofrequency navigation aids

It is noted that the Shuttle navigation system employs redundant tactical air navigation (tacan) and microwave scanning beam landing system (MSBLS) equipment for use in navigation during descent from altitudes of about 150,000 feet through rollout. Attention is given here to the multiple tacan and MSBLS units (three each) that were placed onboard to provide the necessary protection in the event of possible failures. The goals, features, approach, and performance of onboard software required to manage multiple tacan MSBLS units and to provide the corresponding data for navigation processing are described.

Stokes, R. E.↗

Preliminary Design of the Guidance, Navigation, and Control System of the Altair Lunar Lander

Guidance, Navigation, and Control (GN&C) is the measurement and control of spacecraft position, velocity, and attitude in support of mission objectives. This paper provides an overview of a preliminary design of the GN&C system of the Lunar Lander Altair. Key functions performed by the GN&C system in various mission phases will first be described. A set of placeholder GN&C sensors that is needed to support these functions is next described. To meet Crew safety requirements, there must be high degrees of redundancy in the selected sensor configuration. Two sets of thrusters, one on the Ascent Module (AM) and the other on the Descent Module (DM), will be used by the GN&C system. The DM thrusters will be used, among other purposes, to perform course correction burns during the Trans-lunar Coast. The AM thrusters will be used, among other purposes, to perform precise angular and translational controls of the ascent module in order to dock the ascent module with Orion. Navigation is the process of measurement and control of the spacecraft's "state" (both the position and velocity vectors of the spacecraft). Tracking data from the Earth-Based Ground System (tracking antennas) as well as data from onboard optical sensors will be used to estimate the vehicle state. A driving navigation requirement is to land Altair on the Moon with a landing accuracy that is better than 1 km (radial 95%). Preliminary performance of the Altair GN&C design, relative to this and other navigation requirements, will be given. Guidance is the onboard process that uses the estimated state vector, crew inputs, and pre-computed reference trajectories to guide both the rotational and the translational motions of the spacecraft during powered flight phases. Design objectives of reference trajectories for various mission phases vary. For example, the reference trajectory for the descent "approach" phase (the last 3-4 minutes before touchdown) will sacrifice fuel utilization efficiency in order to provide landing site visibility for both the crew and the terrain hazard detection sensor system. One output of Guidance is the steering angle commands sent to the 2 degree-of-freedom (dof) gimbal actuation system of the descent engine. The engine gimbal actuation system is controlled by a Thrust Vector Control algorithm that is designed taking into account the large quantities of sloshing liquids in tanks mounted on Altair. In this early design phase of Altair, the GN&C system is described only briefly in this paper and the emphasis is on the GN&C architecture (that is still evolving). Multiple companion papers will provide details that are related to navigation, optical navigation, guidance, fuel sloshing, rendezvous and docking, machine-pilot interactions, and others. The similarities and differences of GN&C designs for Lunar and Mars landers are briefly compared.

Lee, Allan Y.↗

Assessment of M2020 Terrain Relative Landing Accuracy: Flight Performance vs Predicts

Terrain Relative Navigation (TRN) was a critical enabling Entry, Descent, and Landing (EDL) technology that enabled Mars 2020 mission Perseverance rover to land at Jezero crater. TRN pro-vides real-time, autonomous, map-relative position determination and generates a landing target based on a priori knowledge of hazards. The required performance for TRN was to land within 60m of the selected target. The required 60m was sub-allocated to various error sources in three major categories: targeting error, knowledge error, and control error. The targeting error is the error in selecting an appropriate landing target and the knowledge of the target on the surface. It includes the Lander Vision System (LVS) position localization with respect the ground, the synchronization between the Lander Vision System measurement and the main Navigation filter, and errors associated with the LVS Reference Map and Safe Target Selec-tion (STS). The knowledge error is the contribution of knowledge growth from the synchronization with LVS to touchdown. The control error encompasses how accurately the system could stay on the desired reference trajectory. The TRN error budget uses a combination of analysis, simulation, and hardware test-ing results to bound the various error contributions obtained during the verification and validation process. This paper first presents a description the TRN system, focusing on the architecture of LVS and STS. The paper then gives detailed overview of the TRN error budget, with a description of the major error contribu-tions in each of the three categories. Next, the paper gives the results for three versions of the error budget, pre-launch, in-flight pre-landing, and post-landing. The paper compares the pre-flight analysis, the pre-landing analysis using in-flight data during cruise, to the post-landing analysis of the TRN performance. Pre-landing analysis best estimate of the landing performance was 33m, compared to the 60m require-ment. Post-landing analysis estimated a landing accuracy of 8.53m or better, much better than the 33m pre-landing estimate. The actual post-landing imagery calculated the distance of the rover to the targeted location to be 5m. The post-landing analysis closely bounds the image-based assessment of landing accu-racy, indicating the success of the error budget architecture in bounding the landing accuracy, as well as the fidelity of the simulations used to model and predict performance.

Chen, Allen↗

The Mars 2020 Perseverance Navigation Filter

The Mars 2020 (M2020) Entry Descent and Landing (EDL) system delivered a rover named “Perseverance” at Jezero crater (Mars) on February 18th, 2021. M2020 EDL used a Guidance Navigation and Control (GN&C) system to achieve its landing target objectives. The navigation filter (NavFilter) integrated Descent Inertial Measurement Unit (DIMU) measurements to estimate position and attitude. The NavFilter also used the Terminal Descent Sensor (TDS) to es-timate surface-relative position and velocity corrections. The NavFilter provided all of the dynamic state information to the entry controller, entry guidance, Lander Vision System (LVS) and powered descent guidance and control algo-rithms. The NavFilter for Perseverance is based on Curiosity’s NavFilter with a couple of modifications.

