Abstract: For the past couple of decades Weak signal detection
is of crucial importance in various engineering and scientific
applications. It finds its application in areas like Wireless
communication, Radars, Aerospace engineering, Control systems and
many of those. Usually weak signal detection requires phase sensitive
detector and demodulation module to detect and analyze the signal.
This article gives you a preamble to intrusion detection system which
can effectively detect a weak signal from a multiplexed signal. By
carefully inspecting and analyzing the respective signal, this
system can successfully indicate any peripheral intrusion. Intrusion
detection system (IDS) is a comprehensive and easy approach
towards detecting and analyzing any signal that is weakened and
garbled due to low signal to noise ratio (SNR). This approach
finds significant importance in applications like peripheral security
systems.
Abstract: We constructed a method of phase unwrapping for a typical wave-front by utilizing the maximizer of the posterior marginal (MPM) estimate corresponding to equilibrium statistical mechanics of the three-state Ising model on a square lattice on the basis of an analogy between statistical mechanics and Bayesian inference. We investigated the static properties of an MPM estimate from a phase diagram using Monte Carlo simulation for a typical wave-front with synthetic aperture radar (SAR) interferometry. The simulations clarified that the surface-consistency conditions were useful for extending the phase where the MPM estimate was successful in phase unwrapping with a high degree of accuracy and that introducing prior information into the MPM estimate also made it possible to extend the phase under the constraint of the surface-consistency conditions with a high degree of accuracy. We also found that the MPM estimate could be used to reconstruct the original wave-fronts more smoothly, if we appropriately tuned hyper-parameters corresponding to temperature to utilize fluctuations around the MAP solution. Also, from the viewpoint of statistical mechanics of the Q-Ising model, we found that the MPM estimate was regarded as a method for searching the ground state by utilizing thermal fluctuations under the constraint of the surface-consistency condition.
Abstract: A challenging problem in radar signal processing is to
achieve reliable target detection in the presence of interferences. In
this paper, we propose a novel algorithm for automatic censoring of
radar interfering targets in log-normal clutter. The proposed
algorithm, termed the forward automatic censored cell averaging
detector (F-ACCAD), consists of two steps: removing the corrupted
reference cells (censoring) and the actual detection. Both steps are
performed dynamically by using a suitable set of ranked cells to
estimate the unknown background level and set the adaptive
thresholds accordingly. The F-ACCAD algorithm does not require
any prior information about the clutter parameters nor does it require
the number of interfering targets. The effectiveness of the F-ACCAD
algorithm is assessed by computing, using Monte Carlo simulations,
the probability of censoring and the probability of detection in
different background environments.
Abstract: Human immunodeficiency virus infection and
acquired immunodeficiency syndrome is a global pandemic with
cases reporting from virtually every country and continues to be a
common infection in developing country like India.
Microalbuminuria is a manifestation of human immunodeficiency
virus associated nephropathy. Therefore, microalbuminuria may be
an early marker of human immunodeficiency virus associated
nephropathy, and screening for its presence may be beneficial. A
strikingly high prevalence of microalbuminuria among human
immunodeficiency virus infected patients has been described in
various studies. Risk factors for clinically significant proteinuria
include African - American race, higher human immunodeficiency
virus ribonucleic acid level and lower CD4 lymphocyte count. The
cardiovascular risk factors of increased systolic blood pressure and
increase fasting blood sugar level are strongly associated with
microalbuminuria in human immunodeficiency virus patient. These
results suggest that microalbuminuria may be a sign of current
endothelial dysfunction and micro-vascular disease and there is
substantial risk of future cardiovascular disease events. Positive
contributing factors include early kidney disease such as human
immunodeficiency virus associated nephropathy, a marker of end
organ damage related to co morbidities of diabetes or hypertension,
or more diffuse endothelial cells dysfunction. Nevertheless after
adjustment for non human immunodeficiency virus factors, human
immunodeficiency virus itself is a major risk factor. The presence of
human immunodeficiency virus infection is independent risk to
develop microalbuminuria in human immunodeficiency virus patient.
