A New Method to Reduce Truncation Errors in Partial Spherical Near-Field Measurements

A new and effective method for reduction of truncation errors in partial spherical near-field (SNF) measurements is proposed. The method is useful when measuring electrically large antennas, where the measurement time with the classical SNF technique is prohibitively long and an acquisition over the whole spherical surface is not practical. Therefore, to reduce the data acquisition time, partial sphere measurement is usually made, taking samples over a portion of the spherical surface in the direction of the main beam. But in this case, the radiation pattern is not known outside the measured angular sector as well as a truncation error is present in the calculated far-field pattern within this sector. The method is based on the Gerchberg-Papoulis algorithm used to extrapolate functions and it is able to extend the valid region of the calculated far-field pattern up to the whole forward hemisphere. To verify the effectiveness of the method, several examples are presented using both simulated and measured truncated near-field data.

New methods to reduce leakage errors in planar near-field measurements

This paper describes two methods to cancel the effect of two kinds of leakage signals which may be presented when an antenna is measured in a planar near-field range. One method tries to reduce leakage bias errors from the receiver¿s quadrature detector and it is based on estimating the bias constant added to every near-field data sample. Then, that constant is subtracted from the data, removing its undesired effect on the far-field pattern. The estimation is performed by back-propagating the field from the scan plane to the antenna under test plane (AUT) and averaging all the data located outside the AUT aperture. The second method is able to cancel the effect of the leakage from faulty transmission lines, connectors or rotary joints. The basis of this method is also a reconstruction process to determine the field distribution on the AUT plane. Once this distribution is known, a spatial filtering is applied to cancel the contribution due to those faulty elements. After that, a near-field-to-far-field transformation is applied, obtaining a new radiation pattern where the leakage effects have disappeared. To verify the effectiveness of both methods, several examples are presented.

Tracking and back-tracking

This paper presents a review of back-tracking geometry not only for single axis but also for two-axis tracking and analyses the corresponding energy gains. It compares the different back-tracking strategies with the ideal tracking in terms of energy yield concluding, on the one hand, that back-tracking is more useful for single horizontal axis than for the single vertical one, and on the other hand, that back-tracking is more efficient when applied in the primary axis of a two-axis tracker

Particle filtering for indoor RFID tag tracking

In this paper, we propose a particle filtering (PF) method for indoor tracking using radio frequency identification (RFID) based on aggregated binary measurements. We use an Ultra High Frequency (UHF) RFID system that is composed of a standard RFID reader, a large set of standard passive tags whose locations are known, and a newly designed, special semi-passive tag attached to an object that is tracked. This semi-passive tag has the dual ability to sense the backscatter communication between the reader and other passive tags which are in its proximity and to communicate this sensed information to the reader using backscatter modulation. We refer to this tag as a sense-a-tag (ST). Thus, the ST can provide the reader with information that can be used to determine the kinematic parameters of the object on which the ST is attached. We demonstrate the performance of the method with data obtained in a laboratory environment.

Detection and Tracking of Traffic Signs Using a Recursive Bayesian Decision Framework

In this paper we propose a new method for the automatic detection and tracking of road traffic signs using an on-board single camera. This method aims to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. The proposed approach exploits a combination of different features, such as color, appearance, and tracking information. This information is introduced into a recursive Bayesian decision framework, in which prior probabilities are dynamically adapted to tracking results. This decision scheme obtains a number of candidate regions in the image, according to their HS (Hue-Saturation). Finally, a Kalman filter with an adaptive noise tuning provides the required time and spatial coherence to the estimates. Results have shown that the proposed method achieves high detection rates in challenging scenarios, including illumination changes, rapid motion and significant perspective distortion

Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling

Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.

Subjective Evaluation of Transmission Errors in IPTV and 3DTV

The increase of multimedia services delivered over packet-based networks has entailed greater quality expectations of the end-users. This has led to an intensive research on techniques for evaluating the quality of experience perceived by the viewers of audiovisual content, considering the different degradations that it could suffer along the broadcasting system. In this paper, a comprehensive study of the impact of transmission errors affecting video and audio in IPTV is presented. With this aim, subjective assessment tests were carried out proposing a novel methodology trying to keep as close as possible home environment viewing conditions. Also 3DTV content in side-by-side format has been used in the experiments to compare the impact of the degradations. The results provide a better understanding of the effects of transmission errors, and show that the QoE related to the first approach of 3DTV is acceptable, but the visual discomfort that it causes should be reduced.

Subjective assessment of the impact of transmission errors in 3DTV compared to HDTV

Recently, broadcasted 3D video content has reached households with the first generation of 3DTV. However, few studies have been done to analyze the Quality of Experience (QoE) perceived by the end-users in this scenario. This paper studies the impact of trans- mission errors in 3DTV, considering that the video is delivered in side-by-side format over a conventional packet-based network. For this purpose, a novel evaluation methodology based on standard sin- gle stimulus methods and with the aim of keeping as close as pos- sible the home environment viewing conditions has been proposed. The effects of packet losses in monoscopic and stereoscopic videos are compared from the results of subjective assessment tests. Other aspects were also measured concerning 3D content as naturalness, sense of presence and visual fatigue. The results show that although the final perceived QoE is acceptable, some errors cause important binocular rivalry, and therefore, substantial visual discomfort.

