The fascinating aspect of these materials stems from the fact that when certain particles or devices are manufactured on the nanometer size region by means of special chemical and physical methods, they start showing distinct properties dependent on size, shape, and elemental compositions (such as huge amount of light absorption/emission, plasmonic resonance, high surface area, ability to convert light into heat, desirable magnetic properties, etc). Each of these features have found many applications in technology and they provide superior properties when compared to conventional materials. This article will not cover each technology based on nanomaterials but rather focus on the medical aspects and applications of nanotechnology and the direction it is heading.

Nano-medicine is a novel branch of nanotechnology seeking to deliver medically relevant drugs and imaging agents to the desired sites of the body. Biomedical imaging and drug delivery fields are benefitting from nanotechnology to a greater extent because not only do nanomaterials provide unprecedented results in diagnosis and therapies, considerable amounts of incentives in the form of governmental and private funding also drive topnotch institutions and scientists to study these materials around globe. For instance, iron oxide—when designed and manufactured on the nanometer order—can compete with, if not replace, most of the commercial magnetic resonance imaging (MRI) contrast agents due to some of its attributes, (i.e., being much more sensitive) requiring a less amount compared to other contrast agents, non-toxic to humans, and easy to manipulate in terms of its chemistry (1). Nanometer-sized spherical and rod-shaped Cadmium/Tellerium/Lead sulfides and selenides, also known as “Quantum Dots,” can absorb and emit light from ultra-violet (UV) to infrared region (IR) and this phenomenon could be utilized to construct biomedical sensors capable of detecting biologically relevant species (such as blood glucose, tumor markers, hormones, and etc.) with great accuracy and speed (2). Even by using multiple colors emitting “Quantum Dots,” one can, in principle, detect more than one biological entity simultaneously. Furthermore, their superior emissive properties could be harnessed to develop sensitive and selective fluorescence imaging techniques and assays which can lead to simple and early diagnosis of diseases. Gold nanorods, if irradiated with IR lasers, can generate extreme local temperatures in the surrounding medium owing to “plasmonic resonance of surface electrons,” and this feature could be directed to killing of localized tumor tissues known as “Photothermal Theraphy” (3).

Another class of nanomaterial called liposomes (4) can actually mimic lipid bilayer of the cell membrane which gives rise to a protective layer around organelles and nucleus, and maintains the transport of ions and molecules in and out of the cell. Synthetic liposomes, strikingly, can accommodate various cargoes extending from drugs to imaging agents in their inner cavity and render controlled release of its cargo as it circulates in the body, thereby providing longer bio-availability.

One of the most alluring uses of nanoparticle formulations in cancer therapy is their dimension. Certain sizes of nanoparticles can permeate into tumoral sites and be retained in that region longer than small particles or molecules. This extraordinary feature of nanoparticles, called “enhanced permeability and retention effect” (5), was utilized with liposomes to deliver chemotherapeutics to cancerous tissues effectively in a slow and controlled manner. In addition, chemical malleability of nanoparticles give rise to smart formulations which could respond to external stimuli in drug delivery applications. For example, the fact that cancer cells have lower pH values as compared to normal cells has been used to trigger release and delivery of drugs on site (6).

An alternative approach to conventional treatments is gene therapy in which the malfunctioning or mutant gene has been reintroduced into cells with a properly functioning one in order to restore the malady (7). Nanoparticles, especially polymeric counterparts, have shown promising results in encapsulating, carrying and delivering the gene of interest into desired cells.

Apart from synthetic nanoparticles, naturally occurring nanoparticles, have lately received great attention due to their unique structures and properties such as biocompatibility, uniform size, as well as suitability to chemical and genetic engineering. Plant and bacterial viruses, known as viral nanoparticles (8), have been tested for imaging and drug delivery applications, and because they infect only plants and bacteria, they are considered to be benign towards mammalians. Their inner and outer amino acids could be chemically modified with drugs and imaging modalities and cleverly engineered drug release mechanism could be invoked to operate upon external or internal stimulus.