Cardiovascular risk factors appeared to be stronger predictors of
microalbuminuria than markers of human immunodeficiency virus
severity person with human immunodeficiency virus infection and
microalbuminuria therefore appear to potentially bear the burden of
two separate damage related to known vascular end organ damage
related to know vascular risk factors, and human immunodeficiency
virus specific processes such as the direct viral infection of kidney
cells.The higher prevalence of microalbuminuria among the human
immunodeficiency virus infected could be harbinger of future
increased risks of both kidney and cardiovascular disease. Further
study defining the prognostic significance of microalbuminuria
among human immunodeficiency virus infected persons will be
essential. Microalbuminuria seems to be a predictor of cardiovascular
disease in diabetic and non diabetic subjects, hence it can also be
used for early detection of micro vascular disease in human
immunodeficiency virus positive patients, thus can help to diagnose
the disease at the earliest.
Abstract: An image texture analysis and target recognition approach of using an improved image texture feature coding method (TFCM) and Support Vector Machine (SVM) for target detection is presented. With our proposed target detection framework, targets of interest can be detected accurately. Cascade-Sliding-Window technique was also developed for automated target localization. Application to mammogram showed that over 88% of normal mammograms and 80% of abnormal mammograms can be correctly identified. The approach was also successfully applied to Synthetic Aperture Radar (SAR) and Ground Penetrating Radar (GPR) images for target detection.
Abstract: Safer driver behavior promoting is the main goal of this paper. It is a fact that drivers behavior is relatively safer when being monitored. Thus, in this paper, we propose a monitoring system to report specific driving event as well as the potentially aggressive events for estimation of the driving performance. Our driving monitoring system is composed of two parts. The first part is the in-vehicle embedded system which is composed of a GPS receiver, a two-axis accelerometer, radar sensor, OBD interface, and GPRS modem. The design considerations that led to this architecture is described in this paper. The second part is a web server where an adaptive hierarchical fuzzy system is proposed to classify the driving performance based on the data that is sent by the in-vehicle embedded system and the data that is provided by the geographical information system (GIS). Our system is robust, inexpensive and small enough to fit inside a vehicle without distracting the driver.
Abstract: Field mapping activity for an active volcano mainly in
the Torrid Zone is usually hampered by several problems such as steep
terrain and bad atmosphere conditions. In this paper we present a
simple solution for such problem by a combination Synthetic Aperture
Radar (SAR) and geostatistical methods. By this combination, we
could reduce the speckle effect from the SAR data and then estimate
roughness distribution of the pyroclastic flow deposits. The main
purpose of this study is to detect spatial distribution of new pyroclastic
flow deposits termed as P-zone accurately using the β°data from two
RADARSAT-1 SAR level-0 data. Single scene of Hyperion data and
field observation were used for cross-validation of the SAR results.
Mt. Merapi in central Java, Indonesia, was chosen as a study site and
the eruptions in May-June 2006 were examined. The P-zones were
found in the western and southern flanks. The area size and the longest
flow distance were calculated as 2.3 km2 and 6.8 km, respectively. The
grain size variation of the P-zone was mapped in detail from fine to
coarse deposits regarding the C-band wavelength of 5.6 cm.
Abstract: This paper describes a novel projection algorithm, the Projection Onto Span Algorithm (POSA) for wavelet-based superresolution and removing speckle (in wavelet domain) of unknown variance from Synthetic Aperture Radar (SAR) images. Although the POSA is good as a new superresolution algorithm for image enhancement, image metrology and biometric identification, here one will use it like a tool of despeckling, being the first time that an algorithm of super-resolution is used for despeckling of SAR images. Specifically, the speckled SAR image is decomposed into wavelet subbands; POSA is applied to the high subbands, and reconstruct a SAR image from the modified detail coefficients. Experimental results demonstrate that the new method compares favorably to several other despeckling methods on test SAR images.
Abstract: This work deals with unsupervised image deblurring.
We present a new deblurring procedure on images provided by lowresolution
synthetic aperture radar (SAR) or simply by multimedia in
presence of multiplicative (speckle) or additive noise, respectively.
The method we propose is defined as a two-step process. First, we
use an original technique for noise reduction in wavelet domain.
Then, the learning of a Kohonen self-organizing map (SOM) is
performed directly on the denoised image to take out it the blur. This
technique has been successfully applied to real SAR images, and the
simulation results are presented to demonstrate the effectiveness of
the proposed algorithms.
