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1.
PLoS One ; 17(7): e0269490, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35839164

RESUMO

Marine protected areas (MPAs) are widely utilized for conservation of the world's marine resources. Yet, compliance with MPA regulations remains difficult to measure because of limits to human resources and a lack of affordable technologies to automate monitoring over time. The Marine Monitor, an autonomous vessel monitoring, recording, and reporting system leveraging commercial off-the-shelf X-band marine radar to detect and track vessels, was used to monitor five nearshore California MPAs simultaneously and continuously to identify and compare site-specific use patterns over one year. Vessel tracks were classified into two movement patterns to capture likely fishing activity, "focal" or "linear", that corresponded with local targeted species. Some illegal fishing potentially occurred at all sites (7-17% of tracks depending on site) most frequently on weekends and at mid-day, but the majority of activity occurred just outside the MPAs and in the near vicinity suggesting both a high level of compliance with regulations and awareness of MPA boundaries. Time spent engaged in potential fishing activity compared to track counts suggests that unique vessels may spend more time fishing inside area boundaries at some sites than others. The spatial distribution of activity shows distinct concentrations near MPA boundaries at all sites which strongly suggests vessels purposefully target the narrow area at the MPA boundary or "fish the line", a potential acknowledgement of successful spillover. This activity increased significantly during some local fishing seasons. Concentration of activity at MPA boundaries highlights the importance of continuous monitoring at a high spatial and temporal resolution. Reporting of vessel behavior at a fine-scale using radar can help resource managers target enforcement efforts and understand human use patterns near coastal MPAs.


Assuntos
Conservação dos Recursos Naturais , Pesqueiros , Animais , Peixes , Humanos , Radar , Estações do Ano
2.
Sensors (Basel) ; 22(13)2022 Jun 23.
Artigo em Inglês | MEDLINE | ID: mdl-35808256

RESUMO

This research work extends the fixed interval smoothing based on the joint integrated track splitting (FIsJITS) filter in the multi-maneuvering-targets (MMT) tracking environment. We contribute to tackling unknown dynamics of the multi-maneuvering-targets (MMT) using the standard kinematic model. This work is referred to as smoothing MMT using the JITS (MMT-sJITS). The existing FIsJITS algorithm is computationally more complex to solve for the MMT situation because it enumerates a substantial number of measurement-to-track assignments and calculates their posteriori probabilities globally. The MMT-sJITS updates a current target track by assuming the joint (common) measurements detected by neighbor tracks are modified clutters (or pretended spurious measurements). Thus, target measurement concealed by a joint measurement is optimally estimated based on measurement density of the modified clutter. This reduces computational complexity and provides improved tracking performance. The MMT-sJITS generates forward tracks and backward tracks using the measurements collected by a sensor such as a radar. The forward and backward multi-tracks state predictions are fused to obtain priori smoothing multi-track state prediction, as well as their component existence probabilities. This calculates the smoothing estimate required to compute the forward JITS state estimate, which reinforces the MMT tracking efficiently. Monte Carlo simulation is used to verify best false-track discrimination (FTD) analysis in comparison with existing multi-targets tracking algorithms.


Assuntos
Algoritmos , Radar , Método de Monte Carlo , Probabilidade
3.
Sensors (Basel) ; 22(13)2022 Jun 30.
Artigo em Inglês | MEDLINE | ID: mdl-35808455

RESUMO

The development of satellite sensors and interferometry synthetic aperture radar (InSAR) technology has enabled the exploitation of their benefits for long-term structural health monitoring (SHM). However, some restrictions cause this process to provide a small number of images leading to the problem of small data for SAR-based SHM. Conversely, the major challenge of the long-term monitoring of civil structures pertains to variations in their inherent properties by environmental and/or operational variability. This article aims to propose new hybrid unsupervised learning methods for addressing these challenges. The methods in this work contain three main parts: (i) data augmentation by the Markov Chain Monte Carlo algorithm, (ii) feature normalization, and (iii) decision making via Mahalanobis-squared distance. The first method presented in this work develops an artificial neural network-based feature normalization by proposing an iterative hyperparameter selection of hidden neurons of the network. The second method is a novel unsupervised teacher-student learning by combining an undercomplete deep neural network and an overcomplete single-layer neural network. A small set of long-term displacement samples extracted from a few SAR images of TerraSAR-X is applied to validate the proposed methods. The results show that the methods can effectively deal with the major challenges in the SAR-based SHM applications.


