Results 261 to 270 of about 235,258 (299)

Radar Target Classification by Polarization Properties

Proceedings of the IRE, 1960
The polarization properties of radar targets are studied as a parameter related to, but quite distinct from, echo area. It is found that targets are divided into several different classes. The polarization properties may be measured by rotating a linearly polarized radar antenna around the line of sight, and measuring the complex voltage presented at ...
openaire   +1 more source

Moving Target Classification in Automotive Radar Systems Using Convolutional Recurrent Neural Networks

European Signal Processing Conference, 2018
Moving target classification is a key ingredient to avoid accident in autonomous driving systems. Recently, fast chirp frequency modulated continuous wave (FMCW) radar has been popularly used to recognize moving targets due to its ability to discriminate
Sangtae Kim, Seung-Hee Lee, Seungho Doo, B. Shim   +3 more
semanticscholar   +1 more source

Target Classification for 3D-ISAR Using CNNs

IEEE Transactions on Aerospace and Electronic Systems
In maritime surveillance, inverse synthetic aperture radar (ISAR) is a technique for imaging non-cooperative targets, with classification typically performed by the radar operator.
C. Pui, Brian Ng, L. Rosenberg, T. Cao
semanticscholar   +1 more source

Target classification for air defence radars

IET Seminar on High Resolution Imaging and Target Classification, 2006
Radar is evolving rapidly from being a sensor which detects and tracks targets to a high resolution imaging sensor with target classification capabilities. This paper addresses the techniques being developed for air defence radars. The application of target classification functions in fire control radars which support missile systems and multi-function
openaire   +1 more source

Feature analysis for indoor radar target classification

SPIE Proceedings, 2016
This paper analyzes the spectral features from human beings and indoor clutter for building and tuning Support Vector Machines (SVMs) classifiers for the purpose of classifying stationary human targets. The spectral characteristics were obtained through simulations using Finite Difference Time Domain (FDTD) techniques where the radar cross section (RCS)
Travis D. Bufler, Ram M. Narayanan
openaire   +1 more source

Bispectrum of radar signatures and application to target classification

Radio Science, 1990
The scattering characteristics of a radar target can be specified by its impulse response. The impulse response can be computed using Fourier spectral estimation techniques on samples of the radar scattering obtained at a number of equally spaced frequencies.
Eric K. Walton, Ismail Jouny
openaire   +1 more source

A PointNet-Based CFAR Detection Method for Radar Target Detection in Sea Clutter

IEEE Geoscience and Remote Sensing Letters
Radar target detection on the sea surface is challenging due to the influence of sea clutter. Traditional radar target detection methods cannot model the sea clutter distributions precisely, resulting in poor target detection performance. In this letter,
Xiaolin Chen, Kai Liu, Zhibo Zhang
semanticscholar   +1 more source

Plot based target classification for ATC radars

2015 16th International Radar Symposium (IRS), 2015
Air Traffic Control (ATC) radars are expected today to provide improved performance in terms of maximum range and spatial coverage, while the huge amount of small unwanted flying objects like birds and insects shall not lead to an increased false plot1 and / or false track2 rate. To accomplish these opposite aspects of radar capabilities, the occurring
Christoph Neumann, Hermine Senkowski
openaire   +1 more source

Radar Based Target Detection and Classification

2023 International Conference on Intelligent Systems for Communication, IoT and Security (ICISCoIS), 2023
G Santhanamari, Muni Jyothi Prakash S, Dharshini B, Kousalya S, Akash R   +4 more
openaire   +1 more source

Stochastic resonance and suboptimal radar target classification

SPIE Proceedings, 2010
Stochastic resonance has received significant attention recently in the signal processing community with emphasis on signal detection. The basic notion is that the performance of some suboptimal detectors can be improved by adding independent noise to the measured (and already noise contaminated) observation.
openaire   +1 more source