Abstract: Synthetic Aperture Radar (SAR) is an imaging radar form by taking full advantage of the relative movement of the antenna with respect to the target. Through the simultaneous processing of the radar reflections over the movement of the antenna via the Range Doppler Algorithm (RDA), the superior resolution of a theoretical wider antenna, termed synthetic aperture, is obtained. Therefore, SAR can achieve high resolution two dimensional imagery of the ground surface. In addition, two filtering steps in range and azimuth direction provide accurate enough result. This paper develops a simulation in which realistic SAR images can be generated. Also, the effect of velocity errors in the resulting image has also been investigated. Taking some velocity errors into account, the simulation results on the image resolution would be presented. Most of the times, algorithms need to be adjusted for particular datasets, or particular applications.
Abstract: There are very complex communication systems, as
the multifunction radar, MFAR (Multi-Function Array Radar), where
functions are integrated all together, and simultaneously are
performed the classic functions of tracking and surveillance, as all
the functions related to the communication, countermeasures, and
calibration. All these functions are divided into the tasks to execute.
The task scheduler is a key element of the radar, since it does the
planning and distribution of energy and time resources to be shared
and used by all tasks. This paper presents schedulers based on the use
of multiple queue. Several schedulers have been designed and
studied, and it has been made a comparative analysis of different
performed schedulers. The tests and experiments have been done by
means of system software simulation. Finally a suitable set of radar
characteristics has been selected to evaluate the behavior of the task
scheduler working.
Abstract: In this paper, a new probability density function (pdf)
is proposed to model the statistics of wavelet coefficients, and a
simple Kalman-s filter is derived from the new pdf using Bayesian
estimation theory. Specifically, we decompose the speckled image
into wavelet subbands, we apply the Kalman-s filter to the high
subbands, and reconstruct a despeckled image from the modified
detail coefficients. Experimental results demonstrate that our method
compares favorably to several other despeckling methods on test
synthetic aperture radar (SAR) images.
Abstract: There are many automotive accidents due to blind spots and driver inattentiveness. Blind spot is the area that is invisible to the driver's viewpoint without head rotation. Several methods are available for assisting the drivers. Simplest methods are — rear mirrors and wide-angle lenses. But, these methods have a disadvantage of the requirement for human assistance. So, the accuracy of these devices depends on driver. Another approach called an automated approach that makes use of sensors such as sonar or radar. These sensors are used to gather range information. The range information will be processed and used for detecting the collision. The disadvantage of this system is — low angular resolution and limited sensing volumes. This paper is a panoramic sensor based automotive vehicle monitoring..
Abstract: UWB is a very attractive technology for many
applications. It provides many advantages such as fine resolution and high power efficiency. Our interest in the current study is the use of
UWB radar technique in microwave medical imaging systems, especially for early breast cancer detection. The Federal Communications Commission FCC allowed frequency bandwidth of
3.1 to 10.6 GHz for this purpose. In this paper we suggest an UWB Bowtie slot antenna with enhanced bandwidth. Effects of varying the geometry of the antenna
on its performance and bandwidth are studied. The proposed antenna
is simulated in CST Microwave Studio. Details of antenna design and
simulation results such as return loss and radiation patterns are discussed in this paper. The final antenna structure exhibits good
UWB characteristics and has surpassed the bandwidth requirements.
Abstract: This paper mainly studies the analyses of parameters
in the intersection collision avoidance (ICA) system based on the radar
sensors. The parameters include the positioning errors, the repeat
period of the radar sensor, the conditions of potential collisions of two
cross-path vehicles, etc. The analyses of the parameters can provide
the requirements, limitations, or specifications of this ICA system. In
these analyses, the positioning errors will be increased as the measured
vehicle approach the intersection. In addition, it is not necessary to
implement the radar sensor in higher position since the positioning
sensitivities become serious as the height of the radar sensor increases.
A concept of the safety buffer distances for front and rear of the
measured vehicle is also proposed. The conditions for potential
collisions of two cross-path vehicles are also presented to facilitate the
computation algorithm.
Abstract: Data compression is used operationally to reduce bandwidth and storage requirements. An efficient method for achieving lossless weather radar data compression is presented. The characteristics of the data are taken into account and the optical linear prediction is used for the PPI images in the weather radar data in the proposed method. The next PPI image is identical to the current one and a dramatic reduction in source entropy is achieved by using the prediction algorithm. Some lossless compression methods are used to compress the predicted data. Experimental results show that for the weather radar data, the method proposed in this paper outperforms the other methods.