Assuntos
Monitoramento Ambiental , Radar , Algoritmos , Monitoramento Ambiental/métodos , Humanos , Interferometria/métodos , Redes Neurais de Computação
4.
Sensors (Basel) ; 22(13)2022 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-35808475

RESUMO

With the widespread use of multifunction radars (MFRs), it is hard for the traditional radar signal recognition technology to meet the needs of current electronic intelligence systems. For signal recognition of an MFR, it is necessary to identify not only the type or individual of the emitter but also its current state. Existing methods identify MFR states through hierarchical modeling, but most of them rely heavily on prior information. In the paper, we focus on the MFR state recognition with actual intercepted MFR signals and develop it by introducing recurrent neural networks (RNNs) of deep learning into the modeling of MFR signals. According to the layered MFR signal architecture, we propose a novel end-to-end state recognition approach with two RNNs' connections. This approach makes full use of RNNs' ability to directly tackle corrupted data and automatically learn the features from input data. So, it is practical and less dependent on prior information. In addition, the hierarchical modeling method applied to the end-to-end network effectively restricts the scale of the end-to-end model so that the model can be trained with a small amount of data. Simulation results on a real MFR show the excellent recognition performance of our end-to-end approach with little prior information.


Assuntos
Aprendizado Profundo , Simulação por Computador , Redes Neurais de Computação , Radar
5.
Sensors (Basel) ; 22(13)2022 Jul 02.
Artigo em Inglês | MEDLINE | ID: mdl-35808504

RESUMO

Rubber is one of the most used materials in the world; however, raw rubber shows a relatively very low mechanical strength. Therefore, it needs to be cured before its ultimate applicatios. Curing process specifications, such as the curing time and temperature, influence the material properties of the final cured product. The transient radar method (TRM) is introduced as an alternative for vulcanization monitoring in this study. Three polyurethane-rubber samples with different curing times of 2, 4, and 5.5 min were studied by TRM to investigate the feasibility and robustness of the TRM in curing time monitoring. Additionally, the mechanical stiffness of the samples was investigated by using a unidirectional tensile test to investigate the potential correlations between curing time, dielectric permittivity, and stiffness. According to the results, the complex permittivity and stiffness of the samples with 2, 4, and 5.5 min of curing time was 17.33 ± 0.07 - (2.41 ± 0.04)j; 17.09 ± 0.05 - (4.90 ± 0.03)j; 23.60 ± 0.05 - (14.06 ± 0.06)j; and 0.29, 0.35, and 0.38 kPa, respectively. Further statistical analyses showed a correlation coefficient of 0.99 (p = 0.06), 0.80 (p = 0.40), and 0.92 (p = 0.25) between curing time-stiffness, curing time-permittivity (real part), and curing time-permittivity (imaginary part), respectively. The correlation coefficient between curing time and permittivity can show the potential of the TRM system in contact-free vulcanization monitoring, as the impact of vulcanization can be tracked by means of TRM.


