M.U. de Haag

Improved downward-looking terrain database integrity monitor and terrain navigation

Terrain database integrity monitors and terrain referenced navigation systems are both based on performing a comparison between stored terrain elevation data and data obtained from airborne sensors such as radar altimeters, inertial measurement units (IMUs), Global Positioning System (GPS) receivers etc. The concept of consistency checking as used for the integrity monitor function originated from terrain referenced navigation systems. This paper discusses the extension to a previously proposed method of improving the performance of a spatial integrity monitor for terrain elevation databases. Furthermore, this paper discusses an improvement of the terrain-referenced aircraft position estimation for aircraft navigation using only the information from downward-looking sensors, GPS and the terrain databases, and not the information from the IMU. Horizontal failures have been characterized based on the sensed terrain information. Kalman filter methods have been designed to achieve the integrity monitor and terrain navigation performance improvements. The performance of the proposed position estimator and integrity monitor is evaluated using flight test data from NASAs flight trials at Eagle/Vail (EGE), CO and Ohio Universitys flight trials at Albany (KUNI), OH, Asheville (AVL), NC, and Juneau (JNU), AK.

Aircraft Heading Measurement Potential from an Airborne Laser Scanner Using Edge Extraction

This paper explores some considerations for making aircraft heading measurements by using an airborne laser scanner (ALS). Laser range measurements are very low noise and high accuracy, so there is potential for high accuracy heading measurements that are not susceptible to broad interference. This heading could stabilize other sensors even when GPS is unavailable. Heading measurements are emphasized since they are often the most sought after quantity for inertial alignment and other applications. The traditional ALS configuration is capable of estimating heading from extracted ground feature edges with degree-level accuracy. Furthermore, the paper discusses two techniques for increasing the laser ground pulse density (by rotating the scanner about the aircraft vertical axis (yaw) and by modifying the scanner parameters). Estimates are provided on how much theoretical accuracy can be expected from each technique and a hybrid technique. The results suggest that it is possible to improve the theoretical heading measurement accuracy by at least one order of magnitude. The second half of the paper discusses sensor stabilization limitations to attaining a high accuracy orientation measurement. This sensitivity analysis describes how noise and bias errors from uncompensated motion and/or sensor stabilization in pitch, roll, and yaw will effect the laser ground pulse positions. The results show that it is better to have stabilization noise than uncompensated motion errors.

Feature extraction and separation in airborne laser scanner terrain integrity monitors

This paper describes the methodology and algorithms used in an implementation of a downward-looking airborne laser scanner (ALS) based terrain and feature integrity monitor. Using a high accuracy and high resolution ALS sensor, the described integrity monitor can first separate features from the terrain and then use the extracted feature data to detect and observe systematic and blunder errors in a terrain feature database. Two applications are envisioned for such a system - the first is to check the quality and update a terrain feature database and the second is as a real-time monitor on all aircraft which have systems that use terrain feature databases. Real-time terrain database integrity monitors have been studied at the Ohio University Avionics Engineering Center (AEC) for nearly 10 years. The feature integrity monitor is different from previous research performed at Ohio University in that it extracts specific features, such as buildings, roads, and towers, and performs a consistency check between these objects and a stored feature database. To perform the consistency check between the feature database and the ALS data a four-part building extraction algorithm is used. Once the high-frequency building shapes are extracted, they can be compared to the onboard feature database to determine changes and errors. The four-part building extraction algorithm described in this paper has the following characteristics: it works on non-uniformly spaced point-cloud data, it is designed for integrity monitoring rather than complete scene reconstruction, and the automatic feature extraction is not dependent on (but may use if available) a-priori feature shape information. This paper outlines the four-part building extraction algorithm and provides insight into its operation by applying the algorithms to ALS data collected on NASAs DC-8 Airborne Laboratory over Reno, Nevada in 2003.

A terrain database integrity monitor for synthetic vision systems

This paper discusses a terrain database integrity monitor for Synthetic Vision Systems (SVS) in Civil Aviation applications. SVS provide the pilots with advanced display technology containing terrain information as well as other information about the external environment such as obstacles and traffic. SVS will improve situational awareness and thereby reduce the likelihood of Controlled Flight Into Terrain (CFIT). Safe utilization of the SVS for strategic and tactical applications may require a terrain database integrity check. The discussed integrity monitor checks the consistency between the sensed terrain profile as computed from DGPS and radar altimeter data and the terrain profile as given by the terrain databases. A case study to verify the integrity monitors performance is presented based on data collected during flight-testing performed by NASA at Asheville, NC.

Three-Dimensional Navigation with Scanning Ladars: Concept & Initial Verification

This paper investigates the use of scanning laser radars (LADARs) for 3D navigation of autonomous vehicles in structured environments such as outdoor urban navigation scenarios. The navigation solution (position and orientation) is determined in unknown environments where no a priori map information is available. The navigation is based on the use of planar surfaces (planes) extracted from LADAR scan images. Changes in plane parameters between scans are applied to compute position and orientation changes. Feasibility of the algorithms developed is verified using simulation results and initial results of live data tests.

