Shapeshifting antenna array promises improved sensing technology

Technology News |
By Rich Pell

Researchers at Princeton University have presented a new type of antenna array based on the paper-folding art of origami, potentially vastly improving sensing technology needed for autonomous vehicles, robots and cyberphysical systems. The shape-shifting array, designed like a folded paper box called a “waterbomb,” allows engineers to create a reconfigurable and adaptable radar imaging surface.

With this ability to shift and expand, say the researchers, the origami system offers a wider resolution and has the ability to capture complex three-dimensional scenes beyond the capability of a standard antenna array. The waterbomb antenna can also morph its shape to manipulate electromagnetic waves in carefully calibrated ways.

Combined with advanced algorithms, the waterbomb system can effectively process information from a wide range of electromagnetic fields. This shapeshifting ability, say the researchers, allows engineers to expand the capabilities of devices used for sensing and imaging.

“For most applications, planar, or flat, systems are preferred because they are simpler and easier to design,” says Kaushik Sengupta, an associate professor of electrical and computer engineering. “But reconfigurable systems allow us to substantially expand our ability in computer imaging. Using origami, we are able to combine the simplicity of planar arrays with the expanded ability of reconfigurable systems. It’s like a transformer robot in action.”

To build the system, the researchers installed a new class of broadband metasurface antennas onto standard, flat panels. Then they connected a number of the antenna panels into a precisely designed origami surface with an offset checkerboard pattern. Through proper sequence of folding and unfolding the panels, the array assumes a variety of different shapes like curves, saddles and spheres.

The relative simplicity of the individual antenna systems also means that the sensing arrays can be light and low-cost, making them easier to manufacture and deploy across a wide scale. While rapid developments in energy and computation usually draw the most public attention, say the researchers, they are focused on the invisible wireless networks that allow these breakthroughs to empower society.

“You can think about all these really complex applications that are emerging — robotics, self-driving cars, smart cities, smart healthcare applications, artificial reality, virtual reality,” says Sengupta. “All of these things are sitting on that web of wireless communications.”

While any one of these applications would represent a major increase in demand for wireless networks, say the researchers, together, they demand a fundamental rethinking of how that data is moved across the airwaves, both in terms of the microchips designed to handle the traffic and the signals transmitted by those chips. Far more information needs to be packed into signals, and computer systems needs to be built that can process the information quickly, accurate and securely.

In the most recent project, involving waterbomb origami, the researchers turned their focus from antenna arrays themselves into methods of shape-shifting multiple arrays into complex systems. The reconfigurable system not only allows for hyper-spectral sensing across a wide range of frequencies, it fuses the information together with the surface topology.

This could prove valuable for vehicles and robots that require intensive communications while working in a variety of environments. It also could prove important for other electronic structures that require folding and tuning such as spacecraft and solar panels.

“By eliminating the constraints of flat-panel antenna arrays,” says Sengupta, “we can combine principles of origami with high-frequency electronics and advanced signal processing to create versatile, highly efficient imaging and radar systems.”

For more, see “Origami Microwave Imaging Array: Metasurface Tiles on a Shape-Morphing Surface for Reconfigurable Computational Imaging.”


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