Police Doppler Radar and Motion Sensors

2014 ◽  
pp. 287-302
Keyword(s):  
2020 ◽  
Author(s):  
Susanne Wahlen ◽  
Lorenz Meier ◽  
Gian Darms

<p>We present an operational innovative early warning system for real-time rockfall detection with automatic road closure and simultaneous slope monitoring for a rockfall prone section of Axenstrasse in Central Switzerland. The comprehensive monitoring system combines various technologies, including interferometric radar, Doppler radar, seismic sensors, high-resolution deformation cameras, combi-motion sensors and various webcams, to achieve maximum detection reliability at minimal closing time for waiting traffic.</p><p>The Axenstrasse is a scenic road section along Lake Lucerne with an average traffic volume of 16,000 vehicles a day. On 18 July 2019, heavy rainfall triggered a small debris flow in the steep Gumpisch valley and released a large boulder. The 12-ton boulder crossed the road fortunately without causing any significant damage. The road operator closed the route immediately for safety reasons; large debris accumulations of a previous rockfall remained in the upper Gumpisch valley and further similar events are very likely. In an effort to reopen the important traffic axis as soon as possible, we developed, installed and commissioned an alarm system with automatic traffic control within only a few weeks.</p><p>The system combines two different types of technologies: First, sensors for real-time detection of fast movements and second, techniques for long-term monitoring of surface deformation. For reliable rockfall detection, we use a combination of long-range Doppler radar technology and high-sensitivity seismic sensors to minimize false alarm rates while maintaining high probability of detection. The rockfall radar remotely detects moving debris or large boulders whereas the seismic sensors recognise rockfall based on ground motion. Both technologies work in real time and independent of visibility conditions (day/night, fog, snowfall). At a suitable rock spur, we installed two rockfall radars, one facing up and one down the valley, and three seismic sensors in an array.</p><p>Given the short warning time of around 20-30 seconds, it is vital to close the road immediately once an event is detected. However, many events remain small and never reach the road. In order to avoid unnecessary road closures for minor events, we equipped the protection nets above the road with combi-motion sensors that automatically detect an impact by a boulder or a debris flow passage. The system automatically reopens the road after 2 minutes, if an event was detected in the upper part, but no impact was recorded in the nets. In this way, we can guarantee road safety and avoid long closure times. </p><p>For long-term slope monitoring, we installed an interferometric radar with autonomous power supply for permanent, sub-mm monitoring of the rock face where rockfall initially occurred. Further, two deformation cameras observe the gully and provide daily surface deformation analyses through automatic comparison of high-resolution imagery. This type of data allows to identify unstable zones and detect a potential acceleration early.</p><p>All sensor data and camera imagery are continuously transmitted to an online data portal for user access at any time via PC, tablet or smartphone.</p>


Author(s):  
H. Järvinen ◽  
K. Salonen ◽  
M. Lindskog ◽  
A. Huuskonen ◽  
S. Niemelä ◽  
...  
Keyword(s):  

1971 ◽  
Author(s):  
H. W. Prinsen ◽  
R. H. Jarvis ◽  
S. G. Margolis

2018 ◽  
Vol 146 (8) ◽  
pp. 2483-2502 ◽  
Author(s):  
Howard B. Bluestein ◽  
Kyle J. Thiem ◽  
Jeffrey C. Snyder ◽  
Jana B. Houser

Abstract This study documents the formation and evolution of secondary vortices associated within a large, violent tornado in Oklahoma based on data from a close-range, mobile, polarimetric, rapid-scan, X-band Doppler radar. Secondary vortices were tracked relative to the parent circulation using data collected every 2 s. It was found that most long-lived vortices (those that could be tracked for ≥15 s) formed within the radius of maximum wind (RMW), mainly in the left-rear quadrant (with respect to parent tornado motion), passing around the center of the parent tornado and dissipating closer to the center in the right-forward and left-forward quadrants. Some secondary vortices persisted for at least 1 min. When a Burgers–Rott vortex is fit to the Doppler radar data, and the vortex is assumed to be axisymmetric, the secondary vortices propagated slowly against the mean azimuthal flow; if the vortex is not assumed to be axisymmetric as a result of a strong rear-flank gust front on one side of it, then the secondary vortices moved along approximately with the wind.


Author(s):  
Pallab Kumar Gogoi ◽  
Mrinal Kanti Mandal ◽  
Ayush Kumar ◽  
Tapas Chakravarty

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3588
Author(s):  
Yuki Iwata ◽  
Han Trong Thanh ◽  
Guanghao Sun ◽  
Koichiro Ishibashi

Heart rate measurement using a continuous wave Doppler radar sensor (CW-DRS) has been applied to cases where non-contact detection is required, such as the monitoring of vital signs in home healthcare. However, as a CW-DRS measures the speed of movement of the chest surface, which comprises cardiac and respiratory signals by body motion, extracting cardiac information from the superimposed signal is difficult. Therefore, it is challenging to extract cardiac information from superimposed signals. Herein, we propose a novel method based on a matched filter to solve this problem. The method comprises two processes: adaptive generation of a template via singular value decomposition of a trajectory matrix formed from the measurement signals, and reconstruction by convolution of the generated template and measurement signals. The method is validated using a dataset obtained in two different experiments, i.e., experiments involving supine and seated subject postures. Absolute errors in heart rate and standard deviation of heartbeat interval with references were calculated as 1.93±1.76bpm and 57.0±28.1s for the lying posture, and 9.72±7.86bpm and 81.3±24.3s for the sitting posture.


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