Engineering, 2013, 5, 47-52
doi:10.4236/eng.2013.55B010 Published Online May 2013 (http://www.scirp.org/journal/eng)
New Application, Development and Aerospace
Prospe c t of fN IR
Jinjin Pan, Xuejun Jiao
National Key Laboratory of Human Factor Engineering, China Astronaut Research and Training Centre, Beijing, China
Functional near-infrared imaging (fNIR) is a non-invasive, convenient, safe and stable imaging method to test
biological state. It can obtain the biological tissue hemodynamic data, thus becoming a powerful tool to measure brain
activities, mental workload , metabolism and cognitive activities state. First of all, we introduced the characteristics an d
current situation of fNIR in this article. Then we focused on the applications of fNIR, discussed some existing problems
and future directions, including the prospect in aerospace field. Our purpose is to give a comprehensive description of
fNIR and show its potential in aerospace field.
Keywords: fNIR; Brain Activity; Hemodynamics; Neuro-imaging Technology
Neural science develops rapidly in recent years. Lots of
researches in human cognition and behavior performance
have been carried out. Neuroscience research field is
very wide, including nervous system structure, nervous
function, pathological and so on. Among these aspects,
the researches on nervous structure and function are key
and fundamental. So neural imaging technology is very
important. It developed rapidly these years. And there are
several technology methods can be used to observe brain
structure and activity. FNIR technology is an excellent
neural imaging method of brain observation. It can
observe biological state effectively, non-invasively, and
1.1. Characteristics of fNIR
FNIR is a newly developed technology that utilizes light
from 700 nm to 900 nm to monitor the state of biological
tissue. This technique can be portable, safe, relatively
cheap and noninvasive. [1,2]
It was firstly introduced by Jobsis in his research
paper that relatively high degree of brain tissue
transparency in the NIR range enables the real-time
non-invasive detection of hemoglobin (Hb) oxygenation
using transillumin ation spectroscop y. For about ten years
later, this technology had been remarkable developed.
Researchers found that the near infrared spectroscopy
could be used to monitor brain fun ctional activities, such
as monitoring cognitive activities in normal condition
and war environment.  Early researchers carried out
some simple exercise and cognitive tasks, to verify this
possibility used for non-invasive monitoring of brain
regional activities. Some researchers later began to try to
monitor some complex cognitive tasks, such as war
management  and planes landing simulation .
Chance , Hoshi , and Villringer  are firstly
proved the possibility of NIR’s brain activity monitoring.
The wavelength range of fNIR is 700 nm to 900 nm.
Most biological tissues are relatively transparent to light
in this wavelength, so relatively little scattering of
photons oc curs when these wave length s are introduced to
tissue. It makes fNIR very suitable for tissue imaging. 
The main chromophores in the optical window of 600 to
900 nm are oxy- and deoxy-hemoglobin (denoted HbO
and Hb respectively), water, lipids and
cytochrome-coxidase. HbO and Hb are mainly of interest
because they are related to the regional cerebral blood
flow.  Using the modified Beer-Lambert law and fNIR
measurements conducted at two different wavelengths
within the near infrared light range at two adjacent times,
the relative changes in concentrations of deoxy-and
oxy-Hb can be obtained.  These physiological
parameters are closely related with human oxidation and
metabolism, and can be used for the detection of
cognitive activities and mental workload, so fNIR is a
ideal tool to detect cerebral cortex function.
There are several neuroimaging methods can realize
the monitoring of brain structure and function. They can
Copyright © 2013 SciRes. ENG
J. J. PAN, X. J. JIAO
be divided into invasive and non-invasive imaging
methods on the basis of whether harmful or not to human
body. At present, some high-resolution mode require
invasive methods or injection of pharmacological (such
as CT, MRI), these are not ideal choice. So many
invasive neuroimaging methods become research focus,
such as fNIR, EEG, fMRI, MEG, PET etc.  Among
these techniques, fMRI, EEG and PET are widely used.
Compared with other existing neuroscience imaging
methods, fNIR has several advantages. First of all, fNIR
can provide some physiological parameter information
while other methods cannot, such as oxidation
information. In addition, from Figure 1, we can find
fNIR has a better time resolution compared with fMRI
and P E T . FNIR and fMRI can both provide hemodynamic
responses information, but the fMRI measurements have
much restriction, its equipment is very large. The
subjects need supine measurement, and the image
acquisition time is long. However, fNIR can acquire data
quickly, its time resolution is very high, but it cannot
replace fMRI in the aspect of spatial resolution. 
