scholarly journals Robust Radiation Sources Localization Based on the Peak Suppressed Particle Filter for Mixed Multi-Modal Environments

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3784 ◽  
Author(s):  
Wenrui Gao ◽  
Weidong Wang ◽  
Hongbiao Zhu ◽  
Guofu Huang ◽  
Dongmei Wu ◽  
...  
Keyword(s):  
Particle Filter ◽  
Radiation Field ◽  
Particle Filtering ◽  
Large Scale ◽  
Single Point ◽  
Source Parameters ◽  
Mean Shift ◽  
Sequential Estimation ◽  
Point Sources ◽  
Non Parametric

This paper addresses a detection problem where sparse measurements are utilized to estimate the source parameters in a mixed multi-modal radiation field. As the limitation of dimensional scalability and the unimodal characteristic, most existing algorithms fail to detect the multi-point sources gathered in narrow regions, especially with no prior knowledge about intensity and source number. The proposed Peak Suppressed Particle Filter (PSPF) method utilizes a hybrid scheme of multi-layer particle filter, mean-shift clustering technique and peak suppression correction to solve the major challenges faced by current existing algorithms. Firstly, the algorithm realizes sequential estimation of multi-point sources in a cross-mixed radiation field by using particle filtering and suppressing intensity peak value, while existing algorithms could just identify single point or spatially separated point sources. Secondly, the number of radioactive sources could be determined in a non-parametric manner as the fact that invalid particle swarms would disperse automatically. In contrast, existing algorithms either require prior information or rely on expensive statistic estimation and comparison. Additionally, to improve the prediction stability and convergent performance, distance correction module and configuration maintenance machine are developed to sustain the multimodal prediction stability. Finally, simulations and physical experiments are carried out in aspects such as different noise level, non-parametric property, processing time and large-scale estimation, to validate the effectiveness and robustness of the PSPF algorithm.

TESTING A PARTICLE FILTER TO RECONSTRUCT CLIMATE CHANGES OVER THE PAST CENTURIES

2011 ◽  
Vol 21 (12) ◽  
pp. 3611-3618 ◽  
Author(s):  
SVETLANA DUBINKINA ◽  
HUGUES GOOSSE ◽  
YOANN SALLAZ-DAMAZ ◽  
ELISABETH CRESPIN ◽  
MICHEL CRUCIFIX
Keyword(s):  
Particle Filter ◽  
Particle Filtering ◽  
Large Scale ◽  
Climate Changes ◽  
Climate Model ◽  
Real Data ◽  
Model Output ◽  
Coupled Climate Model ◽  
The Past ◽  
Reasonable Cost

We implement a data-assimilation method based on a particle filter in the coupled climate model LOVECLIM focusing on decadal to centennial time scales. Several tests are performed with particle filtering using pseudo-observations obtained from a twin experiment with the model, as well as using real-data observations over the last century. These tests demonstrate that it is possible to obtain a model output well correlated with the observations at the large scale at a reasonable cost.

scholarly journals A High-Resolution Foreground Model for the MWA EoR1 Field: Model and Implications for EoR Power Spectrum Analysis

2017 ◽  
Vol 34 ◽  
Author(s):  
P. Procopio ◽  
R. B. Wayth ◽  
J. Line ◽  
C. M. Trott ◽  
H. T. Intema ◽  
...  
Keyword(s):  
Power Spectrum ◽  
Large Scale ◽  
Field Model ◽  
Single Point ◽  
Neutral Hydrogen ◽  
Point Sources ◽  
Systematic Effects ◽  
Calibration Accuracy ◽  
Compact Sources ◽  
Residual Power

