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Conformal Patch Antenna Arrays Design for Onboard Ship Deployment Using Genetic Algorithms

Conformal Patch Antenna Arrays Design for Onboard Ship Deployment Using Genetic Algorithms Hindawi Publishing Corporation Advances in Power Electronics Volume 2013, Article ID 960514, 5 pages http://dx.doi.org/10.1155/2013/960514 Research Article Conformal Patch Antenna Arrays Design for Onboard Ship Deployment Using Genetic Algorithms 1 1 2 1 Stelios A. Mitilineos, Symeon K. Symeonidis, Ioannis B. Mpatsis, Dimitrios Iliopoulos, 3 1 1 Georgios S. Kliros, Stylianos P. Savaidis, and Nikolaos A. Stathopoulos Technologial Educational Institute of Piraeus, Department of Electronics, 250, Petrou Ralli kai iTh von Street, 12244 Aigaleo, Greece Hellenic Air Force Academy, Dekeleia Air-Force Base, Dekeleia, Greece Department of Aeronautical Sciences, Hellenic Air Force Academy, Dekeleia Air-Force Base, Dekeleia, Greece Correspondence should be addressed to Stelios A. Mitilineos; smitil@gmail.com Received 17 October 2012; Accepted 17 February 2013 Academic Editor: John Prousalidis Copyright © 2013 Stelios A. Mitilineos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 aircra’fts nose) directly aeff cts 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). eTh 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. eTh flexibility and performance of the proposed platform are demonstrated herein via the design of a high- performance GPS patch antenna. 1. Introduction project from the aircrafts’ hull. As long as commercial appli- cations are considered (including shipping), the technical Conformal antennas and antenna arrays (arrays) inherit their limitations and constraints are similar to avionics, but the name from the fact that they “conform” to the shape of a 2D application of conformal antennas was until recently limited yet not planar surface. More specicfi ally, conformal antennas due to the high related costs of etching and integration. are flat curving antennas that follow or are embedded to However, in the recent years the reduction of these costs an object of predenfi edshape,likethatofanaircra’fts has turned conformal antennas to an attractive choice for nose. Conformal antennas and antenna arrays (arrays) have civilian applications as well, from train antennas to car radio become necessary for vehicular communications (where a antennas in order to improve shape and aesthetics as well high degree of aerodynamic drag reduction is needed) due to as increase vehicle performance, and to cellular base station their so-called “conformity” to arbitrary surface shape, like in antennas to save space and make antennas less visually avionics and high-performance ships or submarines. intrusive [1]. Conformal antennas were developed in the 1980s in order Conformal antennas may also be used in maritime com- to be integrated with the outer metallic layers of aircrasft , with munications and shipping applications, to not only reduce thepurposeofreducingtheaerodynamicdragandimproving aerodynamic or—in this case—“hydrodynamic” drag, but aircraft speed, fuel consumption, and gas emissions. Con- also oer ff the ability to integrate more antenna elements formal antennas gradually replaced conventional ones that in the ship’s hull, oer ff ing a very large surface for antenna 2 Advances in Power Electronics Ramasami’s API Population of is used to provide In-house predefined size EM models for developed GA and each chromosomes chromosome No In-house code EM solver is used performance parses .txt file and to provide EM Is max number results stored returns fitness performance of of generation function of each locally in .txt file reached? each chromosome chromosome Yes Optimization termination Figure 1: Flowchart of the proposed GA-based optimization platform for arbitrary-shape patch antennas. deploymentthatcouldinturnyieldtoincreasedperformance antenna and antenna arrays optimization problems as well. with limited overall antenna profile (volume, visually intru- The flexibility and performance of the proposed platform are siveness). Such an example of a GPS-receiving patch antenna demonstrated herein via the design of a high-performance is presented in this paper that demonstrates the abilities and GPS patch antenna. performance of a proposed platform for arbitrary-shape flat eTh rest of the paper is organized as follows. Section 2 antennas design and optimization. eTh choice of a GPS- illustrates an overall presentation of the proposed platform appropriate antenna has been made on the basis that GPS has for the design of arbitrary-shape flat antennas, while Section 3 become one of the top most important services necessary for discusses in short the concept of patch antennas. Section 4 a ship nowadays; GPS is used in ships not only to monitor discusses