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Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement
Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement
Autore Kobayashi Hirokazu
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 online resource (570 p.)
Soggetto topico History of engineering and technology
Soggetto non controllato 2-D PPS
3-D deformation
adaptive reduced method
aircraft surveillance
altitude measurement accuracy
analytical approach
antenna array
atomic norm
automatic guided vehicle
Bayesian inversion
bistatic inverse synthetic aperture radar
bistatic MIMO radar
block coherence measure
block sparse Bayesian learning
CLEAN technique
clustering methods
clutter reduction
clutter suppression
coherent integration
coherent pulse trains
comprehensive SAR
conductivity
constant modulus sequences
constitutive parameters
contrast target detection
correlation properties
Cramer-Rao lower bound
critical height
crosshole ground penetrating radar (GPR)
curved orbit
deception jamming
dechirping
denoising detection
deramping-based approach
differential SAR tomography
dilation morphology
direct position determination
discrete cosine transform (DCT)
discrete scatterer model
DOA estimation
DoA/DoD estimation
DOD/DOA estimation
Doppler
Doppler rate
doppler tolerance
double negative
dual-band
dual-polarized radar
electromagnetic wave attribute
energy spectrum method
entropy thresholding
FMCW radio altimeter
forward model
fractional Fourier transform (FRFT)
frequency shifting modulation
generative adversarial nets
generator and discriminator
GPR
guided filter
height pulses
high reliability
high switching speed
hyperbolic tangent function
image fusion
image processing
integral cubic phase function (ICPF)
interrupted sampling
interrupted transmitting and receiving (ITR)
inverse synthetic aperture ladar (ISAL)
inverse synthetic aperture radar (ISAR)
ISAR
K-L transform
least square error
linear geometry distortion
local correlation
local gradient method
low control voltage
low-rank approximation
lunar penetrating radar
man-made targets
maneuvering target
maneuvering target detection
marine radar
maritime traffic monitoring
Markov chain Monte Carlo (MCMC)
maximum likelihood estimator
metamaterial absorber
methodological error
micro-Doppler
micro-motion feature extraction
microwave imaging
MIMO radar
modeling error
motion parameter estimation
multiparametric SAR observation
multipath ghost suppression
mutual coupling
n/a
narrowband interference separation
non-uniform fast Fourier transform (NUFFT)
non-uniform grid
off-grid sparse problem
orthogonal matching pursuit
parameter estimation
passive bistatic radar
PBR (passive bistatic radar)
permittivity
phased array radar
polarimetric decomposition
prior information
pulse radar
radar echo cancellation
radar jamming
radon transform
relative water content
remote sensing
RF MEMS
rotating target
S-transformation
saliency detection
saliency preprocessing LLC
SAR
scene classification
seasonal permafrost
second-order phase difference (SoPD)
seislet transform
sensing matrix optimization
series reversion
simultaneous polarimetric radar
single moving sensor
singular value decomposition (SVD)
small wind streak
SNR
spaceborne
sparse recovery
sparse representation
speckle noise filtering
squinted SAR
subspace extraction
switch
synchrosqueezing
synthetic aperture radar
synthetic aperture radar (SAR)
Synthetic Aperture Radar (SAR)
through-wall imaging
through-wall radar imaging
time-frequency analysis
tomography
ultra-wide frequency deviation
ultrahigh resolution
unmanned aerial vehicle
wake detection and analysis
wideband noise interference
wind direction retrieval
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557305803321
Kobayashi Hirokazu  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) / John Ball, Bo Tang
Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) / John Ball, Bo Tang
Autore Ball John
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (344 p.)
Soggetto topico History of engineering and technology
Soggetto non controllato FPGA
recurrence plot (RP)
residual learning
neural networks
driver monitoring
navigation
depthwise separable convolution
optimization
dynamic path-planning algorithms
object tracking
sub-region
cooperative systems
convolutional neural networks
DSRC
VANET
joystick
road scene
convolutional neural network (CNN)
multi-sensor
p-norm
occlusion
crash injury severity prediction
deep leaning
squeeze-and-excitation
electric vehicles
perception in challenging conditions
T-S fuzzy neural network
total vehicle mass of the front vehicle
electrocardiogram (ECG)
communications
generative adversarial nets
camera
adaptive classifier updating
Vehicle-to-X communications
convolutional neural network
predictive
Geobroadcast
infinity norm
urban object detector
machine learning
automated-manual transition
red light-running behaviors
photoplethysmogram (PPG)
panoramic image dataset
parallel architectures
visual tracking
autopilot
ADAS
kinematic control
GPU
road lane detection
obstacle detection and classification
Gabor convolution kernel
autonomous vehicle
Intelligent Transport Systems
driving decision-making model
Gaussian kernel
autonomous vehicles
enhanced learning
ethical and legal factors
kernel based MIL algorithm
image inpainting
fusion
terrestrial vehicle
driverless
drowsiness detection
map generation
object detection
interface
machine vision
driving assistance
blind spot detection
deep learning
relative speed
autonomous driving assistance system
discriminative correlation filter bank
recurrent neural network
emergency decisions
LiDAR
real-time object detection
vehicle dynamics
path planning
actuation systems
maneuver algorithm
autonomous driving
smart band
the emergency situations
two-wheeled
support vector machine model
global region
biological vision
automated driving
ISBN 9783039213764
3039213768
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910367757403321
Ball John  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui