scholarly journals Automotive Radar in a UAV to Assess Earth Surface Processes and Land Responses

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4463
Author(s):  
Christoph Weber ◽  
Johannes von Eichel-Streiber ◽  
Jesús Rodrigo-Comino ◽  
Jens Altenburg ◽  
Thomas Udelhoven
Keyword(s):  
Earth Science ◽  
Low Cost ◽  
Science Research ◽  
Radar Data ◽  
Current Status ◽  
Automotive Radar ◽  
Vast Number ◽  
Radar Sensors ◽  
Before And After ◽  
Insight Into

The use of unmanned aerial vehicles (UAVs) in earth science research has drastically increased during the last decade. The reason being innumerable advantages to detecting and monitoring various environmental processes before and after certain events such as rain, wind, flood, etc. or to assess the current status of specific landforms such as gullies, rills, or ravines. The UAV equipped sensors are a key part to success. Besides commonly used sensors such as cameras, radar sensors are another possibility. They are less known for this application, but already well established in research. A vast number of research projects use professional radars, but they are expensive and difficult to handle. Therefore, the use of low-cost radar sensors is becoming more relevant. In this article, to make the usage of radar simpler and more efficient, we developed with automotive radar technology. We introduce basic radar techniques and present two radar sensors with their specifications. To record the radar data, we developed a system with an integrated camera and sensors. The weight of the whole system is about 315 g for the small radar and 450 g for the large one. The whole system was integrated into a UAV and test flights were performed. After that, several flights were carried out, to verify the system with both radar sensors. Thereby, the records provide an insight into the radar data. We demonstrated that the recording system works and the radar sensors are suitable for the usage in a UAV and future earth science research because of its autonomy, precision, and lightweight.

scholarly journals Automotive radar – investigation of mutual interference mechanisms

2010 ◽  
Vol 8 ◽  
pp. 55-60 ◽  
Author(s):  
M. Goppelt ◽  
H.-L. Blöcher ◽  
W. Menzel
Keyword(s):  
Integrated Circuits ◽  
Silicon Germanium ◽  
High Performance ◽  
Low Cost ◽  
Mutual Interference ◽  
Current Status ◽  
Automotive Radar ◽  
Joint Project ◽  
Radar Sensors ◽  
On Chip

Abstract. In the past mutual interference between automotive radar sensors has not been regarded as a major problem. With an increasing number of such systems, however, this topic is receiving more and more attention. The investigation of mutual interference and countermeasures is therefore one topic of the joint project "Radar on Chip for Cars" (RoCC) funded by the German Federal Ministry of Education and Research (BMBF). RoCC's goal is to pave the way for the development of high-performance, low-cost 79 GHz radar sensors based on Silicon-Germanium (SiGe) Monolithic Microwave Integrated Circuits (MMICs). This paper will present some generic interference scenarios and report on the current status of the analysis of interference mechanisms.

scholarly journals Constraint-Based Hierarchical Cluster Selection in Automotive Radar Data

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3410
Author(s):  
Claudia Malzer ◽  
Marcus Baum
Keyword(s):  
Moving Objects ◽  
Hierarchical Cluster ◽  
Autonomous Driving ◽  
Radar Data ◽  
Background Information ◽  
Automotive Radar ◽  
Data Set ◽  
Radar Sensors ◽  
Small Clusters ◽  
Cluster Level

High-resolution automotive radar sensors play an increasing role in detection, classification and tracking of moving objects in traffic scenes. Clustering is frequently used to group detection points in this context. However, this is a particularly challenging task due to variations in number and density of available data points across different scans. Modified versions of the density-based clustering method DBSCAN have mostly been used so far, while hierarchical approaches are rarely considered. In this article, we explore the applicability of HDBSCAN, a hierarchical DBSCAN variant, for clustering radar measurements. To improve results achieved by its unsupervised version, we propose the use of cluster-level constraints based on aggregated background information from cluster candidates. Further, we propose the application of a distance threshold to avoid selection of small clusters at low hierarchy levels. Based on exemplary traffic scenes from nuScenes, a publicly available autonomous driving data set, we test our constraint-based approach along with other methods, including label-based semi-supervised HDBSCAN. Our experiments demonstrate that cluster-level constraints help to adjust HDBSCAN to the given application context and can therefore achieve considerably better results than the unsupervised method. However, the approach requires carefully selected constraint criteria that can be difficult to choose in constantly changing environments.