the specifics of the genetic algorithm that has been its route and navigation, but also for safety and security. employed for antenna optimization. Section 5 illustrates a Other, more sophisticated GPS applications in shipping GPS-suitable receiving antenna that was optimized using the include synchronizing phasor measurement units for hybrid proposed platform, and the paper concludes with Section 6. state estimators to provide estimates from SCADA control 2. Integrated Platform for Antenna Design units on board, like electric power quality, ship performance monitoring, hull and machinery structural fatigue, and so The proposed platform for antenna and antenna array design forth [2], or speed determination with high accuracy, or even is based on combining an EM solver with an in-house engine speed determination [3]. developed GA solution. The proposed GA solution has been On top of the high related costs of integration, conformal used in the past for the design and optimization of dipole antennas also sueff r from severe constraints imposed on their antennas and antenna arrays [4–6] and is written with the design that arise due to the predefined and oen ft counterpro- MATLAB programming language. ductive shape of the flat area that they need to conform with. In theproposedscheme, theGAisusedinorder to This affects the performance of the antenna array, its shape, congfi ure an initial population of 80 chromosomes (more the elements spacing, the relative signal phase, and so forth. information on GA terminology and literature is available Thereupon, it is necessary to investigate counterintuitive and in Section 4), that are then converted to valid EM models. arbitrary antenna shapes in order to compensate for these Each modelissimulated,and theresults arelocally stored in constraints. Since there does not exist any available theo- a .txt file. en, Th our platform parses the .txt file and returns retical frame for designing and developing arbitrary-shape the tfi ness function of each chromosome to the GA. After antennas in a straightforward manner, we have developed a the execution of the aforementioned steps for the initial combination of a genetic algorithm- (GA-) based design and population, our GA employs selection, mating, and mutation an electromagnetic (EM) solver for designing patch antennas tactics to develop new generations up to a maximum of 100 with a shape that is not a priori known (the genetic algorithm generations. The proposed platform’s internal structure is optimizes the shape of the patch antenna together with its illustrated in Figure 1. othercharacteristics).TheproposedGAisofhighperfor- mance and proved in practice to deliver antenna patches 3. Patch Antennas of arbitrary shapes but of leveraged performance and low profile. Moreover, it is anticipated that the proposed platform Microstrip patch antennas were rfi st introduced during the is of generic use and may be readily deployed to other second half of the twentieth century and are based on Advances in Power Electronics 3 𝑧𝑦 ℎ Radiating patch Feeding line Patch Ground plane Feeding transmission line Dielectric substrate Radiating patch Dielectric substrate ··· Figure 2: Patch antenna schematic example. Ground plate Feeding probe Figure 3: Various patch feeding techniques. the observance that microstrips may radiate electromag- netic waves efficiently given certain limitations [ 7]. A patch antenna schematic example is depicted in Figure 2. eTh width and length of the patch are illustrated in the top been widely used for electromagnetic optimization [9–11]. In side of Figure 2, together with the feeding transmission line GAs, the problem under search is properly parameterized, (the line is connected to the source). Also, there are a substrate and a set of possible solution vectors or chromosomes is of thicknessℎ and a ground plane. eTh substrate has a relative randomly generated. eTh elements of each vector or genes permittivity equal to𝜀 , while the thickness of the patch is correspond to the problem parameters. eTh set of chromo- equal to𝑡 . somes is referred to as population or generation. A tfi ness Due to inherent design limitations, patch antennas usu- function value is assigned to each chromosome, evaluating ally radiate most effectively towards the direction that is its suitability as a potential problem solution. Then, the perpendicular to the substrate surface and opposite to the stochastic search of the solution space is performed through ground plane. Note that, by convention, there is a Cartesian a simulated genetic evolution, using selection, crossover, and coordinates system as the one depicted in the top side of mutation operators. New populations are generated, and the Figure 2,sothatthe𝑧 -axisisalwaysinlinewiththe boresight procedure is repeated, until a termination criterion is