Refrigeration for cryogenic sensors and electronic systems : proceedings of a conference held at the National Bureau of Standards, Boulder, CO, October 6-7, 1980 /

Item 247.

GPS fault detection with IMU and aircraft dynamics

Approaches with Vertical Guidance (APV) can provide greater safety and cost savings to general aviation through accurate GPS horizontal and vertical navigation. However, GPS needs augmentation to achieve APV fault detection requirements. Aircraft Based Augmentation Systems (ABAS) fuse GPS with additional sensors at the aircraft. Typical ABAS designs assume high-quality inertial sensors with Kalman filters but these are too expensive for general aviation. Instead of using high-quality (and expensive) sensors, the purpose of this paper is to investigate augmenting GPS with a low-quality MEMS IMU and Aircraft Dynamic Model (ADM). The IMU and ADM are fused together using a multiple model fusion strategy in a bank of Extended Kalman Filters (EKF) with the Normalized Solution Separation (NSS) fault detection scheme. A tightly-coupled configuration with GPS is used and frequent GPS updates are applied to the IMU and ADM to compensate for their errors. Based upon a simulated APV approach, the performance of this architecture in detecting a GPS ramp fault is investigated showing a performance improvement over a GPS-only “snapshot” implementation of the NSS method. The effect of fusing the IMU with the ADM is evaluated by comparing a GPS-IMU-ADM EKF with a GPS-IMU EKF where a small improvement in protection levels is shown.

A spoofing detection method for civilian L1 GPS and the E1-B Galileo Safety of Life service

This paper describes an effective method for signal-authentication and spoofing detection for civilian GNSS receivers using the GPS L1 C/A and the Galileo E1-B Safety of Life service. The paper discusses various spoofing attack profiles and how the proposed method is able to detect these attacks. This method is relatively low-cost and can be suitable for numerous mass-market applications. This paper is the subject of a pending patent.

Demonstration of closed-­loop airborne sense-­and-­avoid using machine vision

This paper describes a vision-based airborne collision avoidance system developed by the Australian Research Centre for Aerospace Automation (ARCAA) under its Dynamic Sense-and-Act (DSA) program. We outline the system architecture and the flight testing undertaken to validate the system performance under realistic collision course scenarios. The proposed system could be implemented in either manned or unmanned aircraft, and represents a step forward in the development of a “sense-and-avoid” capability equivalent to human “see-and-avoid”.

Real-time wind speed estimation and compensation for improved flight

This paper presents the development and experimental validation of a prototype system for online estimation and compensation of wind disturbances onboard small Rotorcraft unmanned aerial systems (RUAS). The proposed approach consists of integrating a small pitot-static system onboard the vehicle and using simple but effective algorithms for estimating the wind speed in real time. The baseline flight controller has been augmented with a feed-forward term to compensate for these wind disturbances, thereby improving the flight performance of small RUAS in windy conditions. The paper also investigates the use of online airspeed measurements in a closed-loop for controlling the RUAS forward motion without the aid of a global positioning system (GPS). The results of more than 80 flights with a RUAS confirm the validity of our approach.

A Minimax Filter for Systems with Large Plant Uncertainties Using Measurements Corrupted by Colored Noise

A minimax filter is derived to estimate the state of a system, using observations corrupted by colored noise, when large uncertainties in the plant dynamics and process noise are presen.

Finite data performance of MUSIC and minimum norm methods

In the direction of arrival (DOA) estimation problem, we encounter both finite data and insufficient knowledge of array characterization. It is therefore important to study how subspace-based methods perform in such conditions. We analyze the finite data performance of the multiple signal classification (MUSIC) and minimum norm (min. norm) methods in the presence of sensor gain and phase errors, and derive expressions for the mean square error (MSE) in the DOA estimates. These expressions are first derived assuming an arbitrary array and then simplified for the special case of an uniform linear array with isotropic sensors. When they are further simplified for the case of finite data only and sensor errors only, they reduce to the recent results given in [9-12]. Computer simulations are used to verify the closeness between the predicted and simulated values of the MSE.

UAV Grouping and Coordination Tactics for Ground Attack Missions

Grouping and coordination tactics for ground attack missions by a heterogeneous mix of reconnaissance, enemy suppression, and attack unmanned aerial vehicles (UAVs) is presented. Dubins' paths are used to determine the optimal number of attack UAVs and their positional and heading freedoms, as functions of weapon seeker range and field of view. A generic battlefield scenario with layered defense is created and the tactics are evaluated on a Group Flyer simulation platform for both nominal and off-nominal conditions.