scholarly journals Mapping Damage-Affected Areas after Natural Hazard Events Using Sentinel-1 Coherence Time Series

2018 ◽  
Vol 10 (8) ◽  
pp. 1272 ◽  
Author(s):  
Stephanie Olen ◽  
Bodo Bookhagen
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Natural Hazard ◽  
Low Cost ◽  
Region Of Interest ◽  
Radar Data ◽  
Coherence Time ◽  
Rapid Identification ◽  
Before And After ◽  
Event Distribution

The emergence of the Sentinel-1A and 1B satellites now offers freely available and widely accessible Synthetic Aperture Radar (SAR) data. Near-global coverage and rapid repeat time (6–12 days) gives Sentinel-1 data the potential to be widely used for monitoring the Earth’s surface. Subtle land-cover and land surface changes can affect the phase and amplitude of the C-band SAR signal, and thus the coherence between two images collected before and after such changes. Analysis of SAR coherence therefore serves as a rapidly deployable and powerful tool to track both seasonal changes and rapid surface disturbances following natural disasters. An advantage of using Sentinel-1 C-band radar data is the ability to easily construct time series of coherence for a region of interest at low cost. In this paper, we propose a new method for Potentially Affected Area (PAA) detection following a natural hazard event. Based on the coherence time series, the proposed method (1) determines the natural variability of coherence within each pixel in the region of interest, accounting for factors such as seasonality and the inherent noise of variable surfaces; and (2) compares pixel-by-pixel syn-event coherence to temporal coherence distributions to determine where statistically significant coherence loss has occurred. The user can determine to what degree the syn-event coherence value (e.g., 1st, 5th percentile of pre-event distribution) constitutes a PAA, and integrate pertinent regional data, such as population density, to rank and prioritise PAAs. We apply the method to two case studies, Sarpol-e, Iran following the 2017 Iran-Iraq earthquake, and a landslide-prone region of NW Argentina, to demonstrate how rapid identification and interpretation of potentially affected areas can be performed shortly following a natural hazard event.

scholarly journals Pedestrian recognition using automotive radar sensors

2012 ◽  
Vol 10 ◽  
pp. 45-55 ◽  
Author(s):  
A. Bartsch ◽  
F. Fitzek ◽  
R. H. Rasshofer
Keyword(s):  
Machine Learning ◽  
Elevation Angle ◽  
Real Life ◽  
Doppler Frequency ◽  
Radar Data ◽  
Limiting Factors ◽  
Automotive Radar ◽  
Signal Processing Algorithm ◽  
Radar Sensors ◽  
The Impact

Abstract. The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.

Low-cost fully integrated BiCMOS transceiver for pulsed 24-GHz automotive radar sensors

2008 ◽  
Author(s):  
L. Moquillon ◽  
P. Garcia ◽  
S. Pruvost ◽  
S. Le Tual ◽  
M. Marchetti ◽  
...  
Keyword(s):  
Low Cost ◽  
Automotive Radar ◽  
Fully Integrated ◽  
Radar Sensors ◽  
24 Ghz

Low-cost eWLB packaging for automotive radar MMICs in the 76–81 GHz range

2013 ◽  
Vol 5 (1) ◽  
pp. 25-34 ◽  
Author(s):  
J. Böck ◽  
M. Wojnowski ◽  
C. Wagner ◽  
H. Knapp ◽  
W. Hartner ◽  
...  
Keyword(s):  
System Integration ◽  
Low Cost ◽  
Wafer Level ◽  
Automotive Radar ◽  
Package Design ◽  
Radar Sensors ◽  
Radar Systems ◽  
Plastic Package ◽  
Rf Performance ◽  
Near Future

Embedded wafer-level ball grid array (eWLB) is investigated as a low-cost plastic package for automotive radar applications in the 76–81 GHz range. Low transmission losses from chip to package and board are achieved by appropriate circuit and package design. Special measures are taken to effectively remove the heat from the package and to optimize the package process to achieve automotive quality targets. A 77 GHz radar chip set in eWLB package is developed, which can be applied on the system board using standard solder reflow assembly. These radar MMICs provide excellent radio frequency (RF) performance for the next generation automotive radar sensors. The potential for even higher system integration is shown by a radar transceiver with antennas integrated in the eWLB package. These results demonstrate that eWLB technology is an attractive candidate to realize low-cost radar systems and to enable radar safety affordable for everyone in the near future.

