Description

Signal processing technologies enable the extraction of relevant information from signals received from sensors. Signal processing is present whenever a signal, or combination of signals, electrical, optical, fluidic, etc., is intentionally acted upon to increase the over-all usefulness, or value. Signal processing can be applied to monitoring and measuring, such as, for example, when an image is formed of a slice through a person's brain (magnetic resonance imaging) by combining numerous non-invasive images taken around the head. Signal processing can also be used to influence, or control, dynamic processes. For example, some fighter aircraft are only conditionally stable. It is the task of a control system, incorporating signal processing, to keep the multi-dimensional state of that aircraft within its performance envelope. Many systems additionally "push back" on the pilot's controls to give him a "feel" for the maneuver, because he is flying a computer while the computer is flying the plane.

Special Characteristics

Signal processing is a vast enabling technology, whose boundaries sometimes overlap those of other fields, such as software, integrated circuits, communication, imaging, display, etc. Signal processing technologies include microelectronics, specific hardware designs, software correlation techniques, neural networks and algorithm development. Advances in signal processing support reconnaissance and surveillance systems, machine vision, robotics, and autonomous systems. They also have application in law enforcement. It is a key element of the manufacturing, test, diagnosis, and repair process. As signal processing technologies advance, decision-making processes can be automated. It is increasingly becoming integrated into the very products which are being manufactured, tested, diagnosed, and repaired.

Impact on Economy

Future applications have to do with automated manufacturing, operator aids to reduce workload, and improved precision and uniformity in virtually any manual operation. They also lead to manufactured products which perform their functions in a more optimal, and more unsupervised, manner. Thus, integrated signal processing could make a significant contribution to job creation and economic growth by improving productivity in U.S. industry and enabling new manufacturing capabilities.

Impact on Security

National defense/security applications include missile guidance, unmanned air vehicle autopilots, engine monitoring and control systems.

The United States is the world leader in digital signal processing (DSP) technologies, driven by a variety of applications including the home entertainment market. In particular, the strong U.S. position in multimedia computing is a major asset. In addition, the military, though no longer the primary technology driver, is still funding important DSP R&D.

Worldview

While the U.S. leads in the underlying technology, Japan leads in exploiting it in the commercial marketplace. Europe is closer than Japan to challenging much of our military technology, while it is simultaneously an active competitor to Japan in many commercial venues. The U.S. may lead in military applications such as synthetic aperture radar technology, but the Japanese camcorder processes such as image motion compensation, digital zoom, automatic light controls, etc., have virtually no current competition in the U.S. Furthermore, because of the profit-driven need to demonstrate leadership, the U.S. often creates its own competition by revealing costly lessons for the free publicity. The trends are not in favor of the U.S. in this technology.

What’s the use?

Signal processing holds a key to both economic advantage (by providing superior, or previously nonexistent, performance) and also to military advantage (for the very same reasons).

Integrated signal processing is the field wherein the processing is physically integrated (often within the same microcircuit substrate) with the sensor. MEMS (micro electro-mechanical systems) technology best illustrates this field at the current time. The same technology which is used to etch and deposit layers of materials to form microcircuits is also used to micro-machine structures.

An important commercial application of sensor-integrated processing is pursued by Caltech's Carver A. Mead, who is developing a silicon retina which possesses both the photo- sensor and the rudimentary neural capabilities of an eye. The silicon retina reads cursive writing on checks automatically, and then inputs the information into a data base. Mead and his colleagues have developed several additional generations of neuromorphic vision systems which are now being developed through a venture-capital-financed start-up.