met. of the patch. GAs are considered to have certain advantages over other Different patch layouts are proposed in the literature, heuristic methods currently used, like the Particle Swarm yielding rectangular, circular, ring, or other complex patch Optimization (PSO) or the Simulated Annealing methods layouts. Nevertheless, there are no analytic expressions for (SA). Even though it is difficult to establish a benchmark for arbitrary-shape patches, like the one we propose herein; in heuristics algorithms [12], hands-on experience has shown such cases, one can only work with numerical electromag- that GAs converge faster and more oen ft than other heuristic netic solvers. methods currently available, but one should always bear Furthermore, a patch antenna may be fed using either in mind that convergence heavily depends on the specific a microstrip or coaxial probes (see Figure 3), or even using algorithm implementation [13]. sophisticated techniques of induced fields due to proximity eTh GA used herein has been in-house developed based to nearby transmission lines, and so forth [7, 8]. The patch on the work reported by Houck et al. [14]and hasbeenused antenna proposed herein is using a coaxial probe feeding in the past in various dipole-antennas designs [4–6]. The GA technique (like in Figure 3, bottom side) with a standard SMA is of the floating point type, while the functions of selection, connector and cables. crossover, and mutation are of roulette, simple or arithmetic, and uniform type, respectively. eTh population size is 80, while the maximum number of generations has been set up 4. Genetic Algorithm and Fitness to 100. Function Used eTh arbitrary patch of the antenna is optimized as follows: GAs are a robust class of stochastic optimization algorithms, at first, one chromosome gene is designated to correspond especially suited for nonlinear, nondifferential, multiobjec- to the patch’s width and one more to the patch’s length tive, and multidimensional optimization problems. ey Th have (see Figure 2). The genes’ boundaries are subject to intuitive been introduced in early 1960s, but only recently have they decision of the designer (for a 1.5 GHz patch we set them 4 Advances in Power Electronics Then, the tfi ness function takes into account that the 1 ··· reflection coefficient, 𝑆 ,mustbelessthan−10 dB; thereupon 4 ··· it calculates another error value as in (10−𝑆 ) (2) 𝑒 =[ ]. “1110001001100110” Moreover, the tfi ness 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. u Th s, the fitness function also calculates a third error term as in 𝜙=360 𝑒 = ∑ (MeanGain − Gain (𝜙)) , (3) 3 phi phi 𝜙=0 where MeanGain is themeanhorizontalover𝜙 for𝜃=20 , phi and Gain (𝜙) is the horizontal gain versus𝜙 for𝜃=20 . phi Finally, thecumulativeerror is calculated by Figure 4: Patch antenna schematic example. 𝐴=𝑤 ⋅𝑒 +𝑤 ⋅𝑒 +𝑤 ⋅𝑒 , (4) 1 1 2 2 3 3 where𝑤 is the weight of the error𝑒 ,and thefitnessfunction 1 𝑖 value is calculated by up as between 2 cm and 12 cm). en, Th the patch surface is split into 100 tiny rectangles, each of which has dimensions 1 Fitness= . (5) equal to𝑊/10×𝐿/10 . en, Th another 100 genes are assigned 1+ 𝐴 with a binary value of either 0 or 1, with “0” corresponding The specific formula for ( 5) is heuristic and implies to “no metal” and “1” corresponding to “metal.” This means that a “good” chromosome with a low cumulative error that if the GA assigns the value of “0” to a gene, then at will correspond to a tfi ness function value tending to unity, the respective tiny rectangle there will be no metallic patch while a “bad” chromosome with a large cumulative error will surface(andviceversa in thecaseof“1”). uTh s, apatch correspond to a tfi ness function value tending to zero. of arbitrary shape is generated; by “arbitrary” we refer to both its dimensions and its specific shape since its surface varies according to the respective chromosome. For example, 5. Design of a Flat Patch Antenna for consider in Figure 4 thecaseofapatchwith16(insteadof GPS Applications 100) tiny rectangles. In the case where the chromosome had the value of “1110001001100110” assigned to the “metal or no Various runs of the proposed GA optimization platform have metal” genes, then the patch shape would look like the one in been executed with the purpose of designing a patch antenna the bottom of Figure 4. of arbitrary shape suitable for applications around 1.5 GHz, Finally, a GA’s performance strongly depends on the like a GPS receiver. eTh substrate of the patch antenna should design of its tfi ness function. eTh tfi ness function of the be of theFR4 type,withasubstratethickness of 1.6mmand proposed GA is developed as follows: aer ft a patch model is adielectricconstantequal to𝜀 = 4.6.Furthermore,the generated by the GA’s chromosome, it is passed to the EM patch antenna should be fed via standardized SMA cables solver according to Figure 1.TheEMsolverthenoutputs a.txt and connectors that are also integrated in the simulation, file that includes the gain, radiation pattern, and reflection design, and optimization of the patch. Further specifications coefficient of the patch. The tfi ness function takes into of the antenna include a maximum gain as high as possible accountthatthe maximumgainofthe patchmustbethe at𝜃=0 (referring to Figure 2 and with a specicfi target of highest possible; thereupon it rfi st calculates an error value a gain larger than 4 dBi, since this is a rather usual gfi ure in using most commercial patch elements), a reflection coefficient as low as possible (with a specific target of −10 dB, since this is considered to be theruleofthumb forRFand microwave components), and a bandwidth as large as possible. (5− MaxGain) (1) 𝑒 =[ ], 1 After multiple runs it was decided that the various weights of thefitnessfunctionshouldbeassigned, so as thefinalform of thelattershouldbe whereMaxGain is themaximum gain of thepatch.Thevalue 𝐴=4⋅𝑒 +2⋅𝑒 +1.8⋅𝑒 . (6) 1 2 3 of “5” is selected since the majority of commercially available patch antennas exhibits a gain of around 4 dBi; thus with this With this adjustment, the GA was again executed multiple selection our patch is forced to outmatch this limit getting times, and the most promising patch antenna for GPS closeto5dBi. applications is presented herein. Advances in Power Electronics 5 References [1] L. Josefsson and P. Persson, Conformal Array Antenna eTh ory and Design, IEEE Press and John Wiley & Sons, Hoboken, NJ, USA, 2006. Feeding probe [2] A.G.Phadkeand J. S. oTh rp, Synchronized Phasor Measure- ments and Their Applications , Springer Science and Business Media, Springer, 2008. Patch [3] Z.S.Filipi andD.N.Assanis,“Anonlinear,transient,single- cylinder diesel engine simulation for predictions of instanta- 𝑊 neous engine speed and torque,” Journal of Engineering for Gas Turbines and Power,vol.123,no. 4, pp.951–959,2001. [4] S. A. Mitilineos, K. S. Mougiakos, and S. C. A. o Th mopoulos, “Design and optimization of ESPAR antennas via impedance measurements and a genetic algorithm (antenna designer’s notebook),” IEEE Antennas and Propagation Magazine,vol.51, Substrate no. 2, pp. 118–123, 2009. [5] S. A. Mitilineos and C. N. Capsalis, “A new, low-cost, switched beam and fully adaptive antenna array for 2.4 GHz ISM appli- 𝐿=13.4 cm cations,” IEEE Transactions on Antennas and Propagation,vol. 55,no. 9, pp.2502–2508,2007. Figure 5: Layout of the optimized patch antenna (top view). [6] S. A. Mitilineos, P. I. Papakanellos, and C. N. Capsalis, “Com- pensation for elements discrepancies in array development using genetic algorithms,” in Proceedings of the European Microwave Association,vol.2,pp. 269–273, September2006. [7] N.A.Stathopoulos,S.P.Savaidis, andS.A.Mitilineos, “RF Table 1: Technical characteristics and performance results of the measurements and characterization of conductive textile mate- optimized patch antenna. rials,” in Electronics and Computing in Textiles,S.Vassiliadis, Ed., Ventus Publishing ApS, 2012. 1.5 Central frequency (GHz) [8] C. A. Balanis, Antenna eor Th y: Analysis and Design ,JohnWiley Total maximum gain (e- and H-plane) at central & Sons, Hoboken, NJ, USA, 2005. frequency (dBi) [9] R. L. Haupt, “Introduction to genetic algorithms for electromag- −14 Reflection coefficient at central frequency (dB) netics,” IEEE Antennas and Propagation Magazine,vol.37, no.2, 0.3 Standard deviation of horizontal gain for𝜃 =20 (dB) pp. 7–15, 1995. Bandwidth (MHz) [10] J. M. Johnson and Y. Rahmat-Samii, “Genetic algorithms in engineering electromagnetics,” IEEE Antennas and Propagation Magazine,vol.39, no.4,pp. 7–21,1997. [11] Y. R. Samii and E. Michielssen, Electromagnetic Optimization by Genetic Algorithms, John Wiley & Sons, 1999. eTh layout of the patch antenna is illustrated in Figure 5, [12] A. Stefek, “Benchmarking of heuristic optimization methods,” while a summary of its performance results is tabulated in in Proceedings of the 14th MECHATRONIKA International Table 1. It is considered that the optimized patch antenna Symposium, Trencianske Teplice, Slovakia, June 2011. exhibits superior gain (5 dBi) compared to the literature and [13] S.A.Mitilineos, Mitigation of Multipath Fading Using Smart commercially available elements, with a low profile and easily Antenas [Ph.D. thesis], NTUA Press, Athens, Greece, October converted to a conformal antenna. It is worthwhile noting that similar performance is usually available from antennas [14] C. R. Houck, J. A. Joines, and M. G. Kay, “A genetic algorithm that are of signicfi antly larger dimensions. for function optimization: a MATLAB implementation,” Tech. Rep. NCSU-IE 95-09, 1995. 