Assuntos
Radar , Borracha , Poliuretanos , Temperatura
6.
Sensors (Basel) ; 22(14)2022 Jul 13.
Artigo em Inglês | MEDLINE | ID: mdl-35890910

RESUMO

The paper aims to propose a sequence of steps that will allow multi-person tracking with a single UWB radar equipped with the minimal antenna array needed for trilateration. Its localization accuracy is admittedly limited, but on the other hand, thoughtfully chosen placement of antennas can increase the detectability of several humans moving in their immediate vicinity and additionally decrease the computational complexity of the signal processing methods. It is shown that the UWB radar measuring with high rate and fine range resolution in conjunction with properly tuned processing parameters can continually track people even in the case when their radar echoes are crossing or merging. Emphasis is given to the simplified method of the time-of-arrival (TOA) estimation and association and the novel method needed for antenna height compensation. The performance of the proposed human tracking framework is evaluated for the experimental scenario with three people moving closely in a small room. A quantitative analysis of the estimated target tracks confirms the benefits of suggested high antenna placement and application of new signal processing methods in the form of decreasing the mean localization error and increasing the frequency of correct target position estimations.


Assuntos
Radar , Processamento de Sinais Assistido por Computador , Humanos
7.
Sensors (Basel) ; 22(14)2022 Jul 13.
Artigo em Inglês | MEDLINE | ID: mdl-35890928

RESUMO

Ultra-wideband radar application for sleep breathing monitoring is hampered by the difficulty of obtaining breathing signals for non-stationary subjects. This occurs due to imprecise signal clutter removal and poor body movement removal algorithms for extracting accurate breathing signals. Therefore, this paper proposed a Sleep Breathing Detection Algorithm (SBDA) to address this challenge. First, SBDA introduces the combination of variance feature with Discrete Wavelet Transform (DWT) to tackle the issue of clutter signals. This method used Daubechies wavelets with five levels of decomposition to satisfy the signal-to-noise ratio in the signal. Second, SBDA implements a curve fit based sinusoidal pattern algorithm for detecting periodic motion. The measurement was taken by comparing the R-square value to differentiate between chest and body movements. Last but not least, SBDA applied the Ensemble Empirical Mode Decomposition (EEMD) method for extracting breathing signals before transforming the signal to the frequency domain using Fast Fourier Transform (FFT) to obtain breathing rate. The analysis was conducted on 15 subjects with normal and abnormal ratings for sleep monitoring. All results were compared with two existing methods obtained from previous literature with Polysomnography (PSG) devices. The result found that SBDA effectively monitors breathing using IR-UWB as it has the lowest average percentage error with only 6.12% compared to the other two existing methods from past research implemented in this dataset.


Assuntos
Radar , Processamento de Sinais Assistido por Computador , Algoritmos , Frequência Cardíaca , Humanos , Polissonografia , Sono
8.
Sensors (Basel) ; 22(14)2022 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-35890973

RESUMO

This article demonstrates that the complex value of S11 of an antenna, acquired in a multi-monostatic configuration, can be used for localization of a dielectric anomaly hidden inside a dielectric background medium when the antenna is placed close (~5 mm) to the geometry. It uses an Inverse Synthetic Aperture Radar (ISAR) imaging framework where data is acquired at multiple frequencies and look-angles. Initially, near-field scattering data are used for simulation to validate this methodology since the basic derivation of the Multiple Signal Classification (MUSIC) algorithm is based on the plain wave assumption. Later on, from an applications perspective, data acquisition is performed using an antipodal Vivaldi antenna that has eight constant-width slots on each arm. This antenna operates in a frequency range of 1 to 8.5 GHz and its S11 is fed to the 2D MUSIC algorithm with spatial smoothing whereas the antenna artifact and background effect are removed by subtracting the average S11 at each antenna location. Measurements reveal that this methodology gives accurate results with both homogeneous and inhomogeneous backgrounds because the size of data sub-arrays trades between the image noise and resolution, hence reducing the effect of inhomogeneity in the background. In addition to near-field ISAR imaging, this study can be used in the ongoing research on breast tumors and brain stroke detection, among others.