Formation Flying with Nonlinear Partial Integrated Guidance and Control

Using the dynamic inversion philosophy, a nonlinear partial integrated guidance and control approach is presented in this paper for formation flying. It is based on the evolving philosophy of integrated guidance and control. However, it also retains the advantages of the conventional guidance then control philosophy by retaining the timescale separation between translational and rotational dynamics explicitly. Simulation studies demonstrate that the proposed technique is effective in bringing the vehicles into formation quickly and maintaining the formation.

Optimum Magnetic Circuit Configurations for Permanent Magnet Aerospace Generators

In the design of high-speed low-power electrical generators for unmanned aircraft and spacecraft, maximization of specific output (power/weight) is of prime importance. Several magnetic circuit configurations (radial-field, axial-field, flux-squeezing, homopolar) have been proposed, and in this paper the relative merits of these configurations are subjected to a quantitative investigation over the speed range 10 000–100000 rev/min and power range 250 W-10 kW. The advantages of incorporating new high energy-density magnetic materials are described. Part I deals with establishing an equivalent circuit for permanent-magnet generators. For each configuration the equivalent circuit parameters are related to the physical dimensions of the generator components and an optimization procedure produces a minimum volume design at discrete output powers and operating speeds. The technique is illustrated by a quantitative comparison of the specific outputs of conventional radial-field generators with samarium cobalt and alnico magnets. In Part II the specific outputs of conventional, flux-squeezing, and claw-rotor magnetic circuit configurations are compared. The flux-squeezing configuration is shown to produce the highest specific output for small sizes whereas the conventional configuration is best at large sizes. For all sizes the claw-rotor configuration is significantly inferior. In Part III the power densities available from axial-field and flux-switching magnetic circuit configurations are maximized, over the power range 0.25-10 kW and speed range 10 000–100000 rpm, and compared to the results of Parts I & II. For the axial-field configuration the power density is always less than that of the conventional and flux-squeezing radial-field configurations. For the flux-switching generator, which is able to withstand relatively high mechanical forces in the rotor, the power density is again inferior to the radial-field types, but the difference is less apparent for small (low power, high speed) generator sizes. From the combined results it can be concluded that the flux-squeezing and conventional radial-field magnetic circuit configurations yield designs with minimum volume over the power and speed ranges considered. © 1985, IEEE. All rights reserved.

Automatic Understanding of ATC Speech: Study of Prospectives and Field Experiments for Several Controller Positions

Although there has been a lot of interest in recognizing and understanding air traffic control (ATC) speech, none of the published works have obtained detailed field data results. We have developed a system able to identify the language spoken and recognize and understand sentences in both Spanish and English. We also present field results for several in-tower controller positions. To the best of our knowledge, this is the first time that field ATC speech (not simulated) is captured, processed, and analyzed. The use of stochastic grammars allows variations in the standard phraseology that appear in field data. The robust understanding algorithm developed has 95% concept accuracy from ATC text input. It also allows changes in the presentation order of the concepts and the correction of errors created by the speech recognition engine improving it by 17% and 25%, respectively, absolute in the percentage of fully correctly understood sentences for English and Spanish in relation to the percentages of fully correctly recognized sentences. The analysis of errors due to the spontaneity of the speech and its comparison to read speech is also carried out. A 96% word accuracy for read speech is reduced to 86% word accuracy for field ATC data for Spanish for the "clearances" task confirming that field data is needed to estimate the performance of a system. A literature review and a critical discussion on the possibilities of speech recognition and understanding technology applied to ATC speech are also given.

Two-layer particle filter for multiple target detection and tracking

This paper deals with the detection and tracking of an unknown number of targets using a Bayesian hierarchical model with target labels. To approximate the posterior probability density function, we develop a two-layer particle filter. One deals with track initiation, and the other with track maintenance. In addition, the parallel partition method is proposed to sample the states of the surviving targets.

The smart skies project

This paper describes the Smart Skies project, an ambitious and world-leading research endeavor exploring the development of key enabling technologies, which support the efficient utilization of airspace by manned and unmanned airspace users. This paper provides a programmatic description of the research and development of: an automated separation management system, a mobile aircraft tracking system, and aircraft-based sense-and-act technologies. A summary of the results from a series of real-world flight testing campaigns is also presented.