A Short Tutorial on Inertial Navigation System and Global Positioning System Integration

The purpose of this document is to describe a simple method of integrating Inertial Navigation System (INS) information with Global Positioning System (GPS) information for an improved estimate of vehicle attitude and position. A simple two dimensional (2D) case is considered. The attitude estimates are derived from sensor data and used in the estimation of vehicle position and velocity through dead reckoning within the INS. The INS estimates are updated with GPS estimates using a Kalman filter. This tutorial is intended for the novice user with a focus on bringing the reader from raw sensor measurements to an integrated position and attitude estimate. An application is given using a remotely controlled ground vehicle operating in assumed 2D environment. The theory is developed first followed by an illustrative example

Verification of Prognostic Algorithms to Predict Remaining Flying Time for Electric Unmanned Vehicles

This paper addresses the problem of building trust in the online prediction of a eUAVs remaining available flying time powered by lithium-ion polymer batteries. A series of ground tests are described that make use of an electric unmanned aerial vehicle (eUAV) to verify the performance of remaining flying time predictions. The algorithm verification procedure described is implemented on a fully functional vehicle that is restrained to a platform for repeated run-to-functional-failure (charge depletion) experiments. The vehicle under test is commanded to follow a predefined propeller RPM profile in order to create battery demand profiles similar to those expected during flight. The eUAV is repeatedly operated until the charge stored in powertrain batteries falls below a specified limit threshold. The time at which the limit threshold on battery charge is crossed is then used to measure the accuracy of the remaining flying time prediction. In our earlier work battery aging was not included. In this work we take into account aging of the batteries where the parameters were updated to make predictions. Accuracy requirements are considered for an alarm that warns operators when remaining flying time is estimated to fall below the specified limit threshold

Flight Tests of a Remaining Flying Time Prediction System for Small Electric Aircraft in the Presence of Faults

This paper addresses the problem of building trust in the online prediction of a battery powered aircraft's remaining flying time. A series of flight tests is described that make use of a small electric powered unmanned aerial vehicle (eUAV) to verify the performance of the remaining flying time prediction algorithm. The estimate of remaining flying time is used to activate an alarm when the predicted remaining time is two minutes. This notifies the pilot to transition to the landing phase of the flight. A second alarm is activated when the battery charge falls below a specified limit threshold. This threshold is the point at which the battery energy reserve would no longer safely support two repeated aborted landing attempts. During the test series, the motor system is operated with the same predefined timed airspeed profile for each test. To test the robustness of the prediction, half of the tests were performed with, and half were performed without, a simulated powertrain fault. The pilot remotely engages a resistor bank at a specified time during the test flight to simulate a partial powertrain fault. The flying time prediction system is agnostic of the pilot's activation of the fault and must adapt to the vehicle's state. The time at which the limit threshold on battery charge is reached is then used to measure the accuracy of the remaining flying time predictions. Accuracy requirements for the alarms are considered and the results discussed

Variables associated with nest survival of Golden-winged Warblers (Vermivora chrysoptera) among vegetation communities commonly used for nesting

Among shrubland- and young forest-nesting bird species in North America, Golden-winged Warblers (Vermivora chrysoptera) are one of the most rapidly declining partly because of limited nesting habitat. Creation and management of high quality vegetation communities used for nesting are needed to reduce declines. Thus, we examined whether common characteristics could be managed across much of the Golden-winged Warbler’s breeding range to increase daily survival rate (DSR) of nests. We monitored 388 nests on 62 sites throughout Minnesota, Wisconsin, New York, North Carolina, Pennsylvania, Tennessee, and West Virginia. We evaluated competing DSR models in spatial-temporal (dominant vegetation type, population segment, state, and year), intraseasonal (nest stage and time-within-season), and vegetation model suites. The best-supported DSR models among the three model suites suggested potential associations between daily survival rate of nests and state, time-within-season, percent grass and Rubus cover within 1 m of the nest, and distance to later successional forest edge. Overall, grass cover (negative association with DSR above 50%) and Rubus cover (DSR lowest at about 30%) within 1 m of the nest and distance to later successional forest edge (negative association with DSR) may represent common management targets across our states for increasing Golden-winged Warbler DSR, particularly in the Appalachian Mountains population segment. Context-specific adjustments to management strategies, such as in wetlands or areas of overlap with Blue-winged Warblers (Vermivora cyanoptera), may be necessary to increase DSR for Golden-winged Warblers

Verification of Prognostic Algorithms to Predict Remaining Flying Time for Electric Unmanned Vehicles