Assuntos
Música , Algoritmos , Simulação por Computador , Diagnóstico por Imagem/métodos , Radar
9.
Sensors (Basel) ; 22(14)2022 Jul 17.
Artigo em Inglês | MEDLINE | ID: mdl-35891019

RESUMO

Multi-target tracking (MTT) is one of the most important functions of radar systems. Traditional multi-target tracking methods based on data association convert multi-target tracking problems into single-target tracking problems. When the number of targets is large, the amount of computation increases exponentially. The Gaussian mixture probability hypothesis density (GM-PHD) filtering based on a random finite set (RFS) provides an effective method to solve multi-target tracking problems without the requirement of explicit data association. However, it is difficult to track targets accurately in real-time with dense clutter and low detection probability. To solve this problem, this paper proposes a multi-feature matching GM-PHD (MFGM-PHD) filter for radar multi-target tracking. Using Doppler and amplitude information contained in radar echo to modify the weights of Gaussian components, the weight of the clutter can be greatly reduced and the target can be distinguished from clutter. Simulations show that the proposed MFGM-PHD filter can improve the accuracy of multi-target tracking as well as the real-time performance with high clutter density and low detection probability.


Assuntos
Radar , Distribuição Normal
10.
Sensors (Basel) ; 22(15)2022 Jul 22.
Artigo em Inglês | MEDLINE | ID: mdl-35897975

RESUMO

Human Activity Recognition (HAR) that includes gait analysis may be useful for various rehabilitation and telemonitoring applications. Current gait analysis methods, such as wearables or cameras, have privacy and operational constraints, especially when used with older adults. Millimeter-Wave (MMW) radar is a promising solution for gait applications because of its low-cost, better privacy, and resilience to ambient light and climate conditions. This paper presents a novel human gait analysis method that combines the micro-Doppler spectrogram and skeletal pose estimation using MMW radar for HAR. In our approach, we used the Texas Instruments IWR6843ISK-ODS MMW radar to obtain the micro-Doppler spectrogram and point clouds for 19 human joints. We developed a multilayer Convolutional Neural Network (CNN) to recognize and classify five different gait patterns with an accuracy of 95.7 to 98.8% using MMW radar data. During training of the CNN algorithm, we used the extracted 3D coordinates of 25 joints using the Kinect V2 sensor and compared them with the point clouds data to improve the estimation. Finally, we performed a real-time simulation to observe the point cloud behavior for different activities and validated our system against the ground truth values. The proposed method demonstrates the ability to distinguish between different human activities to obtain clinically relevant gait information.


Assuntos
Análise da Marcha , Radar , Idoso , Algoritmos , Marcha , Humanos , Aprendizado de Máquina
11.
Environ Monit Assess ; 194(9): 615, 2022 Jul 28.
Artigo em Inglês | MEDLINE | ID: mdl-35900702

RESUMO

Land subsidence problems have become increasingly prominent. Traditional monitoring methods, such as level measurements, have high costs and low efficiency. Permanent scatterer interferometric synthetic aperture radar (PS-InSAR) has several advantages for land subsidence monitoring based on technological innovations. Aimed at resolving the key problems associated with PS-InSAR technology, the accuracy of three external digital elevations models (DEMs, namely, SRTM, ASTER GDEM, and PleiadesDEM) was analysed and compared. We found that the introduction of ground control points can significantly improve the elevation accuracy of DEMs. Herein, we introduce the specific processing steps and selection of the key parameters for IN-SAR data using the StaMPS software. We discuss the differences between IN-SAR technology and levelling measurements as well as the influence that the different external DEMs have on IN-SAR data. Based on 36 scenes of TerraSAR-X images, we obtained results for land deformation monitoring in Taiyuan City using PS-InSAR technology, which provided satisfactory monitoring results.