Casoliva, Jordi↗

Lunar Navigation Performance Using the Deep Space Network and Alternate Solutions to Support Precision Landing

As human exploration once again targets the surface of the Moon, questions continue to emerge regarding the necessity of Earth-based tracking systems, such as the Deep Space Network, for spacecraft navigation in support of lunar descent and landing. This paper will derive an extensive Deep Space Network sensor model for use in linear covariance analysis and demonstrate the resulting trajectory dispersions and navigation performance in comparison with alternate solutions, such as terrain relative navigation. An in-depth trade study with considerations for various trajectory profiles, time allocated to ground tracking, number of active ground stations, and interaction with other sensors will be conducted to shed significant insight into sensor suite requirements to ensure safe and precise landing on the Moon.

Navigation↗

A Reusable Design for Precision Lunar Landing Systems

The top-level architecture to accomplish NASA's Vision for Space Exploration is to use Lunar missions and systems not just as an end in themselves, but also as testbeds for the more ambitious goals of Human Mars Exploration (HME). This approach means that Lunar missions and systems are most likely going to be targeted for (Lunar) polar missions, and also for long-duration (months) surface stays. This overacting theme creates basic top-level requirements for any next-generation lander system: 1) Long duration stays: a) Multiple landers in close proximity; b) Pinpoint landings for "surface rendezvous"; c) Autonomous landing of pre-positioned assets; and d) Autonomous Hazard Detection and Avoidance. 2) Polar and deep-crater landings (dark); 3) Common/extensible systems for Moon and Mars, crew and cargo. These requirements pose challenging technology and capability needs. Compare and contrast: 4) Apollo: a) 1 km landing accuracy; b) Lunar near-side (well imaged and direct-to-Earth com. possible); c) Lunar equatorial (landing trajectories offer best navigation support from Earth); d) Limited lighting conditions; e) Significant ground-in-the-loop operations; 5) Lunar Access: a) 10-100m landing precision; b) "Anywhere" access includes polar (potentially poor nav. support from Earth) and far side (poor gravity and imaging; no direct-to-Earth com); c) "Anytime" access includes any lighting condition (including dark); d) Full autonomous landing capability; e) Extensible design for tele-operation or operator-in-the-loop; and f) Minimal ground support to reduce operations costs. The Lunar Access program objectives, therefore, are to: a) Develop a baseline Lunar Precision Landing System (PLS) design to enable pinpoint "anywhere, anytime" landings; b) landing precision 10m-100m; c) Any LAT, LON; and d) Any lighting condition; This paper will characterize basic features of the next generation Lunar landing system, including trajectory types, sensor suite options and a reference system architecture.

Fuhrman, Linda↗

Application of differential GPS to civil helicopter terminal guidance

NASA is conducting a research program to evaluate differential Global Positioning System (GPS) concepts for civil helicopter navigation. It is pointed out that the civil helicopter community will probably be an early user of GPS because of the unique mission operations in areas where precise navigation aids are not available. Applications with very demanding accuracy requirements are related to remote area search and rescue, offshore oil platform approach, remote area precision landing, and other precise navigation operations. Differential GPS appears to provide a solution for meeting the accuracy requirements involved in the considered operations. The present investigation is concerned with results obtained in three areas studied in connection with the conducted research program. Attention is given to mission-tailored satellite selection, a satellite selection algorithm concept, satellite selection algorithm simulation results, and differential GPS ground station design.

Denaro, R. P.↗

Development of a Coherent Doppler Lidar for Precision Landing on Planetary Bodies

A coherent Doppler lidar has been developed by NASA for providing vector velocity and altitude data to landing vehicles. Future robotic and manned missions to planetary bodies demand precise ground-relative velocity and altitude data to execute complex descent maneuvers for safe, soft and pinpoint landing at a pre-designated site. Operating from over five kilometers altitude, this lidar provides velocity and range data within a few cm/sec and a few meters precision, respectively, depending on the vehicle dynamics. Two upcoming lunar landing missions will serve as the technology demonstration for robotic and manned landing missions to the Moon, Mars, and other solar system destinations. This paper describes the lidar design and its expected performance on landing vehicles.

Coherent Laser Radar↗

Navigation and EDL for the Mars Exploration Rovers

A viewgraph presentation on Deep Space Navigation, and Entry, Decent, and Landing (EDL) for Mars Exploration Rovers is shown. The contents include: 1) JPL Spacecraft Operating across the Solar System; 2) 2003 - 2004: The Busiest Period in JPL's History; 3) Deep Space Navigation Will Enable Many of the New NASA Missions; 4) What Exactly is Navigation vs. GNC for Deep Space?; 5) Cruise and Approach: Why is Deep Space Navigation So Difficult?; 6) Project Importance of GNC: Landing Site Selection; 7) Planetary Communications and Tracking; 8) Tracking Data Types; 9) Delta Differential One-Way Range (deltaDOR); 10) All Solutions Leading up to TCM-4 Design; 11) Entry Flight Path Sensitivities; 12) MER Navigation Results; 13) Atmospheric Entry Targeting and Delivery; 14) Landing Ellipse Orientation; 15) MER Landing Site Trade Example; 16) Entry, Descent and Landing: Entry Guidance or What Things Do We NOT do for MER Landings (but we will later...); 17) Entering Martian Space 8:29 p.m. PST (ERT); 18) Entry, Descent and Landing; 19) Entry, Descent and Landing: Terminal Guidance; 20) The Challenge Going from 12,000 mph to Zero in Less Than Six Minutes; 21) Spirit Landing Location; 22) Entry, Descent and Landing: The Future; 23) Powered Descent Time-Line; and 24) Updated Sky Crane Maneuver Description. A short summary is also given on planetary guidance, navigation and control as it pertains to EDL systems

Mars Exploration Rover (MER)↗