scholarly journals PBR Clutter Suppression Algorithm Based on Dilation Morphology of Non-Uniform Grid

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 708 ◽  
Author(s):  
Qian Zhu ◽  
Tao Li ◽  
Jiameng Pan ◽  
Qinglong Bao
Keyword(s):  
False Alarm ◽  
Simulated Data ◽  
Iteration Scheme ◽  
Experimental Results ◽  
Uniform Grid ◽  
Clutter Suppression ◽  
Tracing Algorithm ◽  
Polar Grid ◽  
Parallel Iteration ◽  
Grid Platform

Many new challenges are faced by the PBR (passive bi-static radar) employing non-cooperative radar illuminators. After the CFAR (constant false alarm) processor, the appearance of the amount of false alarm clutter points impacts the following tracing performance. To enhance the PBR tracing performance, we consider to reduce these clutter points before target tracing as soon as possible. In this paper, we propose a PBR clutter suppression algorithm based on dilation morphology of non-uniform grid. Firstly, we construct the non-uniform polar grid based on the acquisition geometry of PBR. Then, with the help of the grid platform, we separate the false alarm clutter points based on the dilation morphology. To efficiently operate the algorithm, we build up its parallel iteration scheme. To verify the performance of the proposed algorithm, we utilize both simulated data and field data to do the experiment. Experimental results show that the algorithm can effectively suppress most of the clutter points. Besides, we respectively combine the proposed suppression algorithm with two typical tracking algorithms to test the performance. Experimental results reveal that the compound tracing algorithm outperforms the traditional one. It can enhance the PBR tracing performance, reduce the occurrence probability of false tracks and meanwhile save time.

Ultra Surf Flow Detection Based on Statistical Classification

2015 ◽  
Vol 713-715 ◽  
pp. 495-499
Author(s):  
Xun Yi Ren ◽  
Han Qing Hu
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Experimental Results ◽  
Statistical Classification ◽  
Flow Detection

Unbounded browsing software is an application worked in Internet client. It uses a custom encryption protocol to break the traditional network filtering. In this paper, we can detect this application through classifying the Ultra Surf T mode (TCP packets) packets and using SPID. The experimental results show that we can effectively reduce the false alarm rate and detect the application accurately by classifying the Ultra Surf T mode (TCP packets) packets and using SPID.

scholarly journals An Anti-FOD Method Based on CA-CM-CFAR for MMW Radar in Complex Clutter Background

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1635 ◽  
Author(s):  
Xiaoqi Yang ◽  
Kai Huo ◽  
Jianwei Su ◽  
Xinyu Zhang ◽  
Weidong Jiang
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Millimeter Wave ◽  
Radar System ◽  
Experimental Results ◽  
Foreign Object ◽  
Constant False Alarm Rate ◽  
Test Statistic ◽  
Homogeneous Background ◽  
Distributed Test

Traditional constant false alarm rate (CFAR) methods have shown their potential for foreign object debris (FOD) indication. However, the performance of these methods would deteriorate under the complex clutter background in airport scenes. This paper presents a threshold-improved approach based on the cell-averaging clutter-map (CA-CM-) CFAR and tests it on a millimeter-wave (MMW) radar system. Clutter cases are first classified with variability indexes (VIs). In homogeneous background, the threshold is calculated by the student-t-distributed test statistic; under the discontinuous clutter conditions, the threshold is modified according to current VI conditions, in order to address the performance decrease caused by extended clutter edges. Experimental results verify that the chosen targets can be indicated by the t-distributed threshold in homogeneous background. Moreover, effective detection of the obscured targets could also be achieved with significant detectability improvement at extended clutter edges.

IntegraEPI

2011 ◽  
pp. 444-468
Author(s):  
Fabricio Alves Barbosa da Silva ◽  
Henrique Fabricio Gagliardi ◽  
Eduardo Gallo ◽  
Maria Antonia Madope ◽  
Virgilio Cavicchioli Neto ◽  
...  
Keyword(s):  
Large Scale ◽  
Simulated Data ◽  
Heterogeneous Databases ◽  
Modeling And Analysis ◽  
The Public ◽  
Epidemic Dynamics ◽  
Health Authorities ◽  
Virtual Population ◽  
Disease Spreading ◽  
Grid Platform