Nanomaterials are, furthermore, suitable candidates for vaccine development. The immune system normally recognizes certain chemical groups on the surface of antigens (pathogens) and develops its defense mechanism based on this recognition. Multiple copies of these chemical groups could be chemically tailored around the surface of nanomaterial, and thereby could trigger the same immune response more efficiently (9).

The future of medicine will be shaped and enhanced through a targeted delivery of drugs and imaging contrasts into desired sites. Promisingly, nanoparticles will be able to assist in this regard to a considerable extent. Today’s cancer chemotherapy rely mostly on administering a variety of cancer drugs via intravenous (injecting through the vein) or oral means which delivers drugs to cancer cells as well as a considerable amount to healthy tissues which causes major side effects. In order to accumulate higher doses of drugs in tumor cells selectively and minimize nonspecific delivery, nanoparticles loaded with drugs and chemically decorated with “smart molecules” which have the ability to recognize cancer cells and specifically bind to them have been designed and tested successfully (10). These smart groups (organic molecules, antibodies, peptides and small molecules), surprisingly, have higher binding affinities toward some receptors over-expressed in cancer cells. Furthermore, encapsulation of drugs by nanomaterials provides a protective shell which prevents leakage of drugs to other sites.

An important drawback of cancer therapy is drug resistance in which cancer cells develop mechanisms to pump chemotherapeutics out of cells and decreases the efficacy of drugs. Nanoparticles, however, invalidate these resistance mechanisms by encapsulating drugs and should therefore not be exposed directly to surrounding cell environment. When nanoparticles reach the desired destination in the cell, an engineered mechanism or stimulus augment the release and drugs are expected to show their activity without any compromise (11).

It is fascinating to see how these small nanoparticles behave cleverly and orderly even though they look like inanimate and unconscious clusters of atoms. The extraordinary art, design and engineering witnessed in macro dimensions can also be seen in nano dimensions which means that a conscious and purposeful Hand of Power is present and visible in this nanoworld.

To sum up, nanomaterials could be ideal platforms for drug delivery and imaging applications and could complement the deficiencies in conventional therapies. Loading multiple copies of these entities into nanoparticles and devising clever mechanisms to target and deliver them into desired sites would be key elements in the nanomedicine of the future. We are living in a world where each of us has someone in our families or among our friends who are going through painful cancer treatments, which is a heart-rending and traumatic experience. Hopefully, nanomaterial-based therapies would give rise to solutions and success in battling against cancer. For in one prophetic tradition the Prophet Muhammad, peace be upon him, says: “O servants of God! Search for ways for treatment of illnesses. If God gives you ailments, for sure He bestows upon you cures for those.”

And why can’t this bestowal be in the nano form?

References

• Qiao RR, Yang CH, Gao MY. “Superparamagnetic iron oxide nanoparticles: from preparations to in vivo MRI applications” (vol 19, pg 6274, 2009). J Mater Chem 2009;19:9286-9286.
• Raymo FM, Yildiz I. “Luminescent chemosensors based on semiconductor quantum dots.” Phys Chem Chem Phys 2007;9:2036-2043.
• Giljohann DA, Seferos DS, Daniel WL, Massich MD, Patel PC, Mirkin CA. “Gold Nanoparticles for Biology and Medicine.” Angew Chem Int Edit 2010;49:3280-3294.
• Jesorka A, Orwar O. “Liposomes: Technologies and Analytical Applications.” Annu Rev Anal Chem 2008;1:801-832.
• Sancey L, Barbier E, Hirsjarvi S et al. “Enhanced Permeability and Retention (EPR) effect in tumors: characterization by MRI and fluorescence imaging.” B Cancer 2011;98:S67-S67.
• Hruby M, Konak C, Ulbrich K. “Polymeric micellar pH-sensitive drug delivery system for doxorubicin.” J Control Release 2005;103:137-148.
• Waehler R, Russell SJ, Curiel DT. “Engineering targeted viral vectors for gene therapy.” Nat Rev Genet 2007;8:573-587.
• Yildiz I, Shukla S, Steinmetz NF. “Applications of viral nanoparticles in medicine.” Curr Opin Biotech 2011;22:901-908.
• Peek LJ, Middaugh CR, Berkland C. “Nanotechnology in vaccine delivery.” Adv Drug Deliver Rev 2008;60:915-928.
• Ruoslahti E, Bhatia SN, Sailor MJ. “Targeting of drugs and nanoparticles to tumors.” J Cell Biol 2010;188:759-768.
• Liang XJ, Chen C, Zhao Y, Wang PC. “Circumventing tumor resistance to chemotherapy by nanotechnology.” Methods Mol Biol 2010;596:467-88.