AbstractThe current generation of experiments aiming to detect the neutral hydrogen signal from the Epoch of Reionisation (EoR) is likely to be limited by systematic effects associated with removing foreground sources from target fields. In this paper, we develop a model for the compact foreground sources in one of the target fields of the MWA’s EoR key science experiment: the ‘EoR1’ field. The model is based on both the MWA’s GLEAM survey and GMRT 150 MHz data from the TGSS survey, the latter providing higher angular resolution and better astrometric accuracy for compact sources than is available from the MWA alone. The model contains 5 049 sources, some of which have complicated morphology in MWA data, Fornax A being the most complex. The higher resolution data show that 13% of sources that appear point-like to the MWA have complicated morphology such as double and quad structure, with a typical separation of 33 arcsec. We derive an analytic expression for the error introduced into the EoR two-dimensional power spectrum due to peeling close double sources as single point sources and show that for the measured source properties, the error in the power spectrum is confined to highk⊥modes that do not affect the overall result for the large-scale cosmological signal of interest. The brightest 10 mis-modelled sources in the field contribute 90% of the power bias in the data, suggesting that it is most critical to improve the models of the brightest sources. With this hybrid model, we reprocess data from the EoR1 field and show a maximum of 8% improved calibration accuracy and a factor of two reduction in residual power ink-space from peeling these sources. Implications for future EoR experiments including the SKA are discussed in relation to the improvements obtained.

An Improved Particle Filtering Algorithm Based on Mean Shift Algorithm for Infrared Target Tracking

2014 ◽  
Vol 1079-1080 ◽  
pp. 650-653
Author(s):  
Xi Peng Yin ◽  
Lin Lin Xia ◽  
Min Can He ◽  
Wei Cheng
Keyword(s):  
Particle Filter ◽  
Target Tracking ◽  
Posterior Distribution ◽  
Particle Filtering ◽  
Mean Shift ◽  
Mean Shift Algorithm ◽  
Filtering Algorithm ◽  
Particle Filter Algorithm

Animproved particle filter algorithm which based on mean shift algorithm isintroduced. The algorithm makes the particles move towards the high likelihoodregion in posterior distribution with the effect of mean shift algorithm,increases the efficiency of the particles moving, and reduces the phenomenon ofdegradation and dilution of particles

scholarly journals Estimating CO2 Emissions from Large Scale Coal-Fired Power Plants Using OCO-2 Observations and Emission Inventories

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 811
Author(s):  
Yaqin Hu ◽  
Yusheng Shi
Keyword(s):  
Power Plant ◽  
Co2 Emissions ◽  
Atmospheric Carbon Dioxide ◽  
Power Plants ◽  
Large Scale ◽  
Global Climate ◽  
Gaussian Model ◽  
Point Sources ◽  
Emission Inventories ◽  
Bottom Up

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

scholarly journals Smartphone-Based Inertial Odometry for Blind Walkers

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4033
Author(s):  
Peng Ren ◽  
Fatemeh Elyasi ◽  
Roberto Manduchi
Keyword(s):  
Particle Filtering ◽  
Inertial Sensors ◽  
State Of The Art ◽  
Inertial Sensor ◽  
Mean Shift ◽  
Gait Pattern ◽  
Comparative Assessment ◽  
Pedestrian Tracking ◽  
Step Counter ◽  
Assisted Navigation

Pedestrian tracking systems implemented in regular smartphones may provide a convenient mechanism for wayfinding and backtracking for people who are blind. However, virtually all existing studies only considered sighted participants, whose gait pattern may be different from that of blind walkers using a long cane or a dog guide. In this contribution, we present a comparative assessment of several algorithms using inertial sensors for pedestrian tracking, as applied to data from WeAllWalk, the only published inertial sensor dataset collected indoors from blind walkers. We consider two situations of interest. In the first situation, a map of the building is not available, in which case we assume that users walk in a network of corridors intersecting at 45° or 90°. We propose a new two-stage turn detector that, combined with an LSTM-based step counter, can robustly reconstruct the path traversed. We compare this with RoNIN, a state-of-the-art algorithm based on deep learning. In the second situation, a map is available, which provides a strong prior on the possible trajectories. For these situations, we experiment with particle filtering, with an additional clustering stage based on mean shift. Our results highlight the importance of training and testing inertial odometry systems for assisted navigation with data from blind walkers.

scholarly journals Estimating the Earth’s Outgoing Longwave Radiation Measured from a Moon-Based Platform