Abstract: Due to the high increase in and demand for a wide assortment of applications that require low-cost, high-efficiency, and compact systems, RF power amplifiers are considered the most critical design blocks and power consuming components in wireless communication, TV transmission, radar, and RF heating. Therefore, much research has been carried out in order to improve the performance of power amplifiers. Classes-A, B, C, D, E and F are the main techniques for realizing power amplifiers.
An implementation of high efficiency class-F power amplifier with Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) was realized in this paper. The simulation and optimization of the class-F power amplifier circuit model was undertaken using Agilent’s Advanced Design system (ADS). The circuit was designed using lumped elements.
Abstract: In this paper, an analysis of a target location estimation
system using the best linear unbiased estimator (BLUE) for high
performance radar systems is presented. In synthetic environments,
we are here concerned with three key elements of radar system
modeling, which makes radar systems operates accurately in strategic
situation in virtual ground. Radar Cross Section (RCS) modeling
is used to determine the actual amount of electromagnetic waves
that are reflected from a tactical object. Pattern Propagation Factor
(PPF) is an attenuation coefficient of the radar equation that contains
the reflection from the surface of the earth, the diffraction, the
refraction and scattering by the atmospheric environment. Clutter is
the unwanted echoes of electronic systems. For the data fusion of
output results from radar detection in synthetic environment, BLUE
is used and compared with the mean values of each simulation results.
Simulation results demonstrate the performance of the radar system.
Abstract: Most of the collision warning systems currently
available in the automotive market are mainly designed to warn
against imminent rear-end and lane-changing collisions. No collision
warning system is commercially available to warn against imminent
turning collisions at intersections, especially for left-turn collisions
when a driver attempts to make a left-turn at either a signalized or
non-signalized intersection, conflicting with the path of other
approaching vehicles traveling on the opposite-direction traffic
stream. One of the major factors that lead to left-turn collisions is the
human error and misjudgment of the driver of the turning vehicle
when perceiving the speed and acceleration of other vehicles
traveling on the opposite-direction traffic stream; therefore, using a
properly-designed collision warning system will likely reduce, or
even eliminate, this type of collisions by reducing human error. This
paper introduces perceptual framework for a proposed collision
warning system that can detect imminent left-turn collisions at
intersections. The system utilizes a commercially-available detection
sensor (either a radar sensor or a laser detector) to detect approaching
vehicles traveling on the opposite-direction traffic stream and
calculate their speeds and acceleration rates to estimate the time-tocollision
and compare that time to the time required for the turning
vehicle to clear the intersection. When calculating the time required
for the turning vehicle to clear the intersection, consideration is given
to the perception-reaction time of the driver of the turning vehicle,
which is the time required by the driver to perceive the message
given by the warning system and react to it by engaging the throttle.
A regression model was developed to estimate perception-reaction
time based on age and gender of the driver of the host vehicle.
Desired acceleration rate selected by the driver of the turning vehicle,
when making the left-turn movement, is another human factor that is
considered by the system. Another regression model was developed
to estimate the acceleration rate selected by the driver of the turning
vehicle based on driver-s age and gender as well as on the location
and speed of the nearest approaching vehicle along with the
maximum acceleration rate provided by the mechanical
characteristics of the turning vehicle. By comparing time-to-collision
with the time required for the turning vehicle to clear the intersection,
the system displays a message to the driver of the turning vehicle
when departure is safe. An application example is provided to
illustrate the logic algorithm of the proposed system.
Abstract: In this paper we present a new method for over-height
vehicle detection in low headroom streets and highways using digital
video possessing. The accuracy and the lower price comparing to
present detectors like laser radars and the capability of providing
extra information like speed and height measurement make this
method more reliable and efficient. In this algorithm the features are
selected and tracked using KLT algorithm. A blob extraction
algorithm is also applied using background estimation and
subtraction. Then the world coordinates of features that are inside the
blobs are estimated using a noble calibration method. As, the heights
of the features are calculated, we apply a threshold to select overheight
features and eliminate others. The over-height features are
segmented using some association criteria and grouped using an
undirected graph. Then they are tracked through sequential frames.
The obtained groups refer to over-height vehicles in a scene.