6. Conclusions 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 atypeofantennasthatneed 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. =13.45 cm International Journal of Rotating Machinery International Journal of Journal of The Scientific Journal of Distributed Engineering World Journal Sensors Sensor Networks Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 Volume 2014 Journal of Control Science and Engineering Advances in Civil Engineering Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 Submit your manuscripts at http://www.hindawi.com Journal of Journal of Electrical and Computer Robotics Engineering Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 VLSI Design Advances in OptoElectronics International Journal of Modelling & Aerospace International Journal of Simulation Navigation and in Engineering Engineering Observation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Volume 2014 http://www.hindawi.com Volume 2014 Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com http://www.hindawi.com Volume 2014 International Journal of Active and Passive International Journal of Antennas and Advances in Chemical Engineering Propagation Electronic Components Shock and Vibration Acoustics and Vibration Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Advances in Power Electronics Hindawi Publishing Corporation

Conformal Patch Antenna Arrays Design for Onboard Ship Deployment Using Genetic Algorithms

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Copyright © 2013 Stelios A. Mitilineos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Hindawi Publishing Corporation Advances in Power Electronics Volume 2013, Article ID 960514, 5 pages http://dx.doi.org/10.1155/2013/960514 Research Article Conformal Patch Antenna Arrays Design for Onboard Ship Deployment Using Genetic Algorithms 1 1 2 1 Stelios A. Mitilineos, Symeon K. Symeonidis, Ioannis B. Mpatsis, Dimitrios Iliopoulos, 3 1 1 Georgios S. Kliros, Stylianos P. Savaidis, and Nikolaos A. Stathopoulos Technologial Educational Institute of Piraeus, Department of Electronics, 250, Petrou Ralli kai iTh von Street, 12244 Aigaleo, Greece Hellenic Air Force Academy, Dekeleia Air-Force Base, Dekeleia, Greece Department of Aeronautical Sciences, Hellenic Air Force Academy, Dekeleia Air-Force Base, Dekeleia, Greece Correspondence should be addressed to Stelios A. Mitilineos; smitil@gmail.com Received 17 October 2012; Accepted 17 February 2013 Academic Editor: John Prousalidis Copyright © 2013 Stelios A. Mitilineos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 aircra’fts nose) directly aeff cts 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). eTh 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. eTh flexibility and performance of the proposed platform are demonstrated herein via the design of a high- performance GPS patch antenna. 1. Introduction project from the aircrafts’ hull. As long as commercial appli- cations are considered (including shipping), the technical Conformal antennas and antenna arrays (arrays) inherit their limitations and constraints are similar to avionics, but the name from the fact that they “conform” to the shape of a 2D application of conformal antennas was until recently limited yet not planar surface. More specicfi ally, conformal antennas due to the high related costs of etching and integration. are flat curving antennas that follow or are embedded to However, in the recent years the reduction of these costs an object of predenfi edshape,likethatofanaircra’fts has turned conformal antennas to an attractive choice for nose. Conformal antennas and antenna arrays (arrays) have civilian applications as well, from train antennas to car radio become necessary for vehicular communications (where a antennas in order to improve shape and aesthetics as well high degree of aerodynamic drag reduction is needed) due to as increase vehicle performance, and to cellular base station their so-called “conformity” to arbitrary surface shape, like in antennas to save space and make antennas less visually avionics and high-performance ships or submarines. intrusive [1]. Conformal antennas were developed in the 1980s in order Conformal antennas may also be used in maritime com- to be integrated with the outer metallic layers of aircrasft , with munications and shipping applications, to not only reduce thepurposeofreducingtheaerodynamicdragandimproving aerodynamic or—in this case—“hydrodynamic” drag, but aircraft speed, fuel consumption, and gas emissions. Con- also oer ff the ability to integrate more antenna elements formal antennas gradually replaced conventional ones that in the ship’s hull, oer ff ing a very large surface for antenna 2 Advances in Power Electronics Ramasami’s API Population of is used to provide In-house predefined size EM models for developed GA and each chromosomes chromosome No In-house code EM solver is used