Search NASA⌕ Search

SEARCH · Search NASA

Results for “Tracking error”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Projection-Based Linear Constrained Estimation and Fusion over Long-Haul Links

In this work, we study estimation and fusion with linear dynamics in long-haul sensor networks, wherein a number of sensors are remotely deployed over a large geographical area for performing tasks such as target tracking, and a remote fusion center serves to combine the information provided by these sensors in order to improve the overall tracking accuracy. In reality, the motion of a dynamic target might be subject to certain constraints, for instance, those defined by a road network. We explore the accuracy performance of projection-based constrained estimation and fusion methods that is affected by information loss over the long-haul links. We use a tracking example to compare the tracking errors under various implementations of centralized and distributed projection-based estimation and fusion methods.

Rao, Nageswara S↗
DOE OSTI2017

A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint

This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Simplifying the Tracking of Waste Disposal Inventories: Process Improvement for Rapid Data Interpretation and Reduced Errors - 16143

Tracking the inventory of low-level radioactive waste at an operating disposal facility offers unique challenges. At the Savannah River Site's Saltstone Disposal Facility (SDF) the inventory used in Performance Assessment modeling is determined based on radionuclide concentrations from the aqueous waste in a feed tank and the volume of the waste that is transferred from the feed tank to the Saltstone Production Facility (SPF). These inputs are reported quarterly. As such, the disposal inventories are also updated quarterly; however, due to decay and ingrowth, the inventory values for some radionuclides can be misrepresented if the data is not tracked appropriately. Additionally, it is not feasible to analyze the feed tank samples for every possible radionuclide; therefore, a series of adjustments are necessary to estimate the concentrations of radionuclides that are not explicitly measured but still pose a potential dose risk. Prior to 2015, the SDF disposal inventories were updated using a series of spreadsheets that required users to perform a significant number of steps (including manually transferring data back and forth between a separate decay and ingrowth calculation software). Despite this labor intensive approach, the process only provided single point-in-time results. With multiple steps, minimal automation, and limited result data, this approach to inventory tracking was not ideal and minor mistakes were often identified during the equally cumbersome review process. As a process improvement, the simplified SDF Waste Inventory Disposed Estimator (SDF-WIDE) Model was developed using GoldSim software. The software allows users to identify specific dates to define the duration of the simulation, from the beginning of operations until the time of future facility closure, and provides graphical interfaces for displaying data over time. Further, GoldSim's Contaminant Transport Module is used to perform the decay and ingrowth calculations, making the model completely self-contained (i.e., there is no need to transfer intermediate data back and forth between different programs). GoldSim also includes model 'versioning' features that significantly reduce the time needed to perform the appropriate quality assurance reviews as required for each quarterly inventory update. By transitioning from the complex spreadsheets to the simplified SDFWIDE model, the time needed to perform updates to the SDF inventory has been reduced from days to hours, the risk of making human errors has been greatly mitigated, and users are able to quickly observe trends in the data over time. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

TH-AB-202-02: Real-Time Verification and Error Detection for MLC Tracking Deliveries Using An Electronic Portal Imaging Device

Purpose: The added complexity of the real-time adaptive multi-leaf collimator (MLC) tracking increases the likelihood of undetected MLC delivery errors. In this work we develop and test a system for real-time delivery verification and error detection for MLC tracking radiotherapy using an electronic portal imaging device (EPID). Methods: The delivery verification system relies on acquisition and real-time analysis of transit EPID image frames acquired at 8.41 fps. In-house software was developed to extract the MLC positions from each image frame. Three comparison metrics were used to verify the MLC positions in real-time: (1) field size, (2) field location and, (3) field shape. The delivery verification system was tested for 8 VMAT MLC tracking deliveries (4 prostate and 4 lung) where real patient target motion was reproduced using a Hexamotion motion stage and a Calypso system. Sensitivity and detection delay was quantified for various types of MLC and system errors. Results: For both the prostate and lung test deliveries the MLC-defined field size was measured with an accuracy of 1.25 cm{sup 2} (1 SD). The field location was measured with an accuracy of 0.6 mm and 0.8 mm (1 SD) for lung and prostate respectively. Field location errors (i.e. tracking in wrong direction) with a magnitude of 3 mm were detected within 0.4 s of occurrence in the X direction and 0.8 s in the Y direction. Systematic MLC gap errors were detected as small as 3 mm. The method was not found to be sensitive to random MLC errors and individual MLC calibration errors up to 5 mm. Conclusion: EPID imaging may be used for independent real-time verification of MLC trajectories during MLC tracking deliveries. Thresholds have been determined for error detection and the system has been shown to be sensitive to a range of delivery errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Single-pixel interior filling function approach for detecting and correcting errors in particle tracking

