Results 1 to 10 of about 57,099 (266)

Study on Quantum Radar Detection Probability Based on Flying-Wing Stealth Aircraft. [PDF]

open access: yesSensors (Basel), 2022
The development of quantum radar technology presents a challenge to stealth targets, so it is necessary to study the quantum detection probability. In this study, an analytical expression of the quantum radar cross section (QRCS) for complex targets is ...
Lu S, Meng Z, Huang J, Yi M, Wang Z.
europepmc   +2 more sources

UWB radar detection theory

open access: yes2020 10th International Symposium on Signal, Image, Video and Communications (ISIVC), 2021
In this paper, a study of UWB receivers in terms of detection theory is presented. The UWB radar which is presented in many works previously [1]–[3] has many applications. For road UWB radar application, the receiver based on correlation is the optimum receiver [4]. In fact, it maximizes the probability of detection.
Sakkila, Laila   +4 more
openaire   +2 more sources

Massive MIMO Radar for Target Detection [PDF]

open access: yesIEEE Transactions on Signal Processing, 2020
12 pages, 6 figures, accepted for publication in IEEE Transactions on Signal Processing.
Stefano Fortunati   +4 more
openaire   +3 more sources

FMWC radar for breath detection [PDF]

open access: yes2016 Progress in Electromagnetic Research Symposium (PIERS), 2016
We report on the experimental demonstration of an FMCW radar operating in the 25.7–26.6 GHz range with a repetition rate of 500 sweeps per second. The radar is able to track the breathing rate of an adult human from a distance of 1 meter. The experiments have utilized a 50 second recording window to accurately track the breathing rate.
Suhr, Lau Frejstrup   +2 more
openaire   +1 more source

Radar Target Detection with CNN

open access: yes2021 29th European Signal Processing Conference (EUSIPCO), 2021
Target detection is a fundamental radar application that is traditionally carried out by Constant False Alarm Rate (CFAR) detectors. This paper proposes a Convolutional Neural Network (CNN) based detector (RadCNN) to replace the standard CFAR detectors for a typical pulsed Doppler radar.
openaire   +2 more sources

Animal Lameness Detection With Radar Sensing [PDF]

open access: yesIEEE Geoscience and Remote Sensing Letters, 2018
Lameness is a significant problem for performance horses and farmed animals, with severe impact on animal welfare and treatment costs. Lameness is commonly diagnosed through subjective scoring methods performed by trained veterinary clinicians, but automatic methods using suitable sensors would improve efficiency and reliability.
Aman Shrestha   +9 more
openaire   +1 more source

Tropopause Detected by Radar

open access: yesScience, 1966
The tropopause has been detected by ultrasensitive, narrow-beam, microwave (10.7-centimeter) and ultrahigh-frequency (71.5-cm) radars. Its reflectivity is consistent with that expected theoretically for a refractively turbulent medium. Indications are that the layer is also mechanically turbulent, and that electromagnetic scatter techniques may be used
D, Atlas   +4 more
openaire   +3 more sources

Radar-Based Heart Sound Detection [PDF]

open access: yesScientific Reports, 2018
AbstractThis paper introduces heart sound detection by radar systems, which enables touch-free and continuous monitoring of heart sounds. The proposed measurement principle entails two enhancements in modern vital sign monitoring. First, common touch-based auscultation with a phonocardiograph can be simplified by using biomedical radar systems. Second,
Christoph Will   +8 more
openaire   +2 more sources

Adaptive radar detection

open access: yesElectronics Letters, 1985
In the letter a new adaptive procedure for the detection of a radar target in clutter is described. The procedure is based on the development of linear models for the two hypotheses H0 and H1. Under hypothesis H0, there is no target present, and the received signal is modelled as a regressive process.
Qi-Tu Zwang, S. Haykin
openaire   +1 more source

Home - About - Disclaimer - Privacy