Assuntos
Monitoramento Ambiental , Radar , Monitoramento Ambiental/métodos
12.
Environ Monit Assess ; 194(8): 589, 2022 Jul 16.
Artigo em Inglês | MEDLINE | ID: mdl-35841453

RESUMO

Identifying hitherto unknown palaeo-channels, especially in the arid regions of the Thar Desert, is crucial since these channels may form excellent aquifers, and are also associated with valuable ore deposits of many precious minerals. This study employed integrated C-band Synthetic Aperture Radar (SAR) of Sentinel-1A and high-resolution multispectral Sentinel-2A data of pre- and post-monsoon seasons (June and November) to delineate playas and palaeo-channels. This approach is the first of its kind for this area. The palaeo-channels were delineated through a detailed visual inspection of colour composite (CC) images of Sentinel-2A data, SAR backscatter (VH) images and fused SAR and optical images. Then, we studied the topographic profiles generated from the Shuttle Radar Topography Mission - Digital Elevation Model (SRTM-DEM) across the identified palaeo-channels, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) to further confirm the existence of a palaeo-channel's course and playas. As a result, several playas and palaeo-channels in the area were successfully identified, some of which were previously unmapped and undetected. The results indicate that the post-monsoon datasets are more useful for the precise delineation of palaeo-channels due to the presence of relatively higher moisture along the palaeo-channels' courses.


Assuntos
Água Subterrânea , Radar , Monitoramento Ambiental/métodos , Índia
13.
Sensors (Basel) ; 22(15)2022 Jul 26.
Artigo em Inglês | MEDLINE | ID: mdl-35898090

RESUMO

Landslide susceptibility maps (LSM) are often used by government departments to carry out land use management and planning, which supports decision makers in urban and infrastructure planning. The accuracy of conventional landslide susceptibility maps is often affected by classification errors. Consequently, they become less reliable, which makes it difficult to meet the needs of decision-makers. Therefore, it is proposed in this paper to reduce classification errors and improve LSM reliability by integrating the Small Baseline Subsets-Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique and LSM. By using the logistic regression model (LR) and the support vector machine model (SVM), experiments were conducted to generate LSM in the Dongchuan district. It was classified into five classes: very high susceptibility, high susceptibility, medium susceptibility, low susceptibility, and very low susceptibility. Then, the surface deformation rate of the Dongchuan area was obtained through the ascending and descending orbit sentinel-1A data from January 2018 to January 2021. To correct the classification errors, the SBAS-InSAR technique was integrated into LSM under the optimal model by constructing the contingency matrix. Finally, the LSMs obtained before and after correction were compared. Moreover, the correction results were validated and analyzed by combining remote sensing images, InSAR deformation results, and field surveys. According to the research results, the susceptibility class of 66,094 classification error cells (59.48 km2) was significantly improved in the LSM after the integration of the SBAS-InSAR correction. The enhanced susceptibility classes and the spectral characteristics of remote sensing images are highly consistent with the trends of InSAR cumulative deformation and the results of field investigation. It is suggested that integrating SBAS-InSAR and LSM is effective in correcting classification errors and further improving the reliability of LSM for landslide prediction. The LSM obtained by using this method plays an important role in guiding local government departments on disaster prevention and mitigation, which is conducive to eliminating the risk of landslides.


Assuntos
Deslizamentos de Terra , China , Deslizamentos de Terra/prevenção & controle , Radar , Reprodutibilidade dos Testes , Máquina de Vetores de Suporte
14.
Biosensors (Basel) ; 12(7)2022 Jul 20.
Artigo em Inglês | MEDLINE | ID: mdl-35884344

RESUMO

Waterless transportation for live grouper is a novel mode of transport that not only saves money, but also lowers wastewater pollution. Technical obstacles remain, however, in achieving intelligent monitoring and a greater survival rate. During live grouper waterless transportation, the stress response is a key indicator that affects the survival life-span of the grouper. Studies based on breathing rate analysis have demonstrated that among many stress response parameters, breathing rate is the most direct parameter to reflect the intensity. Conventional measurement methods, which set up sensors on the gills of groupers, interfere with the normal breathing of living aquatic products and are complex in system design. We designed a new breathing monitoring system based on a completely non-destructive approach. The system allows the real-time monitoring of living aquatic products' breathing rate by simply placing the millimeter wave radar on the inner wall of the incubator and facing the gills. The system we developed can detect more parameters in the future, and can replace the existing system to simplify the study of stress responses.