We present a general method for detecting and correcting biases in the outputs of particle-tracking experiments. Our approach is based on the histogram of estimated positions within pixels, which we term the single-pixel interior filling function (SPIFF). We use the deviation of the SPIFF from a uniform distribution to test the veracity of tracking analyses from different algorithms. Unbiased SPIFFs correspond to uniform pixel filling, whereas biased ones exhibit pixel locking, in which the estimated particle positions concentrate toward the centers of pixels. Although pixel locking is a well-known phenomenon, we go beyond existing methods to show how the SPIFF can be used to correct errors. Here, the key is that the SPIFF aggregates statistical information from many single-particle images and localizations that are gathered over time or across an ensemble, and this information augments the single-particle data. We explicitly consider two cases that give rise to significant errors in estimated particle locations: undersampling the point spread function due to small emitter size and intensity overlap of proximal objects. In these situations, we show how errors in positions can be corrected essentially completely with little added computational cost. Additional situations and applications to experimental data are explored in SI Appendix. In the presence of experimental-like shot noise, the precision of the SPIFF-based correction achieves (and can even exceed) the unbiased Cramér–Rao lower bound. We expect the SPIFF approach to be useful in a wide range of localization applications, including single-molecule imaging and particle tracking, in fields ranging from biology to materials science to astronomy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

An Error-Entropy Minimization Algorithm for Tracking Control of Nonlinear Stochastic Systems with Non-Gaussian Variables

This paper presents an error-entropy minimization tracking control algorithm for a class of dynamic stochastic system. The system is represented by a set of time-varying discrete nonlinear equations with non-Gaussian stochastic input, where the statistical properties of stochastic input are unknown. By using Parzen windowing with Gaussian kernel to estimate the probability densities of errors, recursive algorithms are then proposed to design the controller such that the tracking error can be minimized. The performance of the error-entropy minimization criterion is compared with the mean-square-error minimization in the simulation results.

Entropy↗
DOE OSTI2025

Analysis of the Trusted Inertial Terrain-Aided Navigation Measurement Function

The trusted inertial terrain-aided navigation (TITAN) algorithm leverages an airborne vertical synthetic aperture radar to measure the range to the closest ground points along several prescribed iso-Doppler contours. These TITAN minimum-range, prescribed-Doppler measurements are the result of a constrained nonlinear optimization problem whose optimization function and constraints both depend on the radar position and velocity. Owing to the complexity of this measurement definition, analysis of the TITAN algorithm is lacking in prior work. This publication offers such an analysis, making the following three contributions: (1) an analytical solution to the TITAN constrained optimization measurement problem, (2) a derivation of the TITAN measurement function Jacobian, and (3) a derivation of the Cramér-Rao lower bound on the estimated position and velocity error covariance. These three contributions are verified via Monte Carlo simulations over synthetic terrain, which further reveal two remarkable properties of the TITAN algorithm: (1) the along-track positioning errors tend to be smaller than the cross-track positioning errors, and (2) the cross-track positioning errors are independent of the terrain roughness.

TITAN↗
DOE OSTI2017

Analysis and correction of errors in nanoscale particle tracking using the Single-pixel interior filling function (SPIFF) algorithm

Particle tracking, which is an essential tool in many fields of scientific research, uses algorithms that retrieve the centroid of tracked particles with sub-pixel accuracy. However, images in which the particles occupy a small number of pixels on the detector, are in close proximity to other particles or suffer from background noise, show a systematic error in which the particle sub-pixel positions are biased towards the center of the pixel. This “pixel locking” effect greatly reduces particle tracking accuracy. In this report, we demonstrate the severity of these errors by tracking experimental (and simulated) imaging data of optically trapped silver nanoparticles and single fluorescent proteins. We show that errors in interparticle separation, angle and mean square displacement are significantly reduced by applying the corrective Single-Pixel Interior Filling Function (SPIFF) algorithm. Our work demonstrates the potential ubiquity of such errors and the general applicability of SPIFF correction to many experimental fields.

Science & Technology - Other Topics↗
DOE OSTI2016

Minimizing treatment planning errors in proton therapy using failure mode and effects analysis

Purpose: Failure mode and effects analysis (FMEA) is a widely used tool to evaluate safety or reliability in conventional photon radiation therapy. However, reports about FMEA application in proton therapy are scarce. The purpose of this study is to apply FMEA in safety improvement of proton treatment planning at their center. Methods: The authors performed an FMEA analysis of their proton therapy treatment planning process using uniform scanning proton beams. The authors identified possible failure modes in various planning processes, including image fusion, contouring, beam arrangement, dose calculation, plan export, documents, billing, and so on. For each error, the authors estimated the frequency of occurrence, the likelihood of being undetected, and the severity of the error if it went undetected and calculated the risk priority number (RPN). The FMEA results were used to design their quality management program. In addition, the authors created a database to track the identified dosimetric errors. Periodically, the authors reevaluated the risk of errors by reviewing the internal error database and improved their quality assurance program as needed. Results: In total, the authors identified over 36 possible treatment planning related failure modes and estimated the associated occurrence, detectability, and severity to calculate the overall risk priority number. Based on the FMEA, the authors implemented various safety improvement procedures into their practice, such as education, peer review, and automatic check tools. The ongoing error tracking database provided realistic data on the frequency of occurrence with which to reevaluate the RPNs for various failure modes. Conclusions: The FMEA technique provides a systematic method for identifying and evaluating potential errors in proton treatment planning before they result in an error in patient dose delivery. The application of FMEA framework and the implementation of an ongoing error tracking system at their clinic have proven to be useful in error reduction in proton treatment planning, thus improving the effectiveness and safety of proton therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Considerations on the design of a rare isotope beam facility based on superconducting heavy ion linacs

To establish an accelerator facility based on superconducting linear accelerator (linac) for nuclear and applied sciences in Korea, the rare isotope science project started in December 2011 under the auspices of the Institute for Basic Science (IBS). The layout of the facility has been mostly frozen since 2013 and civil construction began in 2016. On the other hand, an alternative linac design option was recently investigated in collaboration with the linac development group of Argonne National Lab in search of a further optimized configuration. A new linac lattice was developed and evaluated against realistic machine errors using TRACK. The beam optics simulations and error analysis then proved the soundness of this alternative design. In addition, beam optics of the injector was studied for simultaneous acceleration of both stable and rare isotope beams with the use of an electron beam ion source (EBIS). Additionally considered are alternative options of high-power cyclotrons as ISOL driver in order to enhance the capability of rare isotope beam production and fully exploit the superconducting linac facility built at high cost.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) can not fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First, the modeling error PDF by the tradional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. Furthermore, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.

Modelling↗
DOE OSTI2016

Poster - 51: A tumor motion-compensating system with tracking and prediction – a proof-of-concept study

Purpose: This work reports on the development of a mechanical slider system for the counter-steering of tumor motion in adaptive Radiation Therapy (RT). The tumor motion was tracked using a weighted optical flow algorithm and its position is being predicted with a neural network (NN). Methods: The components of the proposed mechanical counter-steering system includes: (1) an actuator which provides the tumor motion, (2) the motion detection using an optical flow algorithm, (3) motion prediction using a neural network, (4) a control module and (5) a mechanical slider to counter-steer the anticipated motion of the tumor phantom. An asymmetrical cosine function and five patient traces (P1–P5) were used to evaluate the tracking of a 3D printed lung tumor. In the proposed mechanical counter-steering system, both actuator (Zaber NA14D60) and slider (Zaber A-BLQ0070-E01) were programed to move independently with LabVIEW and their positions were recorded by 2 potentiometers (ETI LCP12S-25). The accuracy of this counter-steering system is given by the difference between the two potentiometers. Results: The inherent accuracy of the system, measured using the cosine function, is −0.15 ± 0.06 mm. While the errors when tracking and prediction were included, is (0.04 ± 0.71) mm. Conclusion: A prototype tumor motion counter-steering system with tracking and prediction was implemented. The inherent errors are small in comparison to the tracking and prediction errors, which in turn are small in comparison to the magnitude of tumor motion. The results show that this system is suited for evaluating RT tracking and prediction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-BRA-06: Electromagnetic Beacon Insertion in Lung Cancer Patients and Resultant Surrogacy Errors for Dynamic MLC Tumour Tracking