performance parses .txt file and to provide EM Is max number results stored returns fitness performance of of generation function of each locally in .txt file reached? each chromosome chromosome Yes Optimization termination Figure 1: Flowchart of the proposed GA-based optimization platform for arbitrary-shape patch antennas. deploymentthatcouldinturnyieldtoincreasedperformance antenna and antenna arrays optimization problems as well. with limited overall antenna profile (volume, visually intru- The flexibility and performance of the proposed platform are siveness). Such an example of a GPS-receiving patch antenna demonstrated herein via the design of a high-performance is presented in this paper that demonstrates the abilities and GPS patch antenna. performance of a proposed platform for arbitrary-shape flat eTh rest of the paper is organized as follows. Section 2 antennas design and optimization. eTh choice of a GPS- illustrates an overall presentation of the proposed platform appropriate antenna has been made on the basis that GPS has for the design of arbitrary-shape flat antennas, while Section 3 become one of the top most important services necessary for discusses in short the concept of patch antennas. Section 4 a ship nowadays; GPS is used in ships not only to monitor discusses the specifics of the genetic algorithm that has been its route and navigation, but also for safety and security. employed for antenna optimization. Section 5 illustrates a Other, more sophisticated GPS applications in shipping GPS-suitable receiving antenna that was optimized using the include synchronizing phasor measurement units for hybrid proposed platform, and the paper concludes with Section 6. state estimators to provide estimates from SCADA control 2. Integrated Platform for Antenna Design units on board, like electric power quality, ship performance monitoring, hull and machinery structural fatigue, and so The proposed platform for antenna and antenna array design forth [2], or speed determination with high accuracy, or even is based on combining an EM solver with an in-house engine speed determination [3]. developed GA solution. The proposed GA solution has been On top of the high related costs of integration, conformal used in the past for the design and optimization of dipole antennas also sueff r from severe constraints imposed on their antennas and antenna arrays [4–6] and is written with the design that arise due to the predefined and oen ft counterpro- MATLAB programming language. ductive shape of the flat area that they need to conform with. In theproposedscheme, theGAisusedinorder to This affects the performance of the antenna array, its shape, congfi ure an initial population of 80 chromosomes (more the elements spacing, the relative signal phase, and so forth. information on GA terminology and literature is available Thereupon, it is necessary to investigate counterintuitive and in Section 4), that are then converted to valid EM models. arbitrary antenna shapes in order to compensate for these Each modelissimulated,and theresults arelocally stored in constraints. Since there does not exist any available theo- a .txt file. en, Th our platform parses the .txt file and returns retical frame for designing and developing arbitrary-shape the tfi ness function of each chromosome to the GA. After antennas in a straightforward manner, we have developed a the execution of the aforementioned steps for the initial combination of a genetic algorithm- (GA-) based design and population, our GA employs selection, mating, and mutation an electromagnetic (EM) solver for designing patch antennas tactics to develop new generations up to a maximum of 100 with a shape that is not a priori known (the genetic algorithm generations. The proposed platform’s internal structure is optimizes the shape of the patch antenna together with its illustrated in Figure 1. othercharacteristics).TheproposedGAisofhighperfor- mance and proved in practice to deliver antenna patches 3. Patch Antennas of arbitrary shapes but of leveraged performance and low profile. Moreover, it is anticipated that the proposed platform Microstrip patch antennas were rfi st introduced during the is of generic use and may be readily deployed to other second half of the twentieth century and are based on Advances in Power Electronics 3 𝑧𝑦 ℎ Radiating patch Feeding line Patch Ground plane Feeding transmission line Dielectric substrate Radiating patch Dielectric substrate ··· Figure 2: Patch antenna schematic example. Ground plate Feeding probe Figure 3: Various patch feeding techniques. the observance that microstrips may radiate electromag- netic waves efficiently given certain limitations [ 7]. A patch antenna schematic example is depicted in Figure 2. eTh width and length of the patch are illustrated in the top been widely used for