Compared with EEG, fNIR can offer higher spatial
resolution for better observing brain structure. At the
same time, fNIR is less susceptible to motion artifacts
than EEG. Meanwhile it does not rely on ionizing
radiation, therefore it is safer than PET. Some
continue-wave fNIR equipment system is very portable,
and can be used for telemeasurement. [10,11] In
conclusion, fNIR is safe, convenient, unrestricted, green,
quick, and balanced. The subjects have no body
limitation, and can realize telemeasurement. Especially,
its balanced characteristics of time and sp atial resolution,
anti-jamming and portable advantages make it quite
suitable for application in the relative field.
Figure 1. Comparisons of neuroscience technologies .
2. Application of fNIR
Because of the advantages of fNIR, it develops rapidly in
recent years. The researchers take full advantage of fNIR,
study and produce many relative applications. Especially
in the near year, with the development of neuroscience,
some new and advanced applications appeared. FNIR
application fields include brain structure and function
research, brain-computer-interface, adaptive interface,
mental workload assessment, monitoring of newborn,
mental fatigue, depth of anesthesia monitoring, medical
rehabilitation, cognitive enhancement etc as shown in
Table 1. Main fields of fnir applications 
2.1. Brain-computer-interface (BCI)
BCI is an interface system which can obtain signal from
the brain, and control the external device or computer
through the signal. Application of fNIR in BCI is a
relatively new method, it can be used to help evaluate the
attention and cognitive load.  EEG, fNIR and other
methods can be used comprehensively in BCI to evaluate
the cognitive state based on neurophysiology and
physiology,  and to monitor cognitive activities such
as attention, working memory, motor nerve activity in
clinical and natural conditions. 
2.2. Cognitive Load and Professional Skills
Here is an example research of monitoring professional
skill development and cognitive load. Kurtulus and
several researchers monitored subjects’ cognitive load
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J. J. PAN, X. J. JIAO 49
and development of professional skill in a simulation
UAV environment. The monitor system used was a
16-channel cw-fNIR system. The results showed that the
operators’ total HB decreased significantly when they
transited from beginner to professional status. At the
same time, they believed that fNIR had great potential
application in research and production, and could also be
used to help optimize performance in adverse
circumstances. Hasan Ayaz et al also conducted
same UAV test, and they got the similar results.
2.3. Mental Workload Assessment
Human mental workload plays a very important role in
many complex control systems. Villringer.A proved that
under natural conditions, fNIR could be used for the
evaluation of mental workload in standard experiment
(n-back) and complex cognitive tasks (ATC). They also
showed that fNIR can evaluate the operators’ skill
progress in a complex cognitive task. They regarded
N-back experiment as a reference to verify the
availability of fNIR application in mental workload.
They used the 16 channels’ data to calculate oxidation
information based on MBLL. The results further proved
that the degree of expertise indeed affect the prefrontal
cortex (PFC) hemodynamic changes of left back.
2.4. Mental Fatigue Research
Jiao xuejun and several researchers simulated a
mircrogravity environment, and studied the relationship
between fNIR sample entropy and power spectrum in
normal and fatigue states. The results showed that fNIR
signal sample entropy and power spectral entropy
decreased obviously during fatigue status. So fNIR has
the potential to monitor mental fatigue.
