Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:


Sparse microwave imaging: A new concept in microwave imaging technology

Sparse microwave imaging is a novel concept in microwave imaging that is intended to deal with the problems of increasing microwave imaging system complexity caused by the requirements of the system applications.

Under the support of the 973 program "Study of theory, system and methodology of sparse microwave imaging", Chinese scientists have conducted considerable research into most aspects of sparse microwave imaging, including its fundamental theories, system design, performance evaluation and applications. Their work, consisting of a series of papers, was published in Science China Information Sciences 2012, vol. 55 (8), as a special issue on sparse microwave imaging.

These are flowcharts comparing the traditional microwave imaging process and the sparse microwave imaging process.
Credit: ©Science China Press

An overview of their work can be found in the paper written by Professor Wu YiRong and his Science and Technology group from the Microwave Imaging Laboratory at the Institute of Electronics of the Chinese Academy of Sciences, entitled "Sparse microwave imaging: Principles and Applications".

Microwave imaging is one of the two major tools of remote sensing, and has been widely used in fields such as agriculture, forestry, oceanic monitoring, topography mapping and military reconnaissance. The best known modern microwave imaging technology used in remote sensing is synthetic aperture radar (SAR), which transmits an electromagnetic wave toward the scene from a platform moving in a straight line, receives the radar echo and produces a high resolution microwave image via signal processing. Compared with optical sensing, microwave imaging has the ability to provide all-weather round-the-clock observation, and can be applied to deal with some special sensing requirements, including moving target detection and digital elevation model extraction.

As microwave imaging technology has been used in increasing numbers of fields, the users have of course raised demands for numerous new requirements for their microwave imaging systems. Among them, high resolution and a wide mapping swath are the basic requirements for modern microwave imaging systems. High resolution means that more details can be observed, and the wide mapping swath means larger observation areas.

According to microwave imaging theory – a theory that has not changed for over 60 years following the invention of SAR technology – the signal bandwidth and the system sampling rate determine the achievable resolution and swath of the microwave imaging system. The only way to improve the signal bandwidth and sampling rate is to increase the system complexity, i.e., to use hardware that is larger, heavier and demands greater power consumption. However, we must eventually reach a limit to the increases in system complexity, and Moore's Law could not hold forever. The concept of sparse microwave imaging was therefore developed.

Sparse microwave imaging introduces sparse signal processing theory to microwave imaging as a replacement for conventional signal processing schemes based on matched filtering. Sparse signal processing was a concept that was developed by mathematicians in the late 1990s, and includes a set of mathematical tools designed to deal with sparse signals – a signal is sparse when most of the elements of the signal are (or are very close to) zero. Thanks to the extraordinary work known as compressive sensing by D. Donoho, E. Candès and T. Tao over the last decade, sparse signal processing theory, and compressive sensing theory in particular, has become a focal point for research in current signal processing fields. Essentially, sparse signal processing theory asserts that, if a signal is sparse, then it can be measured with far fewer samples than would be required for traditional sampling schemes, and can then be perfectly reconstructed from these few samples via sparse reconstruction algorithms.

If we introduce sparse signal processing theory to microwave imaging, we can then achieve sparse microwave imaging. However, while the concept sounds simple, the combination of sparse signal processing with microwave imaging is in fact quite a complex problem. The difficulties include: the method used to obtain a sparse representation of a scene, determination of the constraints of sparse observation, and efficient and robust reconstruction of the microwave image from the sparse observation data.
Consider, for example, the sparse representation problem. We know that sparse signal processing theory can only deal with sparse signals, but, unfortunately, the observed scenes are usually not sparse. In optical sensing, although an optical picture is not always sparse, it can be expected to have a sparse representation in a transform domain such as the discrete cosine transform (DCT) domain or a wavelet domain. However, we are not so lucky in microwave imaging. To date, no universally applicable transform domain has been found that would enable microwave imaging scenes to have sparse representations. We can only deal with a scene that it is sparse itself.

Another example is the reconstruction algorithm. Mathematicians have developed many sparse reconstruction algorithms with various features, and some of them can feasibly be used in sparse microwave imaging, but one problem remains: calculation efficiency. The size of microwave imaging scenes is always very large, especially in wide mapping swath applications. Experimental results show that the calculation time duration – which can usually be counted in months – is unacceptable when the scene is large. In positive news, some accelerated algorithms have been derived by Chinese scientists.

