50,181 research outputs found
Recommended from our members
The GPS Assimilator: a Method for Upgrading Existing GPS User Equipment to Improve Accuracy, Robustness, and Resistance to Spoofing
Preprint of the 2010 ION GNSS Conference
Portland, OR, September 21–24, 2010A conceptual method is presented for upgrading existing GPS user equipment, without requiring hardware or software modifications to the equipment, to improve the equipment’s position, velocity, and time (PVT) accuracy, to increase its PVT robustness in weak-signal or jammed environments, and to protect the equipment from counterfeit GPS signals (GPS spoofing). The method is embodied in a device called the GPS Assimilator that couples to the radio frequency (RF) input of an existing GPS receiver. The Assimilator extracts navigation and timing information from RF signals in its environment—including non-GNSS signals—and from direct baseband aiding provided, for example, by an inertial navigation system, a
frequency reference, or the GPS user. The Assimilator optimally fuses the collective navigation and timing information to produce a PVT solution which, by virtue of the diverse navigation and timing sources on which it is based, is highly accurate and inherently robust to GPS signal obstruction and jamming. The Assimilator embeds the PVT solution in a synthesized set of GPS signals and injects
these into the RF input of a target GPS receiver for which an accurate and robust PVT solution is desired. A prototype software-defined Assimilator device is presented with three example applications.Aerospace Engineerin
An open environment CT-US fusion for tissue segmentation during interventional guidance.
Therapeutic ultrasound (US) can be noninvasively focused to activate drugs, ablate tumors and deliver drugs beyond the blood brain barrier. However, well-controlled guidance of US therapy requires fusion with a navigational modality, such as magnetic resonance imaging (MRI) or X-ray computed tomography (CT). Here, we developed and validated tissue characterization using a fusion between US and CT. The performance of the CT/US fusion was quantified by the calibration error, target registration error and fiducial registration error. Met-1 tumors in the fat pads of 12 female FVB mice provided a model of developing breast cancer with which to evaluate CT-based tissue segmentation. Hounsfield units (HU) within the tumor and surrounding fat pad were quantified, validated with histology and segmented for parametric analysis (fat: -300 to 0 HU, protein-rich: 1 to 300 HU, and bone: HU>300). Our open source CT/US fusion system differentiated soft tissue, bone and fat with a spatial accuracy of ∼1 mm. Region of interest (ROI) analysis of the tumor and surrounding fat pad using a 1 mm(2) ROI resulted in mean HU of 68±44 within the tumor and -97±52 within the fat pad adjacent to the tumor (p<0.005). The tumor area measured by CT and histology was correlated (r(2) = 0.92), while the area designated as fat decreased with increasing tumor size (r(2) = 0.51). Analysis of CT and histology images of the tumor and surrounding fat pad revealed an average percentage of fat of 65.3% vs. 75.2%, 36.5% vs. 48.4%, and 31.6% vs. 38.5% for tumors <75 mm(3), 75-150 mm(3) and >150 mm(3), respectively. Further, CT mapped bone-soft tissue interfaces near the acoustic beam during real-time imaging. Combined CT/US is a feasible method for guiding interventions by tracking the acoustic focus within a pre-acquired CT image volume and characterizing tissues proximal to and surrounding the acoustic focus
A Sliding Mode Multimodel Control for a Sensorless Photovoltaic System
In this work we will talk about a new control test using the sliding mode
control with a nonlinear sliding mode observer, which are very solicited in
tracking problems, for a sensorless photovoltaic panel. In this case, the panel
system will has as a set point the sun position at every second during the day
for a period of five years; then the tracker, using sliding mode multimodel
controller and a sliding mode observer, will track these positions to make the
sunrays orthogonal to the photovoltaic cell that produces more energy. After
sunset, the tracker goes back to the initial position (which of sunrise).
Experimental measurements show that this autonomic dual axis Sun Tracker
increases the power production by over 40%
Nonuniform Dual-Rate Extended Kalman-Filter-Based Sensor Fusion for Path-Following Control of a Holonomic Mobile Robot with Four Mecanum Wheels
[EN] This paper presents an extended Kalman-filter-based sensor fusion approach, which enables path-following control of a holonomic mobile robot with four mecanum wheels. Output measurements of the mobile platform may be sensed at different rates: odometry and orientation data can be obtained at a fast rate, whereas position information may be generated at a slower rate. In addition, as a consequence of possible sensor failures or the use of lossy wireless sensor networks, the presence of the measurements may be nonuniform. These issues may degrade the path-following control performance. The consideration of a nonuniform dual-rate extended Kalman filter (NUDREKF) enables us to estimate fast-rate robot states from nonuniform, slow-rate measurements. Providing these estimations to the motion controller, a fast-rate control signal can be generated, reaching a satisfactory path-following behavior. The proposed NUDREKF is stated to represent any possible sampling pattern by means of a diagonal matrix, which is updated at a fast rate from the current, existing measurements. This fact results in a flexible formulation and a straightforward algorithmic implementation. A modified Pure Pursuit path-tracking algorithm is used, where the reference linear velocity is decomposed into Cartesian components, which are parameterized by a variable gain that depends on the distance to the target point. The proposed solution was evaluated using a realistic simulation model, developed with Simscape Multibody (Matlab/Simulink), of the four-mecanum-wheeled mobile platform. This model includes some of the nonlinearities present in a real vehicle, such as dead-zone, saturation, encoder resolution, and wheel sliding, and was validated by comparing real and simulated behavior. Comparison results reveal the superiority of the sensor fusion proposal under the presence of nonuniform, slow-rate measurements.Grant RTI2018-096590-B-I00 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe" and Grant PRE2019-088467 funded by MCIN/AEI/10.13039/501100011033 and by "ESF Investing in your future".Pizá, R.; Carbonell-Lázaro, R.; Casanova Calvo, V.; Cuenca, Á.; Salt Llobregat, JJ. (2022). Nonuniform Dual-Rate Extended Kalman-Filter-Based Sensor Fusion for Path-Following Control of a Holonomic Mobile Robot with Four Mecanum Wheels. Applied Sciences. 12(7):1-23. https://doi.org/10.3390/app1207356012312
Cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging
The implementation challenges of cooperative localization by dual
foot-mounted inertial sensors and inter-agent ranging are discussed and work on
the subject is reviewed. System architecture and sensor fusion are identified
as key challenges. A partially decentralized system architecture based on
step-wise inertial navigation and step-wise dead reckoning is presented. This
architecture is argued to reduce the computational cost and required
communication bandwidth by around two orders of magnitude while only giving
negligible information loss in comparison with a naive centralized
implementation. This makes a joint global state estimation feasible for up to a
platoon-sized group of agents. Furthermore, robust and low-cost sensor fusion
for the considered setup, based on state space transformation and
marginalization, is presented. The transformation and marginalization are used
to give the necessary flexibility for presented sampling based updates for the
inter-agent ranging and ranging free fusion of the two feet of an individual
agent. Finally, characteristics of the suggested implementation are
demonstrated with simulations and a real-time system implementation.Comment: 14 page
- …