Purpose: To assess endo-bronchial electromagnetic beacon insertion and to quantify the geometric accuracy of using beacons as a surrogate for tumour motion in real-time multileaf collimator (MLC) tracking of lung tumours. Methods: The LIGHT SABR trial is a world-first clinical trial in which the MLC leaves move with lung tumours in real time on a standard linear accelerator. Tracking is performed based on implanted electromagnetic beacons (CalypsoTM, Varian Medical Systems, USA) as a surrogate for tumour motion. Five patients have been treated and have each had three beacons implanted endo-bronchially under fluoroscopic guidance. The centre of mass (C.O.M) has been used to adapt the MLC in real-time. The geometric error in using the beacon C.O.M as a surrogate for tumour motion was measured by measuring the tumour and beacon C.O.M in all phases of the respiratory cycle of a 4DCT. The surrogacy error was defined as the difference in beacon and tumour C.O.M relative to the reference phase (maximum exhale). Results: All five patients have had three beacons successfully implanted with no migration between simulation and end of treatment. Beacon placement relative to tumour C.O.M varied from 14 to 74 mm and in one patient spanned two lobes. Surrogacy error was measured in each patient on the simulation 4DCT and ranged from 0 to 3 mm. Surrogacy error as measured on 4DCT was subject to artefacts in mid-ventilation phases. Surrogacy error was a function of breathing phase and was typically larger at maximum inhale. Conclusion: Beacon placement and thus surrogacy error is a major component of geometric uncertainty in MLC tracking of lung tumours. Surrogacy error must be measured on each patient and incorporated into margin calculation. Reduction of surrogacy error is limited by airway anatomy, however should be taken into consideration when performing beacon insertion and planning. This research is funded by Varian Medical Systems via a collaborative research agreement.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

GEDet: Detecting Erroneous Nodes with A Few Examples

Detecting nodes with erroneous values in real-world graphs re- mains challenging due to the lack of examples and various error scenarios. We demonstrate GEDet, an error detection engine that can detect erroneous nodes in graphs with a few examples. The GEDet framework tackles error detection as a few-shot node classification problem. We invite the attendees to experience the following unique features. (1) Few-shot detection. Users only need to provide a few examples of erroneous nodes to perform error detection with GEDet. GEDet achieves desirable accuracy with (a) a graph augmentation module, which automatically generates synthetic examples to learn the classifier, and (b) an adversarial detection module, which improves classifiers to better distinguish erroneous nodes from both cleaned nodes and synthetic examples. We show that GEDet significantly improves the state-of-the-art error detection methods. (2) Diverse error scenarios. GEDet profiles data errors with a built-in library of transformation functions from correct values to errors. Users can also easily “plug in” new error types or examples. (3) User-centric detection. GEDet supports (a) an active learning mode to engage users to verify detected results, and adapts the error detection process accordingly; and (b) visual interfaces to interpret and track detected errors.

Guan, Sheng↗
DOE OSTI2016

Validation of a pretreatment delivery quality assurance method for the CyberKnife Synchrony system