This paper addresses the problem of building trust in the online prediction of a eUAV’s remaining available flying time powered by lithium-ion polymer batteries. A series of ground tests are described that make use of an electric unmanned aerial vehicle (eUAV) to verify the performance of remaining flying time predictions. The algorithm verification procedure described is implemented on a fully functional vehicle that is restrained to a platform for repeated run-to-functional-failure (charge depletion) experiments. The vehicle under test is commanded to follow a predefined propeller RPM profile in order to create battery demand profiles similar to those expected during flight. The eUAV is repeatedly operated until the charge stored in powertrain batteries falls below a specified limit threshold. The time at which the limit threshold on battery charge is crossed is then used to measure the accuracy of the remaining flying time prediction. In our earlier work battery aging was not included. In this work we take into account aging of the batteries where the parameters were updated to make predictions. Accuracy requirements are considered for an alarm that warns operators when remaining flying time is estimated to fall below the specified limit threshold

Variables associated with nest survival of Golden-winged Warblers (Vermivora Chrysoptera) among vegetation communities commonly used for nesting

Among shrubland-and young forest-nesting bird species in North America, Golden-winged Warblers (Vermivora chrysoptera) are one of the most rapidly declining partly because of limited nesting habitat. Creation and management of high quality vegetation communities used for nesting are needed to reduce declines. Thus, we examined whether common characteristics could be managed across much of the Golden-winged Warbler’s breeding range to increase daily survival rate (DSR) of nests. We monitored 388 nests on 62 sites throughout Minnesota, Wisconsin, New York, North Carolina, Pennsylvania, Tennessee, and West Virginia. We evaluated competing DSR models in spatial-temporal (dominant vegetation type, population segment, state, and year), intraseasonal (nest stage and time-within-season), and vegetation model suites. The best-supported DSR models among the three model suites suggested potential associations between daily survival rate of nests and state, time-within-season, percent grass and Rubus cover within 1 m of the nest, and distance to later successional forest edge. Overall, grass cover (negative association with DSR above 50%) and Rubus cover (DSR lowest at about 30%) within 1 m of the nest and distance to later successional forest edge (negative association with DSR) may represent common management targets across our states for increasing Golden-winged Warbler DSR, particularly in the Appalachian Mountains population segment. Context-specific adjustments to management strategies, such as in wetlands or areas of overlap with Blue-winged Warblers (Vermivora cyanoptera), may be necessary to increase DSR for Golden-winged Warblers

Variables associated with nest survival of Golden-winged Warblers (Vermivora Chrysoptera) among vegetation communities commonly used for nesting

Among shrubland-and young forest-nesting bird species in North America, Golden-winged Warblers (Vermivora chrysoptera) are one of the most rapidly declining partly because of limited nesting habitat. Creation and management of high quality vegetation communities used for nesting are needed to reduce declines. Thus, we examined whether common characteristics could be managed across much of the Golden-winged Warbler’s breeding range to increase daily survival rate (DSR) of nests. We monitored 388 nests on 62 sites throughout Minnesota, Wisconsin, New York, North Carolina, Pennsylvania, Tennessee, and West Virginia. We evaluated competing DSR models in spatial-temporal (dominant vegetation type, population segment, state, and year), intraseasonal (nest stage and time-within-season), and vegetation model suites. The best-supported DSR models among the three model suites suggested potential associations between daily survival rate of nests and state, time-within-season, percent grass and Rubus cover within 1 m of the nest, and distance to later successional forest edge. Overall, grass cover (negative association with DSR above 50%) and Rubus cover (DSR lowest at about 30%) within 1 m of the nest and distance to later successional forest edge (negative association with DSR) may represent common management targets across our states for increasing Golden-winged Warbler DSR, particularly in the Appalachian Mountains population segment. Context-specific adjustments to management strategies, such as in wetlands or areas of overlap with Blue-winged Warblers (Vermivora cyanoptera), may be necessary to increase DSR for Golden-winged Warblers

Data from range-wide study of migratory connectivity of Vermivora warblers

See ReadMe.txt for detailed description of files.This collection of files provide data from a range-wide study of the migratory ecology of Vermivora warblers. Data include raw light-level data from geolocators, R code, and associated output. These data can be used to recreate analyses including: (1) Individual nonbreeding occurrence and population-level nonbreeding overlap (2) Individual migration routes and spatial distribution of individuals and populations during migrationU.S. Fish and Wildlife ServiceU.S Geological SurveyMinnesota Cooperative Fish and Wildlife Research UnitNational Science FoundationVirginia Department of Game and Inland FisheriesGrace Jones Richardson Trus