In order to get a sharp image, ideally one point on the image (film) should receive light rays from only one point on the object. In practice, this ideal case can not be achieved in case of a large pinhole. If we have a large pinhole, as seen in Fig. 4, the light rays emerging from one point on the object reaches multiple points on the film. Also, multiple points on the object can arrive at a single point on the film. The result of both cases is a blurry image. For a small pinhole, however, there are light rays emerging from a point on the object in all directions, and only a very small amount of light is received on the film. To produce a decent image on the film, the exposure time needs to be very long, especially when a very small pinhole is used. Of course, we can make the pinhole a little larger to capture more light. But, wait! This would make the image blurry. Therefore, for pinhole photography, the size of the pinhole sets the quality of the image and the minimum exposure time. Also, we can take the picture of a still object, but a moving object cannot be captured easily by a pinhole camera due to the long exposure time. One important question is: Can we make reduce the size of the pinhole size to increase the quality of the image? Well, physics says: “No!” Fig. 5 shows a comparison of the images of a filament taken by a pinhole camera.⁶ As the size of the pinhole gets smaller and smaller, the effects of the diffraction phenomenon are more and more pronounced, and the image becomes blurry again. We also notice that the image is barely formed with a very small pinhole, indicating that very little light is received.

How can we gather more light and still make the image sharp? Can we achieve this with just the pinhole? Apparently not. That is why we mention lenses when talking about any imaging system. This is what a lens basically does. A lens gathers more light, and still preserves the one-to-one correspondence between the points on the object and those on the image. So, a lens is very useful for imaging. Most cameras have one or multiple lenses. Our eyes have lenses. We should remember, though, a pinhole camera takes a picture, but the compromise is the exposure time. Now, we see that a lens solves the exposure time problem, but is there a price to pay? To answer this question, let’s take a look at once again Fig. 2, where we see two pictures, one taken by a pinhole camera, and the other one by a lens camera. Look at the pictures carefully, and try to understand the difference before proceeding. As you probably observed, in the pinhole camera image everything in the picture is in sharp focus, from the close-by plants to the far distant beacon, and the clouds in the sky. However, in the lens camera image, only the closest daisy is in focus, and the other daisies, only a few meters away, are blurry. Indeed, we lose the depth of field in our images when using a lens camera. Depth of field can be defined as “The distance between the nearest and farthest points that appear in acceptably sharp focus in an image.” This is actually something we live with everyday. Try to focus your eyes on a mountain far away; the objects that are very close will not be in focus anymore. So, our eyes, consisting of lenses, also have limited depth of field. A nautilus eye, on the other hand, has an infinite depth of field, as it has a pinhole eye. Therefore, the price paid for gathering more light with a lens is that not everything will be in focus.

We can understand why lens cameras have a limited depth of field while a pinhole camera has nearly infinite depth of field if we consider the focusing mechanism of a lens. Given a pre-determined film position, a lens can only form sharp images of an object at a certain distance from the lens. Other points that are farther from or closer than same section of the object will be out of focus. However, if the size of the object is not large, we usually do not notice this effect. When we want to take pictures of close-by objects, then this effect is clearly seen, as Fig. 2 (b) shows.

