60 research outputs found

    Novel post-Doppler STAP with a priori knowledge information for traffic monitoring applications

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    The road traffic has worsened over time in most cities, and the methods employed for monitoring and counting the vehicles on the roads (e.g., cameras, induction loops, or even people manually counting) are expensive and limited in spatial coverage. Synthetic aperture radars (SAR) provide an effective solution for this problem due to the wide-area coverage and the independence from daylight and weather conditions. Special attention is given in case of large scale events or catastrophes, when mobile internet is unavailable and phone communication is impossible. In this particular scenario, the traffic monitoring with real-time information ensures the safety of the road users and can even save lives. For that reason, this paper presents a novel a priori knowledge-based algorithm for traffic monitoring, where the powerful post-Doppler space-time adaptive processing (PD STAP) is combined with a road network obtained from the freely available OpenStreetMap (OSM) database. The incorporation of a known road network into the processing chain presents great potential for real-time processing, since only the acquired data related to the roads need to be processed. As a result, decreased processing hardware complexity and low costs compared to state-of-the-art systems can be achieved. In addition, it is a promising solution for detecting effectively the road vehicles and estimating their positions, velocities and moving directions with high accuracy. The PD STAP is well-known for its very good clutter suppression, its sensitivity also to low vehicle velocities, and its accurate target position estimation capabilities. The road information is applied after the PD STAP, where the OSM database fused with a digital elevation model (DEM) is applied in order to recognize and to reject false detections, and moreover, to reposition the vehicles detected in the vicinity of the roads. In other words, the distance between the estimated position of the target and its closest road point is measured and compared to a relocation threshold for deciding whether the target corresponds to a true road vehicle or to a false detection. If the first condition is fulfilled, the target is repositioned to its closest road point; otherwise it is discarded. The relocation threshold is computed adaptively for each detection by using an appropriate performance model. The proposed algorithm was tested using real 4-channel aperture switching data acquired by DLR’s airborne system F-SAR. In the radar data takes examined so far, the PD STAP detected vehicles as slow as 7 km/h, with an overall position estimation accuracy better than 10 m. Besides, the estimated velocities of the vehicles were in very good agreement with the differential GPS reference data. To sum up, the experimental results revealed a powerful algorithm that detects even slow vehicles and discards most of the false detections, being suitable for many traffic monitoring applications. We will not limit our further investigations to the data takes whose results are shown in this paper. We have a large pool of multi-channel F-SAR data takes containing real highway traffic scenarios with dozens or even hundreds of vehicles

    Multi-Channel Calibration for Airborne PostDoppler Space-Time Adaptive Processing

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    This paper presents a fast and efficient multichannel calibration algorithm for along-track systems, which in particular is evaluated for the post-Doppler space-time adaptive processing (PD STAP) technique. The calibration algorithm corrects the phase and magnitude offsets among the receiving channels, estimates and compensates the Doppler centroid variation caused by atmospheric turbulences by using the attitude angles of the antenna array. Important parameters and offsets are estimated directly from the radar rangecompressed data. The proposed algorithm is compared with the state-of-the-art Digital Channel Balancing technique based on real multi-channel X-band data acquired by the DLR’s airborne system F-SAR. The experimental results are shown and discussed in the frame of traffic monitoring applications

    Motion Compensation for Accurate Position Estimation of Ground Moving Targets using the Multi-Channel Airborne System DBFSAR

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    The accurate estimation of the target’s position on the ground is a crucial step for air-based surveillance systems. For the particular case of radar systems with multiple receive channels, the target’s position on the ground can be accurate-ly obtained after estimating its direction-of-arrival (DOA) angle. The problem is that, in practice, the aircraft’s motion tilts the antenna array and introduces undesired phase differences among the receive channels. Consequently, the DOA angle estimation accuracy can be severely impacted. This paper presents a fast and robust algorithm for correcting the undesired phases differences introduced by the aircraft’s motion among the multiple receive channels. The proposed algorithm is tested and validated using simulated radar data as well as radar data acquired with the DLR’s new multi-channel airborne system digital beamforming SAR (DBFSAR)

    Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

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    © The Author(s) 2018. Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups

    Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

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    Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

    Rising rural body-mass index is the main driver of the global obesity epidemic in adults

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    Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe
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