2.5. Medical Rehabilitation
FNIR can be used to help monitor cognitive diseases
rehabilitation. There were dozens of years since
fNIR’s first application in monitoring of brain oxidation
and metabolism. However, fNIR’s history as a mean of
monitoring cognitive process and helping monitor nerve
repair is relatively short, only 10 years. Similarly to
fMRI, the output of fNIR can also be used to produce a
brain activation map, thus can be compared by some
software. Patricia M described several application
examples in nerve recovery field. These examples
showed that fNIR could be applied to monitor brain
function recovery after impact effectively, as well as
evaluation of brain iniury (TBI) function. He also
proposed that a series of united and standard
measurement methods were necessary. And we also need
to further develop connection device, in order to achieve
an integration of a variety of functions.  Study of
Kurtulus Izzetoglu showed that fNIR could be used to
tell the difference between healthy people and patients
with TBI. Darren Roblyer conducted a research
related to breast cancer, the results showed obvious
changes of Hb after treatment. So we can quickly
determine the possible reaction source by using fNIR to
monitor the changes or alter the breast cancer treatment
2.6. Brain Functional Imaging of Newborn
There was about 10 years since fNIR’s first application
in newborn brain functional imaging. S. Lloyd-Fox
summarized the development of fNIR application in
newborn brain functional imaging, and had summed up
38 applications in this field just up to the end of
2009.Fengyu and JiaoXuejun from Tsinghua
university and ACC developed a multichannel fNIR
system, the system was applicable to neonatal head blood
oxygen state bedside monitor. After ensuring system
safety, they verified the effectiveness of the system
through forearm occlusion and ValSalva’s experiments.
The experimental results accorded with physical laws,
were similar with the relatively results other researchers
got, and supplied the blood volume (CBV) information.
At the same time, they carried on ValSalva’s experiment
on adults, which proved the effectiveness of the
apparatus for measuring the human head CBV. Their
research provided a basis for the further study of neonatal
head blood oxygen activity and brain response
characteristics, and will promote the study in early
diagnosis of neonatal hypoxic ischemic encephalopathy.
2.7. Pediatric Pain Assessment
Dr Harel Rosen et al designed a set of pediatric pain
assessment by using fNIR. They found obvious growth
of oxy-Hb and deoxy-Hb when during pain stimulation.
The head blood volume growth under stimulation they
showed was consistent with the prior research.
2.8. Muscle and Brain Oxidation Process
Related researchers tested and verified that fNIR can be
used for understanding the metabolism process of healthy
muscle, the effects of disease on muscle’s oxidation and
metabolism, and evalu ating the efficiency of intervention
treatment. Especially in the field of aerospace,
muscle oxygen monitoring can be used for guiding the
training of athletes, and the astronaut muscle strength
change mechanism analysis.
2.9. Depth of Anesthesia Monitor
Copyright © 2013 SciRes. ENG
J. J. PAN, X. J. JIAO
School of medicine in Drexel University conducted an
experiment about monitoring depth of anesthesia by
fNIR. The results showed that the content of deoxy-Hb
had obvious difference between deep and superficial
anesthesia, thus proved that fNIR could be used for
clinical anesthesia depth monitoring. 
2.10. Social Science and Medicine in the Future
Relevan t rese arc her focu ses on the applicatio n of fNIR in
neonatal and adult language processing.  And there
are also some research directions are about the brain
responses of social people. Andreas Fallgatter is
carrying out a research about psychiatry using fNIR.
these research directions of fNIR will contribute to the
development of social science and medicine. With the
development of fNIR, it can also be used in learning
environment. It will help constitute personalized training
mechanism, and evaluate th e operators’ effort in multiple
2.11. Space Environment
In space environment, fNIR can be used for astronauts to
monitor their working load and cognitive performance.
Many studies showed that in space environment, the
cognition and operation ability of astronauts will change .
Study of Stefan Schneider et al demonstrated that fNIR
could provide brain structure and functional information
in extreme circumstances. And we could use fNIR to
explore oxidation information in different regions of the
cerebral cortex. So we could realize the measurement of
human brain hemodynamic data and function
information in space environment.
There are two available methods to measure brain
functions in aerospace field, EEG and fNIR. And fNIR
has many advantages when compared with EEG. FNIR
do not use to apply conductive paste, is not sensitive to
motion interference, and is comfortable to objects etc.
There are many application fields in apace environment,
such as cognition function, mental workload, emotion,
adaptive human-machine interaction, training
performance assessment in orbit, mental fatigue,
operating force varying mechanism analysis and so on.
3. Problems and Development Trend of fNIR
FNIR has lots of advantages, such as safe, convenient,
little restriction, fast imaging, green, it has balanced time
and spatial revolution, and it can be used freely not only
in daily life, but also in extreme circumstance like space
environment. However, it still exist some problems that
need further to develop, such as MA (motion aircraft),
physiological noise, resolution, unified analytical method
and so on.
