Conformal antennas and antenna arrays (arrays) have become necessary for vehicular communications where a high degree of aerodynamic drag reduction is needed, like in avionics and ships. However, the necessity to conform to a predefined shape (e.g., of an aircraft’s nose) directly affects antenna performance since it imposes strict constraints to the antenna array’s shape, element spacing, relative signal phase, and so forth. Thereupon, it is necessary to investigate counterintuitive and arbitrary antenna shapes in order to compensate for these constraints. Since there does not exist any available theoretical frame for designing and developing arbitrary-shape antennas in a straightforward manner, we have developed a platform combining a genetic algorithm-based design, optimization suite, and an electromagnetic simulator for designing patch antennas with a shape that is not a priori known (the genetic algorithm optimizes the shape of the patch antenna). The proposed platform is further enhanced by the ability to design and optimize antenna arrays and is intended to be used for the design of a series of antennas including conformal antennas for shipping applications. The flexibility and performance of the proposed platform are demonstrated herein via the design of a high-performance GPS patch antenna.
Conformal antennas and antenna arrays (arrays) inherit their name from the fact that they “conform” to the shape of a 2D yet not planar surface. More specifically, conformal antennas are flat curving antennas that follow or are embedded to an object of predefined shape, like that of an aircraft’s nose. Conformal antennas and antenna arrays (arrays) have become necessary for vehicular communications (where a high degree of aerodynamic drag reduction is needed) due to their so-called “conformity” to arbitrary surface shape, like in avionics and high-performance ships or submarines.
Conformal antennas were developed in the 1980s in order to be integrated with the outer metallic layers of aircrafts, with the purpose of reducing the aerodynamic drag and improving aircraft speed, fuel consumption, and gas emissions. Conformal antennas gradually replaced conventional ones that project from the aircrafts’ hull. As long as commercial applications are considered (including shipping), the technical limitations and constraints are similar to avionics, but the application of conformal antennas was until recently limited due to the high related costs of etching and integration.
However, in the recent years the reduction of these costs has turned conformal antennas to an attractive choice for civilian applications as well, from train antennas to car radio antennas in order to improve shape and aesthetics as well as increase vehicle performance, and to cellular base station antennas to save space and make antennas less visually intrusive [
Conformal antennas may also be used in maritime communications and shipping applications, to not only reduce aerodynamic or—in this case—“hydrodynamic” drag, but also offer the ability to integrate more antenna elements in the ship’s hull, offering a very large surface for antenna deployment that could in turn yield to increased performance with limited overall antenna profile (volume, visually intrusiveness). Such an example of a GPS-receiving patch antenna is presented in this paper that demonstrates the abilities and performance of a proposed platform for arbitrary-shape flat antennas design and optimization. The choice of a GPS-appropriate antenna has been made on the basis that GPS has become one of the top most important services necessary for a ship nowadays; GPS is used in ships not only to monitor its route and navigation, but also for safety and security. Other, more sophisticated GPS applications in shipping include synchronizing phasor measurement units for hybrid state estimators to provide estimates from SCADA control units on board, like electric power quality, ship performance monitoring, hull and machinery structural fatigue, and so forth [
On top of the high related costs of integration, conformal antennas also suffer from severe constraints imposed on their design that arise due to the predefined and often counterproductive shape of the flat area that they need to conform with. This affects the performance of the antenna array, its shape, the elements spacing, the relative signal phase, and so forth. Thereupon, it is necessary to investigate counterintuitive and arbitrary antenna shapes in order to compensate for these constraints. Since there does not exist any available theoretical frame for designing and developing arbitrary-shape antennas in a straightforward manner, we have developed a combination of a genetic algorithm- (GA-) based design and an electromagnetic (EM) solver for designing patch antennas with a shape that is not a priori known (the genetic algorithm optimizes the shape of the patch antenna together with its other characteristics). The proposed GA is of high performance and proved in practice to deliver antenna patches of arbitrary shapes but of leveraged performance and low profile. Moreover, it is anticipated that the proposed platform is of generic use and may be readily deployed to other antenna and antenna arrays optimization problems as well. The flexibility and performance of the proposed platform are demonstrated herein via the design of a high-performance GPS patch antenna.
