986 resultados para Tracking performance


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This paper outlines an innovative and feasible flight control scheme for a rotary-wing unmanned aerial system (RUAS) with guaranteed safety and reliable flight quality in a gusty environment. The proposed control methodology aims to increase gust-attenuation capability of a RUAS to ensure improved flight performance when strong gusts occur. Based on the design of an effective estimator, an altitude controller is firstly constructed to synchronously compensate for fluctuations of the main rotor thrust which might lead to crashes in a gusty environment. Afterwards, a nonlinear state feedback controller is proposed to stabilize horizontal positions of the RUAS with gust-attenuation property. Performance of the proposed control framework is evaluated using parameters of a Vario XLC helicopter and high-fidelity simulations show that the proposed controllers can effectively reduce side-effect of gusts and demonstrate performance improvement when compared with the proportional-integral-derivative (PID) controllers.

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The paper presents a new approach to improve the detection and tracking performance of a track-while-scan (TWS) radar. The contribution consists of three parts. In Part 1 the scope of various papers in this field is reviewed. In Part 2, a new approach for integrating the detection and tracking functions is presented. It shows how a priori information from the TWS computer can be used to improve detection. A new multitarget tracking algorithm has also been developed. It is specifically oriented towards solving the combinatorial problems in multitarget tracking. In Part 3, analytical derivations are presented for quantitatively assessing, a priori, the performance of a track-while-scan radar system (true track initiation, false track initiation, true track continuation and false track deletion characteristics). Simulation results are also shown.

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The paper presents, in three parts, a new approach to improve the detection and tracking performance of a track-while-scan radar. Part 1 presents a review of the current status of the subject. Part 2 details the new approach. It shows how a priori information provided by the tracker can be used to improve detection. It also presents a new multitarget tracking algorithm. In the present Part, analytical derivations are presented for assessing, a priori, the performance of the TWS radar system. True track initiation, false track initiation, true track continuation and false track deletion characteristics have been studied. It indicates how the various thresholds can be chosen by the designer to optimise performance. Simulation results are also presented.

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he paper presents, in three parts, a new approach to improve the detection and tracking performance of a track-while-scan (TWS) radar. Part 1 presents a review of current status. In this part, Part 2, it is shown how the detection can be improved by utilising information from tracker. A new multitarget tracking algorithm, capable of tracking manoeuvring targets in clutter, is then presented. The algorithm is specifically tailored so that the solution to the combinatorial problem presented in a companion paper can be applied. The implementation aspects are discussed and a multiprocessor architecture identified to realise the full potential of the algorithm. Part 3 presents analytical derivations for quantitative assessment of the performance of the TWS radar system. It also shows how the performance can be optimised.

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We consider a time varying wireless fading channel, equalized by an LMS linear equalizer. We study how well this equalizer tracks the optimal Wiener equalizer. We model the channel by an Auto-regressive (AR) process. Then the LMS equalizer and the AR process are jointly approximated by the solution of a system of ODEs (ordinary differential equations). Using these ODEs, the error between the LMS equalizer and the instantaneous Wiener filter is shown to decay exponentially/polynomially to zero unless the channel is marginally stable in which case the convergence may not hold.Using the same ODEs, we also show that the corresponding Mean Square Error (MSE) converges towards minimum MSE(MMSE) at the same rate for a stable channel. We further show that the difference between the MSE and the MMSE does not explode with time even when the channel is unstable. Finally we obtain an optimum step size for the linear equalizer in terms of the AR parameters, whenever the error decay is exponential.

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Autonomous underwater vehicles (AUV’s) are increasingly used to collect physical, chemical, and biological information in the marine environment. Recent efforts include merging AUV technology with acoustic telemetry to provide information on the distribution and movements of marine fish. We compared surface vessel and AUV tracking capabilities under rigorous conditions in coastal waters near Juneau, Alaska. Tracking surveys were conducted with a REMUS 100 AUV equipped with an integrated acoustic receiver and hydrophone. The AUV was programmed to navigate along predetermined routes to detect both reference transmitters at 20–500 m depths and tagged fish and crabs in situ. Comparable boat surveys were also conducted. Transmitter depth had a major impact on tracking performance. The AUV was equally effective or better than the boat at detecting reference transmitters in shallow water, and significantly better for transmitters at deeper depths. Similar results were observed for tagged animals. Red king crab, Paralithodes camtschaticus, at moderate depths were recorded by both tracking methods, while only the AUV detected Sablefish, Anoplopoma fimbria, at depths exceeding 500 m. Strong currents and deep depths caused problems with AUV navigation, position estimation, and operational performance, but reflect problems encountered by other AUV applications that will likely diminish with future advances, enhanced methods, and increased use.

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This paper presents a quantitative evaluation of a tracking system on PETS 2015 Challenge datasets using well-established performance measures. Using the existing tools, the tracking system implements an end-to-end pipeline that include object detection, tracking and post- processing stages. The evaluation results are presented on the provided sequences of both ARENA and P5 datasets of PETS 2015 Challenge. The results show an encouraging performance of the tracker in terms of accuracy but a greater tendency of being prone to cardinality error and ID changes on both datasets. Moreover, the analysis show a better performance of the tracker on visible imagery than on thermal imagery.