Assuntos
Técnicas Biossensoriais , Radar , Animais , Peixes , Monitorização Fisiológica/métodos , Respiração
15.
Sci Rep ; 12(1): 12162, 2022 Jul 16.
Artigo em Inglês | MEDLINE | ID: mdl-35842481

RESUMO

Difference far-field patterns represent a way for pin-pointing a target in both azimuth and elevation, extremely useful in radar applications. At the present work, an innovative method for synthesizing good compromise solutions among sum and difference patterns providing low complexity of the antenna feeding network for uniform thinned arrays is addressed. This procedure uses a hybrid version of the Simulated Annealing algorithm (hybrid SA) to optimize a cost function of radiation characteristics for both sum and difference patterns as peak directivity and side lobe level (SLL) while fixing deep nulls. In this framework, examples of half-wavelength spaced linear arrays from 40 to 120 elements were analyzed, as well as an extension to planar arrays by means of separable distributions was developed. The performance of the method is analyzed with different examples and its potential outlined, showing the ability of fixing deep nulls in both sum and difference patterns which share the same uniform excitation relative amplitudes.


Assuntos
Algoritmos , Radar
16.
PLoS One ; 17(7): e0267959, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35895594

RESUMO

A key part of native forest management in designated wood production areas is identifying locations which must be exempt from logging. Forest laws, government regulations, and codes of practice specify where logging is and is not permitted. Assessing compliance with these regulations is critical but can be expensive and time consuming, especially if it entails field measurements. In some cases, spatial data products may help reduce the costs and increase the transparency of assessing compliance. However, different spatial products can vary in their accuracy and resolution, leading to uncertainty in forest management. We present the results of a detailed case study investigating the compliance of logging operations with laws preventing cutting on slopes exceeding 30°. We focused on two designated water catchments in the Australian State of Victoria which supply water to the city of Melbourne. We compared slopes that had been logged on steep terrain using spatial data based on a Digital Elevation Model (DEM) derived from LiDAR, a 1 arc second DEM derived from the Shuttle Radar Topography Mission, and a Digital Terrain Model (DTM) with a resolution of 10m. While our analyses revealed differences in slope measurements among the different spatial products, all three datasets (and the on-site slope measurements) estimated the occurrence of widespread logging of forests on slopes >30° in both water catchments. We found the lowest resolution Shuttle Radar Topography Mission DEM underestimated the steepness of slopes, whilst the DTM was variable in its estimates. As expected, the LiDAR generated slope calculations provided the best fit with on-site measurements. Our study demonstrates the value of spatial data products in assessing compliance with logging laws and codes of practice. We suggest that LiDAR DEMs, and DTMs also can be useful in proactive forest planning and management by helping better identify which areas should be exempt from cutting before logging operations commence.


Assuntos
Florestas , Radar , Austrália , Água
17.
Sci Rep ; 12(1): 10958, 2022 Jun 29.
Artigo em Inglês | MEDLINE | ID: mdl-35768459