electromagnetic optimization [9–11]. In side of Figure 2, together with the feeding transmission line GAs, the problem under search is properly parameterized, (the line is connected to the source). Also, there are a substrate and a set of possible solution vectors or chromosomes is of thicknessℎ and a ground plane. eTh substrate has a relative randomly generated. eTh elements of each vector or genes permittivity equal to𝜀 , while the thickness of the patch is correspond to the problem parameters. eTh set of chromo- equal to𝑡 . somes is referred to as population or generation. A tfi ness Due to inherent design limitations, patch antennas usu- function value is assigned to each chromosome, evaluating ally radiate most effectively towards the direction that is its suitability as a potential problem solution. Then, the perpendicular to the substrate surface and opposite to the stochastic search of the solution space is performed through ground plane. Note that, by convention, there is a Cartesian a simulated genetic evolution, using selection, crossover, and coordinates system as the one depicted in the top side of mutation operators. New populations are generated, and the Figure 2,sothatthe𝑧 -axisisalwaysinlinewiththe boresight procedure is repeated, until a termination criterion is met. of the patch. GAs are considered to have certain advantages over other Different patch layouts are proposed in the literature, heuristic methods currently used, like the Particle Swarm yielding rectangular, circular, ring, or other complex patch Optimization (PSO) or the Simulated Annealing methods layouts. Nevertheless, there are no analytic expressions for (SA). Even though it is difficult to establish a benchmark for arbitrary-shape patches, like the one we propose herein; in heuristics algorithms [12], hands-on experience has shown such cases, one can only work with numerical electromag- that GAs converge faster and more oen ft than other heuristic netic solvers. methods currently available, but one should always bear Furthermore, a patch antenna may be fed using either in mind that convergence heavily depends on the specific a microstrip or coaxial probes (see Figure 3), or even using algorithm implementation [13]. sophisticated techniques of induced fields due to proximity eTh GA used herein has been in-house developed based to nearby transmission lines, and so forth [7, 8]. The patch on the work reported by Houck et al. [14]and hasbeenused antenna proposed herein is using a coaxial probe feeding in the past in various dipole-antennas designs [4–6]. The GA technique (like in Figure 3, bottom side) with a standard SMA is of the floating point type, while the functions of selection, connector and cables. crossover, and mutation are of roulette, simple or arithmetic, and uniform type, respectively. eTh population size is 80, while the maximum number of generations has been set up 4. Genetic Algorithm and Fitness to 100. Function Used eTh arbitrary patch of the antenna is optimized as follows: GAs are a robust class of stochastic optimization algorithms, at first, one chromosome gene is designated to correspond especially suited for nonlinear, nondifferential, multiobjec- to the patch’s width and one more to the patch’s length tive, and multidimensional optimization problems. ey Th have (see Figure 2). The genes’ boundaries are subject to intuitive been introduced in early 1960s, but only recently have they decision of the designer (for a 1.5 GHz patch we set them 4 Advances in Power Electronics Then, the tfi ness function takes into account that the 1 ··· reflection coefficient, 𝑆 ,mustbelessthan−10 dB; thereupon 4 ··· it calculates another error value as in (10−𝑆 ) (2) 𝑒 =[ ]. “1110001001100110” Moreover, the tfi ness 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. u Th s, the fitness function also calculates a third error term as in 𝜙=360 𝑒 = ∑ (MeanGain − Gain (𝜙)) , (3) 3 phi phi 𝜙=0 where MeanGain is themeanhorizontalover𝜙 for𝜃=20 , phi and Gain (𝜙) is the horizontal gain versus𝜙 for𝜃=20 . phi Finally, thecumulativeerror is calculated by Figure 4: Patch antenna schematic example. 