Automated Antenna Design

The spectrum of antenna designs for applications in communication, radar, and remote sensing systems is vast, and there is an increasing need for high-performance, customized antennas. Current methods of designing and optimizing antennas by hand are time and labor intensive, limit complexity, increase the time and cost expended, and require that antenna engineers have significant knowledge of the universe of antenna designs.

The use of evolutionary programming techniques to automate the design of antennas has recently garnered much attention. Considerable research has been focused on determining whether evolutionary techniques can be used to automatically design and optimize antennas so that they outperform those designed by expert antenna designers, and even whether evolutionary techniques can be used to design antennas in cases where humans are simply unable to.

In the Evolvable Systems Group, we have been conducting research on automated antenna design. Our approach has been to encode antenna structure into a genome and use a GA to evolve an antenna that best meets the desired antenna performance as defined in a fitness function. Antenna evaluations are performed by first converting a genotype into an antenna structure, and then simulating this antenna using the Numerical Electromagnetic Code (NEC) antenna simulation software.

To date, we have conducted a benchmark study attempting to optimize the well-known but difficult-to-design Yagi-Uda antenna, and conducted research on the automated design of several different spacecraft antennas, including the Mars Odyssey UHF antenna and the ST5 antenna.


 

Yagi-Uda Antenna

Invented in 1954, the widely used Yagi-Uda antenna, familiar as a common type of TV antenna found on home rooftops, remains a difficult antenna to optimize due to complex interactions, sensitivity at high gain, and the inclusion of numerous parasitic elements.

The Yagi-Uda antenna consists of three types of elements: a driven element, a reflector element, and a variable number of director elements, all supported by a central boom. Only the driven element is connected directly to the feeder; the other elements couple to the transmitter power through the local electromagnetic fields which induce currents in them. The spacing and length of the various components significantly affect the performance characteristics of the antenna.

In order to optimize the Yagi-Uda antenna using a coevolutionary algorithm, we mapped the structure of the antenna into a 14-element byte encoded representation scheme. Each element contained two floating point values, a length and a spacing value. Each floating point value was encoded as three bytes, yielding a resolution of (1/2)^24 for each value. The first pair of values encoded the reflector unit, the second pair of values encoded the driven element, and the remaining 12 pairs encoded the directors. Wire radius values were constrained to 2, 3, 4, 5, or 6 mm. Mutation was applied to individual bytes, and one point crossover was used.

Using this system, we were able to evolve Yagi-Uda antennas that had excellent bandwidth and gain properties with very good impedance characteristics. Results exceeded previous Yagi-Uda antennas produced using evolutionary algorithms by at least 7.8% in mainlobe gain.

Radiation patterns of the best evolved antenna without a ground plane.

 


Mars Odyssey UHF Antenna

The Mars Odyssey spacecraft is an orbiter carrying science experiments designed to make global observations of Mars. It carries onboard an UHF antenna, responsible for the primary, full-duplex, data link between the spacecraft and landed assets. The currently deployed antenna is a graphite/epoxy quadrifilar helix antenna (QHA) with a small ground plane.

 

The performance characteristics of an antenna can be affected by nearby structures. However, the currently deployed UHF antenna was not designed with surrounding structures in mind. As a result, the solar panels on the spacecraft sometimes have to be moved in order to optimize antenna performance. We therefore used the NEC simulator to evaluate the performance of various antenna designs in the presence of models representing the solar panel and fuel tanks.

Using a coevolutionary algorithm, we optimized the design parameters for a quadrifilar helical antenna by encoding various parameters that control the shape and size of the antenna into a linear representation.

We were able to evolve a quadrifilar helix antenna that was a quarter of the volume of the currently deployed Mars Odyssey antenna yet still achieving the performance characteristics of the latter.

Radiation pattern for Mars Odyssey UHF QHA
Radiation pattern for a coevolved UHF QHA

 


ST5 Antenna

The Space Technology 5 Project (ST5) is one of NASA's New Millennium Program missions that will launch multiple miniature spacecraft to test innovative concepts and technologies in the harsh environment of space. During flight validation of its technologies, ST5 may measure the effect of solar activity on the Earth's magnetosphere. ST5's objective is to demonstrate and qualify innovative technologies and concepts for application to future space missions.

The three ST5 spacecraft will communicate with a 34 meter ground-based dish antenna. The antenna specifications for the mission present a challenging design problem, requiring both a wide beamwidth for a circularly-polarized wave and a wide bandwidth. Based on the requirements, a contractor was awarded the contract to design and build the antennas for the ST5 mission. The contractor proceeded using conventional design practices, relying on human expertise and antenna computer-aided design software to produce a compliant design and protoype. In parallel, our group worked on the evolutionary design and fabrication.

We devised a LOGO-like antenna constructing programming language where each node in the tree-structured representation is an antenna-construction command. An antenna is created by starting from the root of the tree and executing the commands at each node in the tree. In constructing an antenna, the current state (location and orientation) is maintained, and subsequent commands add wires or change the current state. We then used a genetic algorithm (GA) to evolve genotypes that specify the design for one arm, and built the complete antenna using four copies of the evolved arm.

Example antennas produced using the antenna constructing programming language: (a) non-branching, (b) branching.

The fitness function used to evaluate antennas is a function of the voltage standing wave ratio (VSWR) and gain values on the transmit and receive frequencies. VSWR is a way to quantify reflected-wave interference, and thus the amount of impedance mismatch at the junction. VSWR is the ratio between the highest voltage and the lowest voltage in the signal envelope along a transmission line.

The two best antennas found, one (ST5-3-10) from a GA that allowed branching and one (ST5-4W-03) from a GA that did not, were fabricated and tested. Antenna ST5-3-10 is a requirements-compliant antenna that was built and tested on an antenna test range. While it is slightly difficult to manufacture without the aid of automated wire-forming and soldering machines, it has a number of benefits as compared to the conventionally-designed antenna.

The two fabricated antennas, each shown next to a quarter for scale.

First, there is the potential of needing less power. Antenna ST5-3-10 achieves high gain (2-4dB) across a wider range of elevation angles. This allows a broader range of angles over which maximum data throughput can be achieved. Also, less power from the solar array and batteries may be required.

Second, the evolved antenna does not require a matching network nor a phasing circuit, removing two steps in design and fabrication of the antenna. A trivial transmission line may be used for the match on the flight antenna, but simulation results suggest that one is not required.

Third, the evolved antenna has more uniform coverage in that it has a uniform pattern with small ripples in the elevations of greatest interest (between 40 and 80 degrees). This allows for reliable performance as elevation angle relative to the ground changes.

Finally, the evolved antenna had a shorter design cycle. It was estimated that antenna ST5-3-10 took 3 person-months to design and fabricate the first prototype as compared to 5 person-months for the conventionally designed antenna.

Measured VSWR plot for antenna ST5-3-10. Point 1 is the receive frequency and point 2 is the transmit frequency.