In a proposed method of designing a recon- figurable antenna, the design would be opt- imized through evolution in hardware. The proposed method would be a specific instance of an emerging general method of automated synthesis of electronic circuits in hardware. Other specific instances of the general method were described in two NASA Tech Briefs articles: “Reconfigurable Arrays of Transistors for Evolvable Hardware” (NPO-20078), Vol. 25, No. 2 (February 2001), page 36; and “Evolutionary Automated Synthesis of Electronic Circuits” (NPO-20535), which precedes this article. To recapitulate: Under the direction of genetic and/or other evolutionary algorithms, the configurations and thus the functionalities of circuits would be made to evolve until at least one circuit exhibited a desired behavior. Evolution would include selective, repetitive connection and/or disconnection of transistors, amplifiers, inverters, and/or other circuit building blocks.
According to the proposed method, a reconfigurable antenna in a basic initial configuration would be placed on an antenna test range equipped for testing at the frequency or frequencies of interest. A computer outside the test range would be connected to interface circuits that would, in turn, be connected to (1) the test equipment (transmitters and receivers) on the range and (2) wires through which the computer could control the configuration of the antenna.
The computer would execute software that would include one or more automated- optimization algorithms plus driver-interface software for controlling the antenna configuration and the test equipment. Following initial activation, the software would go through the optimization process, controlling the test equipment and the antenna configuration as needed to produce an optimized configuration for each set of desired electromagnetic properties.
The only other method of automated design by use of an optimization algorithm involves computational simulation of performance instead of testing of a real physical implementation. The proposed method does not involve computational simulation and is expected to surpass the method that involves computational simulation; this is because the results of testing a real physical implementation are inherently valid and more accurate than are results obtained through computational simulation. In addition, optimization by use of the proposed method is expected to take much less time than does optimization by use of a computational simulation of reasonable fidelity. Moreover, unlike in the computational-simulation method, there would be no need to try to validate the simulated results with a physical test — an undertaking that usually entails manual re-optimization of the design to obtain the same performance from the physical device as from the simulated one.
This work was done by Adrian Stoica and Derek Linden of Caltech for NASA’s Jet Propulsion Laboratory.
This Brief includes a Technical Support Package (TSP).
Designing Reconfigurable Antennas Through Hardware Evolution
(reference NPO-20666) is currently available for download from the TSP library.
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Overview
The document discusses a novel method for designing reconfigurable antennas through hardware evolution, developed by Adrian Stoica and Derek Linden at NASA's Jet Propulsion Laboratory (JPL). This method represents a specific application of a broader approach to automated synthesis of electronic circuits, which utilizes genetic and evolutionary algorithms to optimize circuit configurations.
The proposed design process begins with a reconfigurable antenna placed in a test range, where it can be evaluated at specific frequencies. A computer outside the test range is connected to interface circuits that link it to the test equipment, including transmitters and receivers. The computer runs software that incorporates automated optimization algorithms and driver-interface software, allowing it to control both the antenna configuration and the test equipment. This setup enables the software to execute an optimization process, adjusting the antenna's configuration to achieve desired electromagnetic properties.
One of the key advantages of this method is that it relies on real physical testing rather than computational simulation. The authors argue that results obtained from testing a physical implementation are inherently more valid and accurate than those derived from simulations. Additionally, the optimization process is expected to be faster than that of computational simulations, as it eliminates the need for subsequent validation and manual re-optimization of designs to match simulated performance.
The document also references previous NASA Tech Briefs that describe related instances of automated synthesis in electronic circuits, highlighting the evolution of circuit functionalities through selective connection and disconnection of components like transistors and amplifiers.
Overall, this innovative approach to antenna design not only enhances the performance and adaptability of antennas but also contributes to the broader field of electronic circuit design. By leveraging hardware evolution, the method aims to streamline the design process, reduce time and resource expenditure, and ultimately lead to more effective and versatile antenna systems for various applications. The work underscores the potential of evolutionary algorithms in advancing technology and improving the efficiency of electronic systems.