IDT-3D: Identification and tracking in controlled environments using a 3D unified user interface

Identification and tracking of objects in specific environments such as harbors or security areas is a matter of great importance nowadays. With this purpose, numerous systems based on different technologies have been developed, resulting in a great amount of gathered data displayed through a variety of interfaces. Such amount of information has to be evaluated by human operators in order to take the correct decisions, sometimes under highly critical situations demanding both speed and accuracy. In order to face this problem we describe IDT-3D, a platform for identification and tracking of vessels in a harbour environment able to represent fused information in real time using a Virtual Reality application. The effectiveness of using IDT-3D as an integrated surveillance system is currently under evaluation. Preliminary results point to a significant decrease in the times of reaction and decision making of operators facing up a critical situation. Although the current application focus of IDT-3D is quite specific, the results of this research could be extended to the identification and tracking of targets in other controlled environments of interest as coastlines, borders or even urban areas.

Integrating tracking in concentrating photovoltaics using laterally moving optics

In this work the concept of integrating tracking in concentrating photovoltaics is briefly summarized and possible fields of application are classified. A previously proposed system setup relies on the use of two rotational symmetric laterally moving plano-convex lenses to achieve 500× concentration over an angular range of ±24 ◦ . However, the circular lens apertures are less suitable for application in lens array structures. A new design algorithm based on the Simultaneous Multiple Surface algorithm in three dimensions (SMS3D) demonstrates the ability to address this problem. Performance simulations show that the resulting non-rotational symmetric design outperforms its conventional rotational symmetric counterpart

A method for Kinematic Calibration of a Parallel Robot by using one camera in hand and a spherical object

The main purpose of robot calibration is the correction of the possible errors in the robot parameters. This paper presents a method for a kinematic calibration of a parallel robot that is equipped with one camera in hand. In order to preserve the mechanical configuration of the robot, the camera is utilized to acquire incremental positions of the end effector from a spherical object that is fixed in the word reference frame. The positions of the end effector are related to incremental positions of resolvers of the motors of the robot, and a kinematic model of the robot is used to find a new group of parameters which minimizes errors in the kinematic equations. Additionally, properties of the spherical object and intrinsic camera parameters are utilized to model the projection of the object in the image and improving spatial measurements. Finally, the robotic system is designed to carry out tracking tasks and the calibration of the robot is validated by means of integrating the errors of the visual controller.

Improved Animal Tracking Algorithm using Distributed Kalman Filter-based Algortihms

Animal tracking has been addressed by different initiatives over the last two decades. Most of them rely on satellite connectivity on every single node and lack of energy-saving strategies. This paper presents several new contributions on the tracking of dynamic heterogeneous asynchronous networks (primary nodes with GPS and secondary nodes with a kinetic generator) motivated by the animal tracking paradigm with random transmissions. A simple approach based on connectivity and coverage intersection is compared with more sophisticated algorithms based on ad-hoc implementations of distributed Kalman-based filters that integrate measurement information using Consensus principles in order to provide enhanced accuracy. Several simulations varying the coverage range, the random behavior of the kinetic generator (modeled as a Poisson Process) and the periodic activation of GPS are included. In addition, this study is enhanced with HW developments and implementations on commercial off-the-shelf equipment which show the feasibility for performing these proposals on real hardware.

High efficiency envelope tracking buck converter for RFPA using GaN HEMTs

—In this paper, application of a new technological solution for power switches based on Gallium Nitride and a filter design methodology for high efficiency Envelope Amplifier in RF transmitters are proposed. Comparing to Si MOSFETs, GaN HEMTs can provide higher efficiency of the Envelope Amplifier, due to better Figure Of Merit (lower product of on- resistance and gate charge). Benefits of their application were verified through the experimental results. The goal of the filter design is to generate the envelope reference with the minimum possible distortion and to improve the efficiency of the Amplifier, obtaining the optimum trade-off between conduction and switching losses.

Optimum Design of an Envelope Tracking Buck Converter for RF PA using GaN HEMTs

In this paper, filter design methodology and application of GaN HEMTs for high efficiency Envelope Amplifier in RF transmitters are proposed. The main objectives of the filter design are generation of the envelope reference with the minimum possible distortion and high efficiency of the amplifier obtained by the optimum trade-off between conduction and switching losses. This optimum point was determined using power losses model for synchronous buck with sinusoidal output voltage and experimental results showed good correspondence with the model and verified the proposed methodology. On the other hand, comparing to Si MOSFETs, GaN HEMTs can provide higher efficiency of the envelope amplifier, due to superior conductivity and switching characteristics. Experimental results verified benefits of GaN devices comparing to the appliance of Si switching devices with very good Figure Of Merit, for this particular application

An Efficient Multiple Object Detection and Tracking Framework for Automatic Counting and Video Surveillance Applications

Automatic visual object counting and video surveillance have important applications for home and business environments, such as security and management of access points. However, in order to obtain a satisfactory performance these technologies need professional and expensive hardware, complex installations and setups, and the supervision of qualified workers. In this paper, an efficient visual detection and tracking framework is proposed for the tasks of object counting and surveillance, which meets the requirements of the consumer electronics: off-the-shelf equipment, easy installation and configuration, and unsupervised working conditions. This is accomplished by a novel Bayesian tracking model that can manage multimodal distributions without explicitly computing the association between tracked objects and detections. In addition, it is robust to erroneous, distorted and missing detections. The proposed algorithm is compared with a recent work, also focused on consumer electronics, proving its superior performance.