Purpose: To evaluate the geometric and dosimetric accuracies of the CyberKnife Synchrony respiratory tracking system (RTS) and to validate a method for pretreatment patient-specific delivery quality assurance (DQA). Methods: An EasyCube phantom was mounted on the ExacTrac gating phantom, which can move along the superior–inferior (SI) axis of a patient to simulate a moving target. The authors compared dynamic and static measurements. For each case, a Gafchromic EBT3 film was positioned between two slabs of the EasyCube, while a PinPoint ionization chamber was placed in the appropriate space. There were three steps to their evaluation: (1) the field size, the penumbra, and the symmetry of six secondary collimators were measured along the two main orthogonal axes. Dynamic measurements with deliberately simulated errors were also taken. (2) The delivered dose distributions (from step 1) were compared with the planned ones, using the gamma analysis method. The local gamma passing rates were evaluated using three acceptance criteria: 3% local dose difference (LDD)/3 mm, 2%LDD/2 mm, and 3%LDD/1 mm. (3) The DQA plans for six clinical patients were irradiated in different dynamic conditions, to give a total of 19 cases. The measured and planned dose distributions were evaluated with the same gamma-index criteria used in step 2 and the measured chamber doses were compared with the planned mean doses in the sensitive volume of the chamber. Results: (1) A very slight enlargement of the field size and of the penumbra was observed in the SI direction (on average <1 mm), in line with the overall average CyberKnife system error for tracking treatments. (2) Comparison between the planned and the correctly delivered dose distributions confirmed the dosimetric accuracy of the RTS for simple plans. The multicriteria gamma analysis was able to detect the simulated errors, proving the robustness of their method of analysis. (3) All of the DQA clinical plans passed the tests, both in static and dynamic conditions. No statistically significant differences were found between static and dynamic cases, confirming the high degree of accuracy of the Synchrony RTS. Conclusions: The presented methods and measurements verified the mechanical and dosimetric accuracy of the Synchrony RTS. Their method confirms the fact that the RTS, if used properly, is able to treat a moving target with great precision. By combining PinPoint ion chamber, EBT3 films, and gamma evaluation of dose distributions, their DQA method robustly validated the effectiveness of CyberKnife and Synchrony system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Submodule Capacitor Reduction for a 1 MVA SiC-Based Modular Multilevel Converter Motor Drive using High Frequency Common-Mode Voltage Injection

This paper describes a strategy to reduce the size of submodule capacitors of a 1 MVA, 0-1 kHz, 7-level modular multilevel converter (MMC) based medium voltage variable speed drive (MVVSD) using 1.7 kV SiC MOSFETs. Hardware designs of submodules to withstand high dv/dt and capacitor selection based on common mode voltage injection have been presented in literature. The issue with injection is the error in tracking of injected circulation current which results in fundamental frequency fluctuations in the submodule capacitor voltage. This paper presents a strategy for higher frequency sinusoidal common mode voltage based on more accurate tracking of the circulating current; realized through an improved control strategy combined with a higher switching frequency. Using the methods presented in this paper, a smaller submodule capacitance and reduced output current THD of the motor drive is achieved. A loss analysis model is proposed to evaluate the effect of the proposed strategy on the MMC efficiency. This helps balance the reduction in the capacitor against the increase in the losses as a result of increased switching frequency. Simulations and a down-scaled experimental setup are used to demonstrate this concept.

Potty, Karun↗
DOE OSTI2015

Accuracy of Robotic Radiosurgical Liver Treatment Throughout the Respiratory Cycle

Purpose: To quantify random uncertainties in robotic radiosurgical treatment of liver lesions with real-time respiratory motion management. Methods and Materials: We conducted a retrospective analysis of 27 liver cancer patients treated with robotic radiosurgery over 118 fractions. The robotic radiosurgical system uses orthogonal x-ray images to determine internal target position and correlates this position with an external surrogate to provide robotic corrections of linear accelerator positioning. Verification and update of this internal–external correlation model was achieved using periodic x-ray images collected throughout treatment. To quantify random uncertainties in targeting, we analyzed logged tracking information and isolated x-ray images collected immediately before beam delivery. For translational correlation errors, we quantified the difference between correlation model–estimated target position and actual position determined by periodic x-ray imaging. To quantify prediction errors, we computed the mean absolute difference between the predicted coordinates and actual modeled position calculated 115 milliseconds later. We estimated overall random uncertainty by quadratically summing correlation, prediction, and end-to-end targeting errors. We also investigated relationships between tracking errors and motion amplitude using linear regression. Results: The 95th percentile absolute correlation errors in each direction were 2.1 mm left–right, 1.8 mm anterior–posterior, 3.3 mm cranio–caudal, and 3.9 mm 3-dimensional radial, whereas 95th percentile absolute radial prediction errors were 0.5 mm. Overall 95th percentile random uncertainty was 4 mm in the radial direction. Prediction errors were strongly correlated with modeled target amplitude (r=0.53-0.66, P<.001), whereas only weak correlations existed for correlation errors. Conclusions: Study results demonstrate that model correlation errors are the primary random source of uncertainty in Cyberknife liver treatment and, unlike prediction errors, are not strongly correlated with target motion amplitude. Aggregate 3-dimensional radial position errors presented here suggest the target will be within 4 mm of the target volume for 95% of the beam delivery.

62 RADIOLOGY AND NUCLEAR MEDICINE↗