Sparse microwave imaging theory and technology can be applied in two ways: to design new systems, and to improve existing microwave imaging devices. As a new microwave imaging concept, we can of course design optimized microwave imaging systems using sparse microwave imaging theory for guidance. We can also use the signal processing methods of sparse microwave imaging to improve the imaging performance of the existing microwave devices, e.g. to increase the image distinguishability, reduce the sidelobes and reduce ambiguity. Discussions on both of these topics can be found in the special issue.

Sparse microwave imaging is believed to have the ability to resolve the conflict between growing microwave imaging performance requirements and increasing system complexity. Under this new microwave imaging concept, the system complexity could be reduced remarkably without adversely affecting the imaging performance. Although there are many problems with the technology that need to be solved, sparse microwave imaging can be expected to have a bright future.

See the article: Zhang B C, Hong W, Wu Y R. Sparse microwave imaging: Principles and applications. SCIENCE CHINA Information Science, 2012, 55(8): 1722-1754

WU YiRong | EurekAlert!
Further information:

More articles from Information Technology:

nachricht A novel hybrid UAV that may change the way people operate drones
28.03.2017 | Science China Press

nachricht Timing a space laser with a NASA-style stopwatch
28.03.2017 | NASA/Goddard Space Flight Center

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: A Challenging European Research Project to Develop New Tiny Microscopes

The Institute of Semiconductor Technology and the Institute of Physical and Theoretical Chemistry, both members of the Laboratory for Emerging Nanometrology (LENA), at Technische Universität Braunschweig are partners in a new European research project entitled ChipScope, which aims to develop a completely new and extremely small optical microscope capable of observing the interior of living cells in real time. A consortium of 7 partners from 5 countries will tackle this issue with very ambitious objectives during a four-year research program.

To demonstrate the usefulness of this new scientific tool, at the end of the project the developed chip-sized microscope will be used to observe in real-time...

Im Focus: Giant Magnetic Fields in the Universe

Astronomers from Bonn and Tautenburg in Thuringia (Germany) used the 100-m radio telescope at Effelsberg to observe several galaxy clusters. At the edges of these large accumulations of dark matter, stellar systems (galaxies), hot gas, and charged particles, they found magnetic fields that are exceptionally ordered over distances of many million light years. This makes them the most extended magnetic fields in the universe known so far.

The results will be published on March 22 in the journal „Astronomy & Astrophysics“.

Galaxy clusters are the largest gravitationally bound structures in the universe. With a typical extent of about 10 million light years, i.e. 100 times the...

Im Focus: Tracing down linear ubiquitination

Researchers at the Goethe University Frankfurt, together with partners from the University of Tübingen in Germany and Queen Mary University as well as Francis Crick Institute from London (UK) have developed a novel technology to decipher the secret ubiquitin code.

Ubiquitin is a small protein that can be linked to other cellular proteins, thereby controlling and modulating their functions. The attachment occurs in many...

Im Focus: Perovskite edges can be tuned for optoelectronic performance

Layered 2D material improves efficiency for solar cells and LEDs

In the eternal search for next generation high-efficiency solar cells and LEDs, scientists at Los Alamos National Laboratory and their partners are creating...

Im Focus: Polymer-coated silicon nanosheets as alternative to graphene: A perfect team for nanoelectronics

Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are less stable. Now researchers at the Technical University of Munich (TUM) have, for the first time ever, produced a composite material combining silicon nanosheets and a polymer that is both UV-resistant and easy to process. This brings the scientists a significant step closer to industrial applications like flexible displays and photosensors.

Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are...

All Focus news of the innovation-report >>>



Event News

International Land Use Symposium ILUS 2017: Call for Abstracts and Registration open

20.03.2017 | Event News

CONNECT 2017: International congress on connective tissue

14.03.2017 | Event News

ICTM Conference: Turbine Construction between Big Data and Additive Manufacturing

07.03.2017 | Event News

Latest News

'On-off switch' brings researchers a step closer to potential HIV vaccine

30.03.2017 | Health and Medicine

Penn studies find promise for innovations in liquid biopsies

30.03.2017 | Health and Medicine

An LED-based device for imaging radiation induced skin damage

30.03.2017 | Medical Engineering

More VideoLinks >>>