Actually, we can correct this problem. The image of the farther points of the object forms at a farther point on the film. So, multiple light rays coming from one point will end up on the film. If we place an aperture next to the lens, then we can block some of these light rays. If we make the size of the aperture sufficiently small, we can get a sharp image of the farther point. Our original question about the lenses can be posed once again at this point: By using the aperture we make the image sharper, but what do we lose? Of course, since we block some of the light rays, we lose the light-gathering ability of the lens. Now, if we make the aperture size smaller and smaller, we finally reach the pinhole, and an almost infinite depth of field!

Our eyes also use similar mechanism of placing an aperture. The amount of light allowed to enter each eye is controlled by the iris, a circular diaphragm that opens wide at low light levels and closes to protect the pupil (the aperture) and retina (light detector of the eye) at very high levels of illumination. As illumination changes, the diameter of the pupil (positioned in front of the crystalline lens) reflexively varies between a size of about 2 to 8 millimeters. When illumination is very bright, the pupil narrows and light rays from the side are excluded from the optical pathway.⁷ The result is a sharper image on the retina. A very narrow pupil (approximately 2 millimeters) produces diffraction artifacts that spread the image of a point source on the retina, similar to the image of the filament captured by a very tiny pinhole (Fig. 5)

In conclusion, a pinhole camera is a very instructive tool for learning about imaging concepts. A pinhole camera has an infinite depth of field and the ability to produce sharp images regardless of the distance of the objects. This comes with a price, though: the small size of the pinhole limits the amount of light received by the film, so long exposure times are needed. A lens helps to gather more light, but compromises the depth of field. These concepts are used in imaging technologies, and can be found in the eyes of living organisms.

Notes

1. E. Hecht, Optics, 2nd edition, pp. 199. Addison-Wesley Publishing Co.
2. http://images.encarta.msn.com/xrefmedia/aencmed/targets/illus/ilt/T045986A.gif.
3. http://www.kosara.net/gallery/.
4. http://www.eyedesignbook.com/.
5. http://www.spylife.com/pinholecam.html.
6. http://www.umiacs.umd.edu/~ramani/cmsc426/Lecture3.pdf
7. http://www.olympusmicro.com/primer/lightandcolor/humanvisionintro.html.

Radar, a contraction of the words radio detection and ranging, is an electronic device for detecting and locating objects. It operates by transmitting a particular waveform pattern and detects the nature of the echo (return) signal.1 Radar is used to extend the capability of the man’s senses, especially that of vision. We can think of radar as being a substitute for the eye, although it can do so much more: it can see objects through such impervious conditions as darkness, haze, fog, rain, and snow, for its wavelengths are much longer than those of visible or infrared light. The human eye works as a passive device, since the object is illuminated by sunlight or other light sources. However, radar produces its own illumination via electromagnetic waves, which means that it is an active device. 

APPLICATIONS OF RADAR AND RADAR IMAGING

Radar is used in civilian applications as air-traffic-control radar to guide aircraft to a safe landing, and in commercial aircraft as radar altimeters to determine height and weather avoidance, as well as wind-shear radars to navigate in severe weather conditions.

The military uses radar for surveillance and weapons control. Examples of such radars are DEW (Distant Early Warning) and AEW (Airborne Early Warning), which detect aircraft, long-range search radars, and guided missile radars.2

Research scientists use radar as a measurement tool. Radars have been placed on satellites, space modules, and shuttles to explore meteors, planets, and other objects in the solar system.

