scholarly journals GPS/Reduced IMU with a Local Terrain Predictor in Land Vehicle Navigation

2008 ◽  
Vol 2008 ◽  
pp. 1-15 ◽  
Author(s):  
Debo Sun ◽  
Mark G. Petovello ◽  
M. Elizabeth Cannon
Keyword(s):  
Global Positioning System ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Vehicle Navigation ◽  
Test Results ◽  
Inertial Measurement ◽  
Land Vehicle ◽  
Land Vehicle Navigation ◽  
Global Positioning ◽  
The Cost

In order to reduce the cost and volume of land vehicle navigation (LVN) systems, a “reduced” inertial measurement unit (IMU) consisting of only one vertical gyro and two or three accelerometers is generally used and is often integrated with other sensors. Since there are no horizontal gyros in a reduced IMU, the pitch and roll cannot be calculated or observed directly from the inertial data, and the navigation performance is thus affected by local terrain variations. In this work, a reduced IMU is integrated with global positioning system (GPS) data and a novel local terrain predictor (LTP) algorithm. The latter is used primarily to help estimate the pitch and roll of the reduced IMU system and thus to improve the navigation performance. In this paper, two reduced IMU configurations and two grades of IMUs are investigated using field data. Test results show that the LTP is valid. Specifically, inclusion of the LTP provides more than an 80% horizontal velocity improvement relative to the case when the LTP is not used in a GPS/reduced IMU configuration.

scholarly journals Soaring energetics and glide performance in a moving atmosphere

2016 ◽  
Vol 371 (1704) ◽  
pp. 20150398 ◽  
Author(s):  
Graham K. Taylor ◽  
Kate V. Reynolds ◽  
Adrian L. R. Thomas
Keyword(s):  
Global Positioning System ◽  
Inertial Measurement Unit ◽  
Mechanical Energy ◽  
Measurement Unit ◽  
Cost Of Transport ◽  
Inertial Measurement ◽  
Dynamic Soaring ◽  
Energy Flows ◽  
Weak Evidence ◽  
Global Positioning

Here, we analyse the energetics, performance and optimization of flight in a moving atmosphere. We begin by deriving a succinct expression describing all of the mechanical energy flows associated with gliding, dynamic soaring and thermal soaring, which we use to explore the optimization of gliding in an arbitrary wind. We use this optimization to revisit the classical theory of the glide polar, which we expand upon in two significant ways. First, we compare the predictions of the glide polar for different species under the various published models. Second, we derive a glide optimization chart that maps every combination of headwind and updraft speed to the unique combination of airspeed and inertial sink rate at which the aerodynamic cost of transport is expected to be minimized. With these theoretical tools in hand, we test their predictions using empirical data collected from a captive steppe eagle ( Aquila nipalensis ) carrying an inertial measurement unit, global positioning system, barometer and pitot tube. We show that the bird adjusts airspeed in relation to headwind speed as expected if it were seeking to minimize its aerodynamic cost of transport, but find only weak evidence to suggest that it adjusts airspeed similarly in response to updrafts during straight and interthermal glides. This article is part of the themed issue ‘Moving in a moving medium: new perspectives on flight’.

Cartesian Control for the Inertial Measurement Unit Calibration Platform

2000 ◽  
Author(s):  
John J. Hall ◽  
Robert L. Williams ◽  
Frank van Graas
Keyword(s):  
Global Positioning System ◽  
Inertial Measurement Unit ◽  
Vertical Motion ◽  
High Accuracy ◽  
Measurement Unit ◽  
Positioning System ◽  
Ohio University ◽  
Inertial Measurement ◽  
Gps Technology ◽  
Global Positioning

Abstract The Department of Mechanical Engineering and the Avionics Engineering Center at Ohio University are developing an electromechanical system for the calibration of an inertial measurement unit (IMU) using global positioning system (GPS) antennas. The GPS antennas and IMU are mounted to a common platform to be oriented in the angular roll, pitch, and yaw motions. Vertical motion is also included to test the systems in a vibrational manner. A four-dof system based on the parallel Carpal Wrist is under development for this task. High-accuracy positioning is not required from the platform since the GPS technology provides absolute positioning for the IMU calibration process.

An autonomous rice transplanter guided by global positioning system and inertial measurement unit

2009 ◽  
Vol 26 (6-7) ◽  
pp. 537-548 ◽  
Author(s):  
Yoshisada Nagasaka ◽  
Hidefumi Saito ◽  
Katsuhiko Tamaki ◽  
Masahiro Seki ◽  
Kyo Kobayashi ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Positioning System ◽  
Inertial Measurement ◽  
Global Positioning

scholarly journals Vehicle location measurement method for radio-shadow area through iBeacon message

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881257
Author(s):  
ChoonSung Nam ◽  
Dong-Ryeol Shin
Keyword(s):  
Global Positioning System ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Positioning System ◽  
Inertial Measurement ◽  
Location Data ◽  
Shadow Area ◽  
Global Positioning ◽  
Vehicle Location ◽  
Roadside Unit