IMIKO-Radar Project: Laboratory Interference Measurements of Automotive Radar Sensors

2020 ◽  
Author(s):  
Alicja Ossowska ◽  
Leen Sit ◽  
Sarath Manchala ◽  
Thomas Vogler ◽  
Kevin Krupinski ◽  
...  
Keyword(s):  
Automotive Radar ◽  
Radar Sensors ◽  
Interference Measurements

Antibacterial and Anti-Biofilm Biosynthesised Silver and Gold Nanoparticles for Medical Applications: Mechanism of Action, Toxicity and Current Status

2020 ◽  
Vol 17 (2) ◽  
pp. 88-100 ◽  
Author(s):  
Sundos Suleman Ismail Abdalla ◽  
Haliza Katas ◽  
Fazren Azmi ◽  
Mohd Fauzi Mh Busra
Keyword(s):  
Gold Nanoparticles ◽  
Synthesis Method ◽  
Chemical Characterization ◽  
Current Status ◽  
Silver And Gold Nanoparticles ◽  
Physical And Chemical Characterization ◽  
Biosynthesized Agnps ◽  
Physical And Chemical ◽  
Insight Into ◽  
Bio Synthesis

Fast progress in nanoscience and nanotechnology has contributed to the way in which people diagnose, combat, and overcome various diseases differently from the conventional methods. Metal nanoparticles, mainly silver and gold nanoparticles (AgNPs and AuNPs, respectively), are currently developed for many applications in the medical and pharmaceutical area including as antibacterial, antibiofilm as well as anti-leshmanial agents, drug delivery systems, diagnostics tools, as well as being included in personal care products and cosmetics. In this review, the preparation of AgNPs and AuNPs using different methods is discussed, particularly the green or bio- synthesis method as well as common methods used for their physical and chemical characterization. In addition, the mechanisms of the antimicrobial and anti-biofilm activity of AgNPs and AuNPs are discussed, along with the toxicity of both nanoparticles. The review will provide insight into the potential of biosynthesized AgNPs and AuNPs as antimicrobial nanomaterial agents for future use.

Upcoming Drifts In Bio-Similars

2020 ◽  
Vol 15 ◽  
Author(s):  
Geeta Aggarwal ◽  
Manju Nagpal ◽  
Ameya Sharma ◽  
Vivek Puri ◽  
Gitika Arora Dhingra
Keyword(s):  
Metabolic Diseases ◽  
Market Competition ◽  
Current Status ◽  
Medicinal Products ◽  
The Past ◽  
Biologic Activity ◽  
Emerging Trends ◽  
Regulatory Guidelines ◽  
Food Drug Administration ◽  
Insight Into

Background: Biopharmaceuticals such as Biologic medicinal products have been in clinical use over the past three decades and have benefited towards the therapy of degenerative and critical metabolic diseases. It is forecasted that market of biologics will be going to increase at a rate of 20% per year, and by 2025, more than ˃ 50% of new drug approvals may be biological products. The increasing utilization of the biologics necessitates for cost control, especially for innovators products that have enjoyed a lengthy period of exclusive use. As the first wave of biopharmaceuticals is expired or set to expire, it has led to various opportunities for the expansion of bio-similars i.e. copied versions of original biologics with same biologic activity. Development of biosimilars is expected to promote market competition, meet worldwide demand, sustain the healthcare systems and maintain the incentives for innovation. Methods: Appraisal of published articles from peer reviewed journals, PubMed literature, latest news and guidelines from European Medicine Agency, US Food Drug Administration (FDA) and India are used to identify data for review. Results: Main insight into the quality requirements concerning biologics, current status of regulation of biosimilars and upcoming challenges lying ahead for the upgrading of marketing authorization of bio-similars has been incorporated. Compiled literature on therapeutic status, regulatory guidelines and the emerging trends and opportunities of biosimilars has been thoroughly stated. Conclusion: Updates on biosimilars will support to investigate the possible impact of bio-similars on healthcare market.

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