In the case of an imaging radar, the radar travels along an airplane’s or a space shuttle’s flight path. The area underneath is illuminated by the radar, and the radar architecture builds the image as it moves on the top of its footprint (Fig.1). The radar image’s finer resolution is achieved by using a very long antenna array to focus transmitted and received energy into a sharp beam.2 The beam’s sharpness defines the resolution. Similarly, such optical systems as telescopes require large apertures (mirrors or lenses that are analogous to the radar antenna) to obtain fine imaging resolution. Synthetic Aperture Radar (SAR) is a common and very popular technique in radar imaging that achieves a very fine resolution.3 In the following sections, we introduce and explain different types of SAR imaging techniques.

SYNTHETIC APERTURE RADAR (SAR)

SAR refers to a technique that synthesizes a very long antenna by combining echoes received by the radar when it travels.4.5 Typically, SAR is used to produce a two-dimensional (2-D) image. One dimension in the image is called range (or along track), and is a measure of the “line-of-sight” distance from the radar to the target (Fig.l). Range is determined by precisely measuring the time from a pulse’s transmission to receiving the echo from target. The range resolution is determined by the transmitted pulse’s width (i.e., narrow pulses yield fine range resolution).

The other dimension is called azimuth (or cross track), and is perpendicular to range. Usually, the length of the radar antenna determines azimuth resolution. However, a good azimuth resolution requires a radar antenna that is not practically carried by an airborne platform, for imaging radars are much lower in frequency (1 to 10 GHz) than optical systems (4,000 to 8,000 GHz). The length of the required antenna could be around several hundred meters, which obviously cannot be carried by an air vehicle.

However, SAR differs from other radars in that it collects data along the flight path when it travels, instead of using a large antenna. Therefore, a very small antenna is adequate for the job. After collecting the data, it processes this aperture data as if it came from a physically long antenna. The distance the aircraft flies in synthesizing the antenna is known as the synthetic aperture. A narrow synthetic beamwidth results from the relatively long synthetic aperture, which yields finer resolution than what is possible from a smaller physical antenna.

SARs are not as simple as described above. Transmitting short pulses to provide range resolution is generally not practical. Typically, longer pulses with wide-bandwidth modulation are transmitted, which complicates range processing but decreases peak power requirements on the transmitter. For even moderate azimuth resolutions, a target’s range to each location on the synthetic aperture changes along the synthetic aperture. The energy reflected from the target must be “mathematically focused” to compensate for the range dependence across the aperture prior to image formation. Additionally, for fine-resolution systems, range and azimuth processing is coupled (dependent on each other), which greatly increases computational processing. The trick in SAR processing is to correctly match the variation in frequency due to motion (moving target or moving radar) for each point in the image.

An example of SAR imaging is shown in Fig. 2. The colors in the image reflect the received signal intensity. The strongest signal level is red, whereas the weakest is black. The figure is a SAR image of San Francisco, California, obtained by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture (SIR-C/X-SAR) imaging radar when it flew aboard the space shuttle Endeavour on October 3, 1994. The size of the image is about 26 miles by 36 miles. The center of the area is 37.83 degrees north latitude, 122.38 degrees east longitude.

This particular SAR image is a good illustration of how SAR distinguishes urban areas from nearby relatively less populated areas. Such densely populated regions as downtown San Francisco (center) and the city of Oakland (at the right across the San Francisco Bay) show up as red images due to the alignment of streets and buildings vis A vis the incoming radar beam. The bridges in the area are easily detected by the imaging radar, including the Golden Gate Bridge (left center) at the opening of San Francisco Bay, the Bay Bridge (right center), and the San Mateo Bridge (bottom center). All dark regions on the image represent smooth water. Radar also easily detects the major faults in the area: those bounding the San Francisco-Oakland urban areas and the San Andreas Fault (at the lower left), As seen from the image, faults are shown as dark straight lines in the SAR image.