2021 ◽  
Vol 13 (11) ◽  
pp. 2201
Author(s):  
Hanlin Ye ◽  
Huadong Guo ◽  
Guang Liu ◽  
Jinsong Ping ◽  
Lu Zhang ◽  
...  
Keyword(s):  
Outgoing Longwave Radiation ◽  
Large Scale ◽  
Single Point ◽  
Longwave Radiation ◽  
Earth Observation ◽  
Artificial Satellites ◽  
Earth Observations ◽  
The Earth ◽  
Observation Geometry ◽  
Global Mean

Moon-based Earth observations have attracted significant attention across many large-scale phenomena. As the only natural satellite of the Earth, and having a stable lunar surface as well as a particular orbit, Moon-based Earth observations allow the Earth to be viewed as a single point. Furthermore, in contrast with artificial satellites, the varied inclination of Moon-based observations can improve angular samplings of specific locations on Earth. However, the potential for estimating the global outgoing longwave radiation (OLR) from the Earth with such a platform has not yet been fully explored. To evaluate the possibility of calculating OLR using specific Earth observation geometry, we constructed a model to estimate Moon-based OLR measurements and investigated the potential of a Moon-based platform to acquire the necessary data to estimate global mean OLR. The primary method of our study is the discretization of the observational scope into various elements and the consequent integration of the OLR of all elements. Our results indicate that a Moon-based platform is suitable for global sampling related to the calculation of global mean OLR. By separating the geometric and anisotropic factors from the measurement calculations, we ensured that measured values include the effects of the Moon-based Earth observation geometry and the anisotropy of the scenes in the observational scope. Although our results indicate that higher measured values can be achieved if the platform is located near the center of the lunar disk, a maximum difference between locations of approximately 9 × 10−4 W m−2 indicates that the effect of location is too small to remarkably improve observation performance of the platform. In conclusion, our analysis demonstrates that a Moon-based platform has the potential to provide continuous, adequate, and long-term data for estimating global mean OLR.

scholarly journals Modeling Gamma-Ray SEDs and Angular Extensions of Extreme TeV Blazars from Intergalactic Proton-Initiated Cascades in Contemporary Astrophysical EGMF Models

Universe ◽  
2021 ◽  
Vol 7 (7) ◽  
pp. 220
Author(s):  
Emil Khalikov
Keyword(s):  
Gamma Rays ◽  
Large Scale ◽  
Gamma Ray ◽  
High Energy ◽  
Cascade Model ◽  
Point Sources ◽  
Spectral Energy ◽  
Observation Data ◽  
Cherenkov Telescopes ◽  
The Universe

The intrinsic spectra of some distant blazars known as “extreme TeV blazars” have shown a hint at an anomalous hardening in the TeV energy region. Several extragalactic propagation models have been proposed to explain this possible excess transparency of the Universe to gamma-rays starting from a model which assumes the existence of so-called axion-like particles (ALPs) and the new process of gamma-ALP oscillations. Alternative models suppose that some of the observable gamma-rays are produced in the intergalactic cascades. This work focuses on investigating the spectral and angular features of one of the cascade models, the Intergalactic Hadronic Cascade Model (IHCM) in the contemporary astrophysical models of Extragalactic Magnetic Field (EGMF). For IHCM, EGMF largely determines the deflection of primary cosmic rays and electrons of intergalactic cascades and, thus, is of vital importance. Contemporary Hackstein models are considered in this paper and compared to the model of Dolag. The models assumed are based on simulations of the local part of large-scale structure of the Universe and differ in the assumptions for the seed field. This work provides spectral energy distributions (SEDs) and angular extensions of two extreme TeV blazars, 1ES 0229+200 and 1ES 0414+009. It is demonstrated that observable SEDs inside a typical point spread function of imaging atmospheric Cherenkov telescopes (IACTs) for IHCM would exhibit a characteristic high-energy attenuation compared to the ones obtained in hadronic models that do not consider EGMF, which makes it possible to distinguish among these models. At the same time, the spectra for IHCM models would have longer high energy tails than some available spectra for the ALP models and the universal spectra for the Electromagnetic Cascade Model (ECM). The analysis of the IHCM observable angular extensions shows that the sources would likely be identified by most IACTs not as point sources but rather as extended ones. These spectra could later be compared with future observation data of such instruments as Cherenkov Telescope Array (CTA) and LHAASO.

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