The rest of the paper is organized as follows. Section
The proposed platform for antenna and antenna array design is based on combining an EM solver with an in-house developed GA solution. The proposed GA solution has been used in the past for the design and optimization of dipole antennas and antenna arrays [
In the proposed scheme, the GA is used in order to configure an initial population of 80 chromosomes (more information on GA terminology and literature is available in Section
Flowchart of the proposed GA-based optimization platform for arbitrary-shape patch antennas.
Microstrip patch antennas were first introduced during the second half of the twentieth century and are based on the observance that microstrips may radiate electromagnetic waves efficiently given certain limitations [
Patch antenna schematic example.
The width and length of the patch are illustrated in the top side of Figure
Due to inherent design limitations, patch antennas usually radiate most effectively towards the direction that is perpendicular to the substrate surface and opposite to the ground plane. Note that, by convention, there is a Cartesian coordinates system as the one depicted in the top side of Figure
Different patch layouts are proposed in the literature, yielding rectangular, circular, ring, or other complex patch layouts. Nevertheless, there are no analytic expressions for arbitrary-shape patches, like the one we propose herein; in such cases, one can only work with numerical electromagnetic solvers.
Furthermore, a patch antenna may be fed using either a microstrip or coaxial probes (see Figure
Various patch feeding techniques.
GAs are a robust class of stochastic optimization algorithms, especially suited for nonlinear, nondifferential, multiobjective, and multidimensional optimization problems. They have been introduced in early 1960s, but only recently have they been widely used for electromagnetic optimization [
GAs are considered to have certain advantages over other heuristic methods currently used, like the Particle Swarm Optimization (PSO) or the Simulated Annealing methods (SA). Even though it is difficult to establish a benchmark for heuristics algorithms [
The GA used herein has been in-house developed based on the work reported by Houck et al. [
The arbitrary patch of the antenna is optimized as follows: at first, one chromosome gene is designated to correspond to the patch’s width and one more to the patch’s length (see Figure
Patch antenna schematic example.
Finally, a GA’s performance strongly depends on the design of its fitness function. The fitness function of the proposed GA is developed as follows: after a patch model is generated by the GA’s chromosome, it is passed to the EM solver according to Figure
Then, the fitness function takes into account that the reflection coefficient,
Moreover, the fitness function also takes into account the variance of the patch’s horizontal gain since it needs to be kept as low as possible for uniform radiation. Thus, the fitness function also calculates a third error term as in
Finally, the cumulative error is calculated by
The specific formula for (
Various runs of the proposed GA optimization platform have been executed with the purpose of designing a patch antenna of arbitrary shape suitable for applications around 1.5 GHz, like a GPS receiver. The substrate of the patch antenna should be of the FR4 type, with a substrate thickness of 1.6 mm and a dielectric constant equal to
After multiple runs it was decided that the various weights of the fitness function should be assigned, so as the final form of the latter should be
The layout of the patch antenna is illustrated in Figure
Technical characteristics and performance results of the optimized patch antenna.
Central frequency (GHz) | 1.5 |
Total maximum gain (e- and H-plane) at central frequency (dBi) | 5 |
Reflection coefficient at central frequency (dB) | −14 |
Standard deviation of horizontal gain for |
0.3 |
Bandwidth (MHz) | 50 |
Layout of the optimized patch antenna (top view).
Using arbitrary-shape antennas may be a significant aid in developing high-performance antennas and arrays under strict constraints. Conformal antennas are a priori considered as a type of antennas that need to comply with such strict constraints and at the same time are of high importance for avionics and marine communications. With the proposed platform we were able to design a GPS antenna of low profile and high performance. Future work will include the design of planar antennas that will be etched at the outer metallic layers of ships and aircrafts using our design platform.