3.1. Motion aircraft (MA)
FNIR can monitor the changes of HbO and Hb in the
brain. However, any physiological phenomenon or
activity occurred from head or other parts of the body,
can lead to changes in the fNIR indexes, and bring the
fNIR signals some interference. In particular, the motion
of human body can lead to this change, which is called
MA. Eliminating the interference of human motion on
fNIR signal, is very necessary for the reliable use of
cognitive activity evalu ation.
Some researchers are doing related study about fNIR
MA, Meltem Izzetoglu proposed a Kalman filter to solve
the movement interference for fNIR signals. In fNIR field,
there are only adaptive filer and Wiener filter methods
before, which were widely used in biology,
communication, and voice processing etc. However,
adaptive filter needs additional sensor an d hardware, and
changes the transmission function according to the
characteristics of input signals. And Wiener filter need
fixed data, it cannot be effectively used in real-time
environment. This newly proposed method could reduce
the motion interference in fNIR signal effectively. FNIR,
which combines the advantages of adaptive filter with
the Wiener filter, has higher SNR, ne eds no extra sensor,
and is applicable for real-time use. 
In addition, Behnam Molavi proposed a fNIR MA
elimination method based on wavelet. This method relies
on the difference of cycle and amplitude between motion
artifacts and fNIR signals, and is designed specially for
long motion artifacts. Through fNIR experiments on 3
infants, they confirmed that this method could effectively
eliminate the motion artifacts, and obtain a better artifact
reduction. This method is very suitable for eliminating
fringy motion artifacts, and artifacts with short cycle and
high amplitude. And the wavelets are changed adaptively
based on the changes of noise. 
These methods are effective, but they also have some
limitations. Therefore, one development direction of fNIR
signal should be to minimize interference as weak as
possible. Little MA is an advantage for fNIR compared
with other imaging methods (such as EEG, fMRI etc), so
it is important to constantly develop and strengthen this
3.2. Resolution Problem
From fig  we can see that, fNIR has higher spatial
resolution than EEG, and higher time resolution than
fMRI. It is a balanced and comprehensive method.
However, fNIR may be less excellent than EEG or fMRI
in some extreme required conditions, such as in very
high spatial or time resolution conditions. Therefore, we
should combine and use their advantages. A very good
method is to combine the fNIR with EEG or fMRI, make
full use of their advantages, so can we deal with the
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J. J. PAN, X. J. JIAO 51
resolution problem and get accurate and quick brain
Compared to the existing fixed hood type fNIR sensor,
future design of sensor should include modular sensor
and hairbrush sensor. The modular sensor can adapt to
adult and children, and all kinds of forehead size. And
hairbrush sensor can install light source and perceptron
in the hairbrush, it can make the light source and detector
contacted to skin directly by separated the hair. This
design will allow fNIR to measure information of
forehead and all other cortex area in brain, which has
never been realized before. And we should also focus
on the issue about how to detect the comfort and
accuracy of sensor.
3.4. Develop toward More Convenient Direction
FNIR develops from wired style to wireless style. There
was only cable fNIR equipment before Maurico
Rodriguez published an article about wireless fNIR
device in 2011. He studied and designed a wireless fNIR
system. Science develops quickly, and now we can find
many excellent wireless fNIR products. 
Although fNIR is very smart and convenient when
compared with other imaging modalities, it still needs to
develop toward a more convenient, compact, and light
direction. Thus it can be more suitable for using in
learning and training.
3.5. Establish a Standardized Method of Data
Although we have made remark able progress in the field
of light propagation in brain tissue, and the field of image
reconstruction from optical data, there is no standard data
analysis method to establish DOT image by multi-chan-
nel system, and no standard data analysis method to
determine statistical characteristics and cortical oxidative
changes. So establishing unified data analysis
methods is also a very important development direction
for fNIR technology application.
3.6. Combination with Other Techniques
By combining the eye-movement apparatus and fNIR
technology, we can capture the attention points and get
relative brain activities simultaneou sly. This function can
be easily realized by combining convenient fNIR and
accurate eye-movement apparatus.
In addition, we can achieve more accurate and quick
presentation of brain structure and function by combining
fNIR with EEG, fMRI etc.