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This paper presents object tracking in depth, RGB and normal-maps images using LGT tracker. The depth and RGB images are rendered using depth imaging plugins. A series of experiments were held to evaluate the tracker performance in tracking objects in different image sequences. The experiments conducted were from the Visual Object Tracking (VOT) challenge that was arranged in association with ICCV'13 The accuracy was chosen as the evaluation measure, where the the tracker's bounding box was compared against the ground truth bounding box. Results show that tracking object using depth images gives better results and is more accurate than tracking using either the RGB or nomal maps images.

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The first LHC pp collisions at centre-of-mass energies of 0.9 and 2.36 TeV were recorded by the CMS detector in December 2009. The trajectories of charged particles produced in the collisions were reconstructed using the all-silicon Tracker and their momenta were measured in the 3.8 T axial magnetic field. Results from the Tracker commissioning are presented including studies of timing, efficiency, signal-to-noise, resolution, and ionization energy. Reconstructed tracks are used to benchmark the performance in terms of track and vertex resolutions, reconstruction of decays, estimation of ionization energy loss, as well as identification of photon conversions, nuclear interactions, and heavy-flavour decays.

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External metrology systems are increasingly being integrated with traditional industrial articulated robots, especially in the aerospace industries, to improve their absolute accuracy for precision operations such as drilling, machining and jigless assembly. While currently most of the metrology assisted robotics control systems are limited in their position update rate, such that the robot has to be stopped in order to receive a metrology coordinate update, some recent efforts are addressed toward controlling robots using real-time metrology data. The indoor GPS is one of the metrology systems that may be used to provide real-time 6DOF data to a robot controller. Even if there is a noteworthy literature dealing with the evaluation of iGPS performance, there is, however, a lack of literature on how well the iGPS performs under dynamic conditions. This paper presents an experimental evaluation of the dynamic measurement performance of the iGPS, tracking the trajectories of an industrial robot. The same experiment is also repeated using a laser tracker. Besides the experiment results presented, this paper also proposes a novel method for dynamic repeatability comparisons of tracking instruments. © 2011 Springer-Verlag London Limited.

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Performance evaluation of object tracking systems is typically performed after the data has been processed, by comparing tracking results to ground truth. Whilst this approach is fine when performing offline testing, it does not allow for real-time analysis of the systems performance, which may be of use for live systems to either automatically tune the system or report reliability. In this paper, we propose three metrics that can be used to dynamically asses the performance of an object tracking system. Outputs and results from various stages in the tracking system are used to obtain measures that indicate the performance of motion segmentation, object detection and object matching. The proposed dynamic metrics are shown to accurately indicate tracking errors when visually comparing metric results to tracking output, and are shown to display similar trends to the ETISEO metrics when comparing different tracking configurations.

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Intelligent surveillance systems typically use a single visual spectrum modality for their input. These systems work well in controlled conditions, but often fail when lighting is poor, or environmental effects such as shadows, dust or smoke are present. Thermal spectrum imagery is not as susceptible to environmental effects, however thermal imaging sensors are more sensitive to noise and they are only gray scale, making distinguishing between objects difficult. Several approaches to combining the visual and thermal modalities have been proposed, however they are limited by assuming that both modalities are perfuming equally well. When one modality fails, existing approaches are unable to detect the drop in performance and disregard the under performing modality. In this paper, a novel middle fusion approach for combining visual and thermal spectrum images for object tracking is proposed. Motion and object detection is performed on each modality and the object detection results for each modality are fused base on the current performance of each modality. Modality performance is determined by comparing the number of objects tracked by the system with the number detected by each mode, with a small allowance made for objects entering and exiting the scene. The tracking performance of the proposed fusion scheme is compared with performance of the visual and thermal modes individually, and a baseline middle fusion scheme. Improvement in tracking performance using the proposed fusion approach is demonstrated. The proposed approach is also shown to be able to detect the failure of an individual modality and disregard its results, ensuring performance is not degraded in such situations.

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INTRODUCTION: High-fidelity simulation-based training is often avoided for early-stage students because of the assumption that while practicing newly learned skills, they are ill suited to processing multiple demands, which can lead to "cognitive overload" and poorer learning outcomes. We tested this assumption using a mixed-methods experimental design manipulating psychological immersion. METHODS: Thirty-nine randomly assigned first-year paramedicine students completed low- or high-environmental fidelity simulations [low-environmental fidelity simulations (LFenS) vs. high-environmental fidelity simulation (HFenS)] involving a manikin with obstructed airway (SimMan3G). Psychological immersion and cognitive burden were determined via continuous heart rate, eye tracking, self-report questionnaire (National Aeronautics and Space Administration Task Load Index), independent observation, and postsimulation interviews. Performance was assessed by successful location of obstruction and time-to-termination. RESULTS: Eye tracking confirmed that students attended to multiple, concurrent stimuli in HFenS and interviews consistently suggested that they experienced greater psychological immersion and cognitive burden than their LFenS counterparts. This was confirmed by significantly higher mean heart rate (P < 0.001) and National Aeronautics and Space Administration Task Load Index mental demand (P < 0.05). Although group allocation did not influence the proportion of students who ultimately revived the patient (58% vs. 30%, P < 0.10), the HFenS students did so significantly more quickly (P < 0.01). The LFenS students had low immersion resulting in greater assessment anxiety. CONCLUSIONS: High-environmental fidelity simulation engendered immersion and a sense of urgency in students, whereas LFenS created assessment anxiety and slower performance. We conclude that once early-stage students have learned the basics of a clinical skill, throwing them in the "deep end" of high-fidelity simulation creates significant additional cognitive burden but this has considerable educational merit.