The authors present in this work a large-scale system for space-time visualization, monitoring, modeling and analysis of epidemic data using a Grid platform. This system, dubbed IntegraEPI, is capable to integrate data from heterogeneous databases related to epidemic analysis and to make available analytical and computational methods to increase the predicting capability of the public heath system, in order to optimize its activities and resources when dealing with epidemic outbreak and prevention. This system, differently of what has been proposed before, is integrated and consequently it enables the construction of detailed predictive models of the dynamics of disease spreading. With the help of IntegraEPI, Health authorities will be able to decide about a set of possible actions that will be previously tested in a virtual population interacting in an urban infrastructure, considering its environmental factors, and finally compare the simulated data to consolidated data of real epidemic dynamics.

A Low-Complexity Algorithm of Joint Multiple Frequency Offsets and Channels Estimation in Cooperative Relay Systems

2013 ◽  
Vol 748 ◽  
pp. 1046-1050 ◽  
Author(s):  
Hui Yan ◽  
Zhong Pei Zhang
Keyword(s):  
Interference Cancellation ◽  
Low Complexity ◽  
Training Sequence ◽  
Iteration Scheme ◽  
Cooperative Relay ◽  
Decode And Forward ◽  
Relay Systems ◽  
Parallel Iteration ◽  
Correlation Properties ◽  
Frequency Estimator

A low complexity joint estimator of multiple CFOs and Channels is presented in cooperative relay systems. The new algorithm first utilizes correlation-based frequency estimator to get CFOs initial estimation, and then serial interference cancellation based on correlation properties of training sequence in different relays is done to obtain the initial channel estimation. Moreover, a parallel iteration scheme with interference cancellation is proposed to reduce time complexity of the traditional serial iteration. In the overall process, matrix inversion is avoided. Thus, the complexity of the proposed algorithm in both time and computation is much less than the existing algorithms. In last, simulation results verify the iterative algorithm achieves a good performance in Decode and Forward (DF) relay system.

scholarly journals New Robust MEWMA Control Chart for Monitoring Contaminated Data

2019 ◽  
Vol 8 (10) ◽  
pp. 2773-2780
Keyword(s):  
False Alarm ◽  
Covariance Matrix ◽  
Control Chart ◽  
Time Series Data ◽  
Simulated Data ◽  
Series Data ◽  
Random Pattern ◽  
Contaminated Data ◽  
Mewma Control Chart ◽  
Mean Vector

Multivariate Exponential Weighted Moving Average (MEWMA), E 2 control chart is a popular multivariate control chart for monitoring the stability of time series data (non-random pattern). However, in this paper, we have shown that the existing MEWMA, E 2 control chart is sensitive in contaminated data or in the presence of outliers. To address this problem, this paper proposed an alternative MEWMA E 2 control chart using robust mean vector and covariance matrix instead of the classical mean vector and covariance matrix respectively. The classical mean vector in MEWMA E 2 control chart is replaced by Winsorized Modified One-step M-estimator (WM) while the classical covariance matrix is replaced by the Winsorized covariance matrix. The proposed MEWMA E 2 control chart known as robust MEWMA control chart, denoted as RE2 control chart. The control limit for the RE2 control chart was calculated based on simulated data. The performance of RE2 and existing MEWMA E 2 control charts are based on the false alarm rate. The result revealed that the RE2 control chart is more effective in controlling false alarm rates as compared to the existing MEWMA, E 2 control chart. The zinc-lead flotation data show that the RE2 performs better in application.

Fat ray ultrasound transmission tomography: preliminary experimental results with simulated data

2020 ◽  
Author(s):  
Torsten Hopp ◽  
Franziska Zuch ◽  
Pierre-Antoine Comby ◽  
Nicole Ruiter
Keyword(s):  
Simulated Data ◽  
Experimental Results ◽  
Transmission Tomography

scholarly journals Analysis and Denoising of Hyperspectral Remote Sensing Image in the Curvelet Domain

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Dong Xu ◽  
Lei Sun ◽  
Jianshu Luo ◽  
Zhihui Liu
Keyword(s):  
Remote Sensing ◽  
Simulated Data ◽  
Real Data ◽  
Remote Sensing Image ◽  
Hyperspectral Remote Sensing ◽  
Experimental Results ◽  
Spectral Correlation ◽  
The Real ◽  
Characteristics Analysis ◽  
Hyperspectral Remote Sensing Image