4. Application Prospect of Aerospace
Neuroscience is developing very rapidly, and fNIR will
no doubt pl ay a key role i n fut ure as a h uman brain activity
measurement tool in neuroscience, especially in aerospace
Aerospace comprises the atmosphere of earth and
surrounding space. Typically, aerospace industries
combine aeronautics and astronautics to design and
maintain vehicles moving through air and space. The
environment in aerospace is very extreme, such as
weightlessness, radiation, vacuum, large temperature
difference, vibrancy, and long distance. Aerospace
activities are hard, large and expensive. So each kilogram
in weight must be seriously considered in aerospace
The equipment used in space circumstance must be
portable, safe, simple and no much restriction, and fNIR
has these characteristics. Thus fNIR is competitive in the
field of aerospace. FNIR may be used to monitor the
astronauts’ performance and skills duri ng traini ng and learn-
ing process. FNIR may also be used to acquire
astronauts’ cognitive state when they were in space work.
To sum up, there are many application fields in apace
environment, such as cognition function, mental
workload, emotion, adap tive human-machine interaction,
training perform a nce assessment in orbit， mental fatigue,
operating force varying mechanism analysis and so on.
With the development of science and technology,
people pay more attention to human being themselves.
We can see more and more human-centric training,
learning, and human-centered machine and equipment
emerge, and these new things also obey the ergonomics
law of safety, efficiency, and comfort.
The technology of fNIR not only obtains human physic-
ology and brain activity information, but also has the
characteristics of safe, green, convenient, quick, and
ergonomics trait. These proved the considerable
development space of fNIR. We can see its fine vitality
and development prospect in aerospace and many other
 A. Illringer and B. Chance, “Non-invasive Optical
Spectroscopy and Imaging of Human Brain Function,”
Trends in Neuroscience, Vol. 1997, No. 20, pp. 435-442.
 M. Izzetoglu, K. Izzetoglu, S. Bunce, B. Onaral and K.
Pourrezaei, “Functional Near Infrared Neuroimaging,”
Neural Systems and Rehabilitation Engineering, IEEE
Transactions on, Vol. 13, No. 2, 2005, pp. 153-159.
Copyright © 2013 SciRes. ENG
J. J. PAN, X. J. JIAO
Copyright © 2013 SciRes. ENG
 M. Izzetoglu, A. Devaraj, S. Bunce and B. Onaral,
“Motion Artifact Cancellation in NIRs Using Wiener
Filtering,” IEEE Trans on BME, Vol. 52, No. 5, 2005, pp.
 K. Izzetoglu, S. Bunce, M. Izzetoglu, B. Onaral and K.
Pourrezaei, “FNIR Spectroscopy As a Measure Of
Cognitive Task Load,” Proceedings of the 25th Annual
International Conference of the IEEE EMBS, 2003, pp.
 Y. Takeuchi, “Change In Blood Volume In The Brain
During A Simulated Aircraft Landing Task,” Journal of
Occupational Health, Vol. 42, 2000, pp. 60-65.
 B. Chance, et al., “Comparison of Time-Resolved and
Unresolved Measurement of Deoxy Hemoglobin in
Brain,” In Proceedings of National Academy of Science,
Vol. 1, 1988, pp. 4971-4975.
 Y. Hoshiand and M. Tamura, “Detection of Dynamic
Changes in Cerebral Oxygenation Coupled to Neuronal
Function During Mental Work In Man,” Neuroscience
Letters, Vol. 150, 1993, pp. 5-8.
 A. Villringer, et al. “Near Infrared Spectroscopy (Nirs): A
New Tool to Study Hemodynamic Changes During
Activation of Brain Function in Human Adults,”
Euroscience Letters, Vol. 154, 1993, pp. 101-104.
 S. I-Young and Yaz. c. Birsen, “Near Infrared Imaging
and Spectroscopy for Brain Activity Monitoring,” NATO
Security through Science Series, Vol. 2, 2006, pp.
 “Opportunities in Neuroscience for Future Army
Applications,” Committee on Opportunities in
Neuroscience for Future Army Applications, Vol. 11,
2009, pp. 11-11.
 S. Lloyd-Fox, A. Blasi and C. E. Elwell, “Illuminating the
Developing Brain: The Past, Present and Future of
Functional Near Infrared Spectroscopy,” Neuroscience &
Biobehavioral Reviews, Vol. 34, No. 3, 2010, pp.