Dual Airborne Laser Scanners Aided Inertial for Improved Autonomous Navigation

A dead-reckoning terrain referenced navigation (TRN) system is presented that uses two airborne laser scanners (ALS) to aid an inertial navigation system (INS). The system uses aircraft autonomous sensors and is capable of performing the dual functions of mapping and navigation simultaneously. The proposed system can potentially serve as a backup to the Global Positioning System (GPS), increase the robustness of GPS or it can be used to coast for extended periods of time. Although the system has elements of a conventional TRN system, it does not require a terrain database since its in-flight mapping capability generates the terrain data for navigation. Hence, the system can be used in both non-GPS as well as unknown terrain environments. It is shown that the navigation system is dead-reckoning in nature since errors accumulate over time, unless the system can be reset periodically by the availability of geo-referenced terrain data or a position estimate from another navaid. Results of the algorithm using a combination of flight trajectory data and synthesized ALS data are presented.

Assessment of radar altimeter performance when used for integrity monitoring in a synthetic vision system

Synthetic Vision Systems (SVS) are being developed to support a wide variety of operations. These operations include tactical or critical applications of the SVS. To enable certification of an SVS as a flight-critical system several requirements must be met with regards to accuracy, integrity, availability, and continuity. Ohio University has been developing a prototype SVS as part of NASAs aviation safety program that includes a real-time terrain database integrity monitor to guarantee the required integrity. Ohio Universitys integrity monitor provides a consistency check between a terrain database profile and a synthesized terrain profile. The synthesized terrain profile is generated from information from Global Positioning System (GPS) and a radar altimeter. This paper explores the radar altimeter performance for use in a SVS terrain database integrity monitor. This data will be used in this paper to assess the various radar altimeters. Data from two different radar altimeters and highly accurate photogrammetry digital elevation models (DEM) are used to evaluate the performance of the radar altimeters. The effects of the terrain variation underneath the aircraft and the radar altimeter antenna beamwidth on the performance of the radar altimeter are discussed.

Flight test results of loose integration of dual airborne laser scanners (DALS)/INS

Aircraft positioning and navigation capability much be robust to ensure continuity of operation. Such navigation information is largely provided by an inertial navigation system (INS), which is a self-contained autonomous system. INS is usually integrated with GPS measurements to improve its accuracy and a GPS/INS package is a common feature of most navigation systems. However, these systems suffer degraded performance in non-GPS environments; such as when GPS is denied due to interference or jamming, or when GPS is unavailable as in Lunar or Martian scenarios. In recent years, the challenge of navigating in non-GPS environments has generated much interest. With this same objective, we investigate the use of dual airborne laser scanners (DALS), integrated with an INS for navigation in non-GPS and unknown terrain environments. In this paper, we present a proof-of-concept demonstration of the DALS/INS autonomous navigation system with flighttest data, collected onboard Ohio Universitypsilas DC-3 aircraft over Athens, OH.

Runway obstacle detection using onboard sensors: Modeling and simulation analysis

In recent years, the increasing demand on the national airspace system (NAS) has propelled further research on new technologies, communication systems, sensors and methods to handle the growing congestion around the terminal area. These include programs such as the runway incursion prevention system (RIPS), automatic dependent surveillance - broadcast (ADS-B), the national aeronautics and space administrationpsilas (NASA) synthetic vision systems (SVS) and more recently, NASApsilas integrated intelligent flight deck (IIFD) project. One of the aspects of the IIFD is an external hazard monitor (EHM) function that interfaces with onboard terrain and obstacle databases, communications, and also with aircraft sensors. The EHM is envisioned to provide improved obstacle detection and hazard evaluation with added integrity and reliability. The work in this paper is performed in support of the EHM function and presents a modeling and simulation framework that models the aircraft sensors, synthesizes their measurements and analyzes their runway obstacle detection capability using both simulations and flight data playback. Various sensor parameters, measurement errors and physical properties of potential runway hazards/objects are evaluated in the simulations. Particular sensors that are considered for this work are: airborne laser scanner (ALS), 3D imaging camera, and forward-looking infrared camera (FLIR). The sensors are evaluated with regard to detection metrics such as probability of detection and time-to-alarm. Furthermore, results from the simulations using playback of actual flight test data in the vicinity of Braxton county airport (K48I), WV and Reno (RNO), NV are presented.

Detection of mobile runway obstacles using dual airborne laser scanners

This paper examines the use of airborne Light Detection and Ranging (LIDAR) for detection and velocity estimation of mobile obstacles in airport movement areas during landing and low altitude flight. Depending upon the operational conditions, obstacles may become hazards posing a threat to landing safety. In order to prevent runway incursions caused by runway obstacles, pilots must be made aware of all surface traffic. This traffic not only includes other aircraft, but also objects such as ground vehicles, wildlife, pedestrians, and debris. Current landing safety systems such as Automatic Dependent Surveillance-Broadcast (ADS-B) are limited to vehicles equipped with a transponder, while the Airport Movement Area Safety System (AMASS) is limited by factors including hazard size and communication latency with the pilot. A truly robust hazard monitoring system capable of operating in all scenarios and landing conditions must include the capability to detect all airport surface traffic, estimate the state of that traffic. This task would preferably be independent of information from monitoring systems external to the aircraft. The hazard monitor proposed in this paper makes use of two airborne laser scanners (ALS), an inertial measurement unit (IMU), and the Global Positioning System (GPS) to identify and accurately geo-locate all runway obstacles in addition to estimating the state of the hazard though velocity prediction. Flight-testing and data collection using this system has been preformed at the Ohio University Airport (KUNI) in Albany, Ohio. Results indicate geo-referencing accuracy of approximately 2 m in most cases, along with successful hazard classification, and hazard velocity estimates accurate to within 2.8 m/s.