A new denoising algorithm is proposed according to the characteristics of hyperspectral remote sensing image (HRSI) in the curvelet domain. Firstly, each band of HRSI is transformed into the curvelet domain, and the sets of subband images are obtained from different wavelength of HRSI. And then the detail subband images in the same scale and same direction from different wavelengths of HRSI are stacked to obtain new 3-D datacubes of the curvelet domain. Again, the characteristics analysis of these 3-D datacubes is performed. The analysis result shows that each new 3-D datacube has the strong spectral correlation. At last, due to the strong spectral correlation of new 3-D datacubes, the multiple linear regression is introduced to deal with these new 3-D datacubes in the curvelet domain. The simulated and the real data experiments are performed. The simulated data experimental results show that the proposed algorithm is superior to the compared algorithms in the references in terms of SNR. Furthermore, MSE and MSSIM in each band are utilized to show that the proposed algorithm is superior. The real data experimental results show that the proposed algorithm effectively removes the common spotty noise and the strip noise and simultaneously maintains more fine features during the denoising process.

Optimization of the Working Conditions of a Single Molten Carbonate Fuel Cell

2012 ◽  
Vol 267 ◽  
pp. 64-71
Author(s):  
Jarosław Milewski ◽  
Andrzej Miller
Keyword(s):  
Mathematical Model ◽  
Fuel Cell ◽  
Working Conditions ◽  
Simulated Data ◽  
Experimental Results ◽  
Molten Carbonate Fuel Cell ◽  
Molten Carbonate ◽  
Carbonate Fuel Cell

A mathematical model of a Molten Carbonate Fuel Cell (MCFC) is shown. The model is used to simulate an experimental lab-stand single fuel cell unit measuring 55 cm2. The comparison of simulated data against the experimental results is shown and commented on.

False Alarm and Missing Alarm Models of Multiple Bits Watermarking

2014 ◽  
Vol 543-547 ◽  
pp. 2155-2158
Author(s):  
Jun Xiao ◽  
Deng Yu Li ◽  
Xiao Xu Leng ◽  
Jiao Rao Su
Keyword(s):  
False Alarm ◽  
Experimental Results ◽  
Probability Models ◽  
Dither Modulation ◽  
Multiple Watermarks ◽  
Theoretical Results ◽  
Detection Principle

False alarm and missing alarm are two of the most important performances for multiple bits watermarking systems. In this paper, we study false alarm and missing alarm probability models when multiple watermarks or multiple bits watermarks embedded. We derive the false alarm and missing alarm probability models for dither modulation from the detection principle of the detectors. The theoretical results are compared with the experimental results obtained in the case of random work and watermark, and the comparison validates the accuracy of the models, and it also shows that random work and watermark have little influence on the false alarm and missing alarm probabilities, and this is the same with the situation when only one bit watermark is embedded by DM.

scholarly journals Weather Radar Network Benefit Model for Tornadoes

2019 ◽  
Vol 58 (5) ◽  
pp. 971-987 ◽  
Author(s):  
John Y. N. Cho ◽  
James M. Kurdzo
Keyword(s):  
False Alarm ◽  
Detection Probability ◽  
Weather Radar ◽  
Horizontal Resolution ◽  
Experimental Results ◽  
Regression Analyses ◽  
Personal Time ◽  
Radar Network ◽  
Tornado Warning ◽  
Rapid Scanning

AbstractA monetized tornado benefit model is developed for arbitrary weather radar network configurations. Geospatial regression analyses indicate that improvement of two key radar parameters—fraction of vertical space observed and cross-range horizontal resolution—leads to better tornado warning performance as characterized by tornado detection probability and false-alarm ratio. Previous experimental results showing faster volume scan rates yielding greater warning performance are also incorporated into the model. Enhanced tornado warning performance, in turn, reduces casualty rates. In addition, lower false-alarm ratios save costs by cutting down on work and personal time lost while taking shelter. The model is run on the existing contiguous U.S. weather radar network as well as hypothetical future configurations. Results show that the current radars provide a tornado-based benefit of ~$490 million (M) yr−1. The remaining benefit pool is about $260M yr−1, split roughly evenly between coverage- and rapid-scanning-related gaps.

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