INCERSE SAR (ISAR)

While SAR images a region of the Earth from an airplane or an air shuttle, Inverse SAR (ISAR) images a flying object, such as airplane or an asteroid, from land-based radar. ISAR is very popular, and also very critical in military applications.6 It is commonly used for identification purposes. In a possible war scenario where there are too many aircraft in the sky, it is almost impossible to guess which one is friendly or hostile. In that case, ISAR imaging technique is used to identify the approaching aircraft and classify it from a collection of possible targets.

In theory, ISAR is an imaging technique that maps the locations of dominant scattering points of a target based on the multi-frequency, multi-aspect, backscattered data.7 In this data, the signal’s amplitude reflects the magnitude information of the scattering points on the target, while the backscattered signal’s phase is related to the location information of the scattering point off the target. After collecting this 2-D raw data, several signal-processing tools extract from this data the amplitude and location information of the scattering centers. Then, a 2-D image of the target is constructed by using a convenient image processing technique.

An example of ISAR imagery is shown in Fig. 3. The model of the test airplane (C-29 model) is shown at the lower portion, while a 2-D ISAR image of the airplane is constructed at the upper portion of Fig.3. The measurement is taken at the center frequency of 10 GHz, where the frequency bandwidth is 16 GHz. The data is collected from 0.10 steps to cover the entire 3600 azimuth. At the end, a 2048 by 2048 2-D grid is constructed by using the ISAR algorithm. By comparing both, it is seen that ISAR imaging provides accurate target information. By looking at this image, it is very easy to identify and classify the aircraft.

ISAR is an active operation of the radar at the target’s far field. Both receiving and transmitting antennas must be far away from the target. Recently, new ISAR imaging techniques that allow passive radar operation have been discovered. Antenna SAR (ASAR) and Antenna Coupling (ACSAR) imaging techniques use direct radiation from an antenna mounted on the near field of an airplane or a ship to image the dominant radiation points off these platforms. In these cases, the radar functions only as a receiver, for the target’s own antenna provides illumination to the target. These techniques are mainly used to determine the dominant radiation points off the target to explore ways to cancel or mitigate undesired extra radiation from the target’s platform.

The development of fast computers during the 1980s allowed researchers to apply intensive computational electromagnetic (CEM) tools that ultimately led them to develop new SAR/ISAR algorithms. One of the most appreciated and widely used tool is Interferometric Synthetic Aperture Radar (INSAR) imaging, which allows the extraction of height information that can be used to render 3-D topographic views of a SAR scene.

INTERFEROMETRIC SAR (INSAR)

Radar interferometry involves coherently combining radar measurements made by two or more radar antennas displaced by a relatively small distance.8 Depending on the relative geometry of the two antennas, the combined measurements can be turned into measurements of surface topography, topographic change, or displacement over time. Mapping precision of around 2m in three dimensions over a wide area is now possible from airborne interferometric radars.

Here is how an INSAR works: A radar system launches electromagnetic energy to scan the ground terrain to be imaged. Two radar antennas collect the backscattered wave to obtain two different snapshots of SAR image. To avoid phase ambiguity, these antennas must be close enough to each other. Since the waves travel different distances from a particular scatterer to each antenna, the resultant phases of each SAR image is different. In the next step, an image called interferogram is formed by multiplying one SAR image by the complex conjugate of the other SAR image. The phase of the interferogram represents the differences in range to the scattering centers of each pixel in the image. These differences are caused by the terrain’s topography. Then, a signal-processing algorithm converts this phase information to extract the terrain’s topographic features. Finally, a 3-D INSAR image of the region is formed by combining the SAR images with the height information.

An example of INSAR imaging is illustrated in Fig.4, which depicts the Long Valley of east central California. The images were taken by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the space shuttle Endeavour during its two flights in April and October 1994. The four images show the steps necessary to produce 3-D data from radar interferometry. The image covers an area of 21 by 37 miles. The radar illumination is from the top of the image. The bright areas are hilly regions of big rocks and pine forest; the darker areas are the relatively smooth, sparsely vegetated valley floors. The curving ridge running across the image’s center from top to bottom is the northeast rim of the Long Valley caldera, a remnant crater from a massive volcanic eruption roughly 750,000 years ago.