RESUMO

Despite their widespread use for performing advanced electromagnetic properties, metamaterial suffers from several restrictions in this technological era. Generally, technology affects the way individuals communicate, learn, think and plays an important role in society today. For this reason, there has been a surge of interest in a coding metamaterial field that possesses the ability to manipulate electromagnetic waves and realize different functionalities. This research work investigates circular-shaped coding metamaterial for microwave frequency applications through several analyses. First, the 1-bit coding metamaterial that is made up of only "0" and "1" elements with 0 and π phase responses by adopting two types of unit cells such as square-shaped Rogers RT6002 substrate material with and without metamaterial structure were analysed in this work. The proposed element '1' successfully manifests several more than 180○ phase responses at several frequency ranges, for instance, 7.35 to 9.48 GHz, 12.87 to 14.25 GHz and 17.49 to 18 GHz (C, X, and Ku-bands), respectively. Besides that, three types of coding sequences were proposed and the radar cross-section (RCS) reduction values of the designs were numerically calculated by utilising Computer Simulation Technology (CST) software. Meanwhile, the single-layered coding metamaterial with 6 lattices was compared with double and triple-layered metamaterial structures. At 2 GHz, the triple-layered structure exhibit reduced RCS values with near to - 30 dBm2 for all coding sequences. Therefore, the transmission coefficient results of the triple-layered coding metamaterial sequences were numerically calculated. Several advanced coding metamaterial designs were constructed and the properties were discussed in terms of RCS values and scattering patterns. Meanwhile, the scattering and effective medium parameters of the unit cell metamaterial structure were also analysed in this work. In a nutshell, the 1-bit coding metamaterial in a controlled sequence can control electromagnetic waves and realize different functionalities.


Assuntos
Radar , Software , Simulação por Computador , Humanos , Micro-Ondas
18.
An Acad Bras Cienc ; 94(suppl 2): e20211207, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35730898

RESUMO

Three SAR-derived observations of dark surface patches along the Northeastern Brazilian coastline by the end of 2019 were misreported in the Brazilian media as oil spill-related. Unfortunately, these observations were misled by false positives or look-alikes. Therefore, this paper aims to technically evaluate these look-alike classes by analyzing image attributes found to be helpful to the identification of ocean targets, including oil spills, rain cells, biofilms, and low wind conditions. We use image augmentation to extend our dataset size and create the probability density function curves. The processing includes image segmentation, optimal attribute extraction, and classification with random forest classifiers. Our results contrast with the open-source oil spill detection system and patch classifier methodology called "RIOSS." Analysis of the feature probability density functions based on optimal attributes is promising since we could capture most of the false positive targets in the three SAR-reported images in 2019. The only exception was the biofilm slick observed on October 28th, where the RIOSS mistakenly classified this organic patch as a low wind region with oil spots. This pitfall is acceptable at this project stage since we had only five biogenic film samples to train the algorithm.


Assuntos
Poluição por Petróleo , Poluentes Químicos da Água , Brasil , Monitoramento Ambiental/métodos , Poluição por Petróleo/análise , Radar , Poluentes Químicos da Água/análise , Vento
19.
Sensors (Basel) ; 22(12)2022 Jun 10.
Artigo em Inglês | MEDLINE | ID: mdl-35746186

RESUMO

The extremely low power transmission levels of ultra-wideband (UWB) technology, alongside its advantageously large bandwidth, make it a prime candidate for being used in numerous healthcare scenarios, which require short-range high-data-rate communications and safe radar-based applications [...].


Assuntos
Radar
20.
Sensors (Basel) ; 22(12)2022 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-35746317

RESUMO

A single-beam radar system cannot adopt a side-looking installation scheme, which is completely perpendicular to the moving direction of the target in an intelligent transportation system (ITS), because of its own limitations. In this paper, a side-looking radar velocity measurement system that utilizes a new signal processing method and multi-channel radar scheme is proposed. Constant false alarm rate (CFAR) and generalized likelihood ratio test (GLRT) detectors are used to detect the data processing results in different stages in order to reduce the false alarm rate of targets. At the same time, a deconvolution-based clutter map algorithm is proposed to solve the problem of clutter interference in the test environment, and its theoretical performance is verified by simulation. Finally, 77 G commercial radar is used to test the system, and the results show that this algorithm can effectively detect and accurately estimate the speed of tangential low-speed targets under clutter interference.


Assuntos
Radar , Processamento de Sinais Assistido por Computador , Algoritmos , Simulação por Computador
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