 Kurtulus, Izzetoglu, et al., “The Evolution of Field
Deployable Fnir Spectroscopy from Bench to Clinical
Settings,” Journal of Innovative Optical Health Sciences,
Vol. 4, No. 3, 2011, pp. 239-239.
 Dorneich, et al, “Supporting Real-time Cognitive State
Classification on a Mobile Individual,” Journal of
Cognitive Engineering and Decision Making, Vol. 1, No.
3, 2007, pp. 240-270.doi:10.1518/155534307X255618
 Mauricio, Rodriguez. Development of a Versatile
Wireless fNIR System[J/OL].
 Kurtulus, Izzetoglu, Hasan, Ayaz, et al, “Applications of
Functional Near Infrared Imaging: Case Study on UAV
Ground Controller,” Lecture Notes In Computer Science,
Vol. 1, 2011, pp. 608-617.
 K. Izzetoglu, S. Bunce, B. Onaral, K. Pourrezaei and B.
Chance, “Functional Optical Brain Imaging Using
Near-Infrared During Cognitive Tasks,” International
Journal of Human-Computer Interaction, Vol. 17, No. 2,
2004, pp. 211-227.doi:10.1207/s15327590ijhc1702_6
 X. J. Jiao, J. Bai, S. G. Chen and Q. J. Li, “Browse
Conference Publications, Virtual Environments
Human-Co,” Virtual Environments Human-Computer
Interfaces and Measurement Systems (VECIMS), 2012
IEEE International Conference on, Vol. 1, 2012, pp.
 M. Patricia, Arenth, Joseph, H. Ricker, Maria and T.
Schultheis, “Applications of Functional Near-Infrared
Spectroscopy (fNIRS) to Neurorehabilitation of Cognitive
Disabilities,” The Clinical Neuropsychologist, Vol. 21,
No. 1, 2007, pp. 38-57
 D. Roblyer, et al., “Optical Imaging of Breast Cancer
Oxyhemoglobin Flare Correlates with Neoadjuvant
Chemotherapy Response One Day After Starting
Treatment,” Proceedings of the National Academy of
Science of the United States of America, Vol. 108, No. 15,
2011, pp. 14626-14631.
 Y. Feng, J. S. Chen, X. J. Jiao and J. Bai, “Design of a
Multi-channel Near-Infrared Spectroscopy System Used
for Bedside Real-time Monitoring of Newborn Infants’
Brain,” Space Medicine
Medical Engineering, Vol.
25, No. 1, 2012, pp. 25-27.
 M. Ferrari, T. Binzoni and Quaresima, “Oxidative
Metabolism in Muscle,” Philosophical Transactions of
the Royal Society B Biological Sciences, Vol. 352, 1997,
 B. Molavi and G. A. Dumont, “Wavelet-Based Motion
Artifact Removal for Functional Near-Infrared
Spectroscopy,” Physiological Measurement, Vol. 33, No.
2, 2012, pp. 259-261.
 M. Izzetoglu, P. Chitrapu, S. Bunce and B. Onaral,
“Motion Artifact Cancellation in NIR Spectroscopy
Using Discrete Kalman Filtering[J/OL], BioMedical
Engineering On Line.
 F. F. Jobsis, “Noninvasive, Infrared Monitoring of
Cerebral and Myocardial Oxygen Sufficiency and
Circulatory Parameters,” Science, Vol. 198, No. 4323,
1977, pp. 1264-1267.
 R. Parasuraman, “Neuroergonomics: Brain, Cognition,
and Performance at Work,” Current Directions in
Psychological Science, Vol. 20, No. 3, 2011, pp. 181-186.
 S. Schneider, “Imaging of Neuro-Cognitive Performance
in Extreme Environments—A (p) Review,” Planetary
and Space Science, Vol. 74, 2012, pp. 135-141.
 M. P. Cakir, “A Group Cognitive Perspective on the
Multimodal Analysis of Learning,” Third International
Conference on Emerging Intelligent Data and Web
 M. Ferrari, “A Brief Review on the History of Human
Functional Near-Infrared Spectroscopy (fNIRS)
Development and Fields of Application,” NeuroImage,
Vol. 63, 2012, pp. 921-935.
 H. Ayaz, “Monitoring Expertise Development during
Simulated UAV Piloting Tasks using Optical Brain
Imaging [J/OL],” Aerospace Conference, 2012 IEEE.