Information communication technology related vehicle services need to support location and the transmission of communication and traffic information between vehicles, or between vehicles and infrastructure. In particular, the technology for the measurement of the accurate location of a vehicle is dependent on location-determination technology like Global Positioning System, and this technology is very important for vehicle driving and location services. If, however, a vehicle is in a Global Positioning System radio-shadow area, neither a Global Positioning System nor a Differential Global Positioning System can accurately measure the corresponding location because of a high error rate caused by the shadowing intervention. Even an Inertial Measurement Unit could provide inaccurate location data due to sensor drift faults around corners and traffic-road speed dumps. Vehicles, therefore, need an absolute location to prevent the provision of inaccurate vehicle-location data that is due to radio-shadow areas and relational Inertial Measurement Unit positions. To achieve this, we assume that vehicle-to-infrastructure communication is possible between a vehicle and roadside unit in Vehicular Ad hoc Networks. We used iBeacon at the roadside unit and revised its Universally Unique Identifier so that it generates absolute Global Positioning System location data; that is, moving vehicles can receive absolute Global Positioning System data from the roadside unit-based iBeacon. We compared the proposed method with current Global Positioning System and Inertial Measurement Unit systems for the following two cases: one with a radio-shadow area and one without. We proved that the proposed method generates location data that are more accurate than those of the other methods.

Three-Axis Gimbal Surveillance Algorithms for Use in Small UAS

2008 ◽  
Author(s):  
Jaganathan Ranganathan ◽  
William H. Semke
Keyword(s):  
Coordinate System ◽  
Global Positioning System ◽  
Inertial Measurement Unit ◽  
Target Location ◽  
Measurement Unit ◽  
Positioning System ◽  
Inertial Measurement ◽  
University Of North Dakota ◽  
Global Positioning ◽  
Accurate Position

An active three-axis gimbal system is developed to allow small fixed wing Unmanned Aircraft Systems (UAS) platforms to estimate accurate position information by pointing at a target and also to track a known target location. Specific targets vary from a stationary point on the ground to aircraft in the national airspace. The payload developed to accomplish this at the University of North Dakota is the Surveillance by University of North Dakota Observational Gimbal (SUNDOG). This paper will focus on a novel, nonlinear closed form analytical algorithm developed to calculate the exact rotation angles for a three-axis gimbal system to point a digital imaging sensor at a target, as well as how to estimate accurate position of a target by using the pointing angles of a three-axis gimbal system. A kinematic analysis is done on a three-axis gimbal system to get the appropriate model of gimbal rotations in order to point at a certain location on the ground. The mathematical model includes an inertial coordinate system that has coordinates fixed to the Earth, a coordinate system that is body-fixed to the aircraft, and a third coordinate system that is fixed to the gimbal. Therefore, multiple three-dimensional transformations are required to accurately provide the necessary pointing angles to the gimbal system. The autonomous control system uses Global Positioning System (GPS), Inertial Measurement Unit (IMU), and other sensor data to estimate position and attitude during flight. Since the algorithm is entirely based on Inertial Measurement Unit (IMU) and Global Positioning System (GPS) device inputs, any error from these devices cause offset in the target location. Hence, an error analysis is carried out to find the offset distance and the operating range of the algorithm. The main advantage obtained in the three-axis gimbal system is that the orientation of the image will always be aligned in a specified direction for effective interpretation. The closed form expressions to the non-linear transformations provide simple solutions easily programmed without large computational expense. Experimental work will be carried out in a controlled environment and in flight testing to show the autonomous tracking ability of the gimbal system. Simulation and experimental data illustrating the effectiveness of the surveillance algorithms is presented.

scholarly journals The Visual–Inertial Canoe Dataset

2018 ◽  
Vol 37 (1) ◽  
pp. 13-20 ◽  
Author(s):  
Martin Miller ◽  
Soon-Jo Chung ◽  
Seth Hutchinson
Keyword(s):  
Global Positioning System ◽  
Inertial Measurement Unit ◽  
Ground Truth ◽  
Data Bank ◽  
Measurement Unit ◽  
Round Trip ◽  
Inertial Measurement ◽  
Global Positioning ◽  
Position Data ◽  
Inertial Measurements

We present a dataset collected from a canoe along the Sangamon River in Illinois. The canoe was equipped with a stereo camera, an inertial measurement unit (IMU), and a global positioning system (GPS) device, which provide visual data suitable for stereo or monocular applications, inertial measurements, and position data for ground truth. We recorded a canoe trip up and down the river for 44 minutes covering a 2.7 km round trip. The dataset adds to those previously recorded in unstructured environments and is unique in that it is recorded on a river, which provides its own set of challenges and constraints that are described in this paper. The dataset is stored on the Illinois Data Bank and can be accessed at: https://doi.org/10.13012/B2IDB-9342111_V1 .

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