The image in the upper right is an interferogram of the same region, constructed by combining data from the April and October flights. The different phases are shown as different color levels. These variations are caused by elevation differences in the area. The same color levels indicate that those regions have same altitudes. The image in the lower left shows a topographic map derived from the interferometric data. The black bold contour lines represent levels of elevation. In this particular image, elevation levels are spaced at 250-meter intervals. The last image is a 3-D view of the northeast rim of the caldera, looking toward the northwest. As can be seen from the image, it is possible to extract such geologic structural and landform features as elevation, vegetation, and soil type with the help of INSAR processing.

Another example of INSAR imaging is shown in Fig. 5, which depicts the Washington, DC, Mall area. A similar approach is used to form this 3-D image. The region starts from the Capitol building (top) to the Lincoln Memorial and the Arlington Memorial Bridge (toward the right bottom). The Washington Monument is very easy to observe at the center of the image. The bright areas (from white to yellow) represent higher elevation places; darker colors (from green to dark blue) represent the areas of lower elevation. The Potomac river (right bottom of the image) and the reflecting pool (from the Lincoln Memorial toward the Washington Monument) are all in dark blue because of the water and the lowest elevations. We can also clearly distinguish Constitution Avenue running from bottom to top. The green regions are intermediate elevation consisting mostly of vegetation. As seen from the image, the highest elevation is the top of the Washington Monument, the Library of Congress building, and the Capitol building.

CONCLUSION

In this paper, we presented a survey study of radar basics and radar imagery. It is obvious that radar has been a very important and useful tool throughout the 20th century, both in the military and industry. With developments in the computer era and new imaging algorithms, it looks like it will be a very critical tool in the 21st century as well. It is now possible to simulate very complex models and targets in a reasonable computation time in radar frequencies thanks to new developments in computational electromagnetics methods (CEM). Examples of those are Xpatch9 (a high frequency code that can predict the scattering from large, complex bodies) and FISC10 (a fast simulator of electromagnetic bodies at high frequencies). While computers continue to grow faster and faster, new electromagnetic simulators are also getting faster and more efficient. As a result, more compact, fancier, faster, and more accurate radar-imaging techniques are being developed.

REFERENCES

1. Morris, G. V. and Harkness, L. (1996) ‘Airborne Pulsed Doppler Radar’, Artech House.
2. Mensa, D. L. (1981) ‘High Resolution Radar Imaging’, pp. 185-189, Artech House.
3. Wehner, D. R. (1994) ‘High-Resolution Radar’. Artech House.
4. Carrara, W. C., Goodman, R. S. and Majewski, R. M. (1995) ‘Spotlight Synthetic Aperture Radar: Signal Processing Algorithms’, Artech House.
5. Franceschetti, G. and Lanari,. (1999) ‘Synthetic Aperture Radar Processing’, C. R. C. Press LLC.
6. Baltes, H. P. (1980) ‘Inverse Scatteiing Problems in Optics’, Springer-Verlag.
7. Chu, T. H. and Lin, D. B. (1991) ‘Microwave diversity imaging of perfectly conducting objects in the near-field region’, IEEE Trans. Antennas Propagat., vol. 39, pp. 480-487.
8. Askne, J., et al. (1997) ‘C-band repeat-pass inter ferometric SAR observations of forest, IEEE Trans. on Geoscience and Remote Sensing, vol.35, pp. 25-35.
9. Lee, S. W. (1992) ‘Test cases for XPATCH’, Electromagn. Lab. Tech. Rept., ARTI-92-4, Univ. of Illinois.
10. Ctr. Computat. Electromagn. (1997) ‘User’s Manual for FISC (Fast Illinois Solver Code)’, Univ. Illinois, Urbana-Champaign, and DEMACO. Inc.