𝐴=𝑤 ⋅𝑒 +𝑤 ⋅𝑒 +𝑤 ⋅𝑒 , (4) 1 1 2 2 3 3 where𝑤 is the weight of the error𝑒 ,and thefitnessfunction 1 𝑖 value is calculated by up as between 2 cm and 12 cm). en, Th the patch surface is split into 100 tiny rectangles, each of which has dimensions 1 Fitness= . (5) equal to𝑊/10×𝐿/10 . en, Th another 100 genes are assigned 1+ 𝐴 with a binary value of either 0 or 1, with “0” corresponding The specific formula for ( 5) is heuristic and implies to “no metal” and “1” corresponding to “metal.” This means that a “good” chromosome with a low cumulative error that if the GA assigns the value of “0” to a gene, then at will correspond to a tfi ness function value tending to unity, the respective tiny rectangle there will be no metallic patch while a “bad” chromosome with a large cumulative error will surface(andviceversa in thecaseof“1”). uTh s, apatch correspond to a tfi ness function value tending to zero. of arbitrary shape is generated; by “arbitrary” we refer to both its dimensions and its specific shape since its surface varies according to the respective chromosome. For example, 5. Design of a Flat Patch Antenna for consider in Figure 4 thecaseofapatchwith16(insteadof GPS Applications 100) tiny rectangles. In the case where the chromosome had the value of “1110001001100110” assigned to the “metal or no Various runs of the proposed GA optimization platform have metal” genes, then the patch shape would look like the one in been executed with the purpose of designing a patch antenna the bottom of Figure 4. of arbitrary shape suitable for applications around 1.5 GHz, Finally, a GA’s performance strongly depends on the like a GPS receiver. eTh substrate of the patch antenna should design of its tfi ness function. eTh tfi ness function of the be of theFR4 type,withasubstratethickness of 1.6mmand proposed GA is developed as follows: aer ft a patch model is adielectricconstantequal to𝜀 = 4.6.Furthermore,the generated by the GA’s chromosome, it is passed to the EM patch antenna should be fed via standardized SMA cables solver according to Figure 1.TheEMsolverthenoutputs a.txt and connectors that are also integrated in the simulation, file that includes the gain, radiation pattern, and reflection design, and optimization of the patch. Further specifications coefficient of the patch. The tfi ness function takes into of the antenna include a maximum gain as high as possible accountthatthe maximumgainofthe patchmustbethe at𝜃=0 (referring to Figure 2 and with a specicfi target of highest possible; thereupon it rfi st calculates an error value a gain larger than 4 dBi, since this is a rather usual gfi ure in using most commercial patch elements), a reflection coefficient as low as possible (with a specific target of −10 dB, since this is considered to be theruleofthumb forRFand microwave components), and a bandwidth as large as possible. (5− MaxGain) (1) 𝑒 =[ ], 1 After multiple runs it was decided that the various weights of thefitnessfunctionshouldbeassigned, so as thefinalform of thelattershouldbe whereMaxGain is themaximum gain of thepatch.Thevalue 𝐴=4⋅𝑒 +2⋅𝑒 +1.8⋅𝑒 . (6) 1 2 3 of “5” is selected since the majority of commercially available patch antennas exhibits a gain of around 4 dBi; thus with this With this adjustment, the GA was again executed multiple selection our patch is forced to outmatch this limit getting times, and the most promising patch antenna for GPS closeto5dBi. applications is presented herein. Advances in Power Electronics 5 References [1] L. Josefsson and P. Persson, Conformal Array Antenna eTh ory and Design, IEEE Press and John Wiley & Sons, Hoboken, NJ, USA, 2006. Feeding probe [2] A.G.Phadkeand J. S. oTh rp, Synchronized Phasor Measure- ments and Their Applications , Springer Science and Business Media, Springer, 2008. Patch [3] Z.S.Filipi andD.N.Assanis,“Anonlinear,transient,single- cylinder diesel engine simulation for predictions of instanta- 𝑊 neous engine speed and torque,” Journal of Engineering for Gas Turbines and Power,vol.123,no. 4, pp.951–959,2001. [4] S. A. Mitilineos, K. S. Mougiakos, and S. C. A. o Th mopoulos, “Design and optimization of ESPAR antennas via impedance measurements and a genetic algorithm (antenna designer’s notebook),” IEEE Antennas and Propagation Magazine,vol.51, Substrate no. 2, pp. 118–123, 2009. [5] S. A. Mitilineos and C. N. Capsalis, “A new, low-cost, switched beam and fully adaptive antenna array for 2.4 GHz ISM appli- 𝐿=13.4 cm cations,” IEEE Transactions on Antennas and Propagation,vol. 55,no. 9, pp.2502–2508,2007. Figure 5: Layout of the optimized patch antenna (top view). [6] S. A. Mitilineos, P. I. Papakanellos, and C. N. Capsalis, “Com- pensation for elements discrepancies in array development using genetic algorithms,” in Proceedings of the European Microwave Association,vol.2,pp. 269–273, September2006. [7] N.A.Stathopoulos,S.P.Savaidis, andS.A.Mitilineos, “RF Table 1: Technical characteristics and performance results of the measurements and characterization of conductive textile mate- optimized patch antenna. rials,” in Electronics and Computing in Textiles,S.Vassiliadis, Ed., Ventus Publishing ApS, 2012. 1.5 Central frequency (GHz) [8] C. A. Balanis, Antenna eor Th y: Analysis and Design ,JohnWiley Total maximum gain (e- and H-plane) at central & Sons, Hoboken, NJ, USA, 2005. frequency (dBi) [9] R. L. Haupt, “Introduction to genetic algorithms for electromag- −14 Reflection coefficient at central frequency (dB) netics,” IEEE Antennas and Propagation Magazine,vol.37, no.2, 0.3 Standard deviation of horizontal gain for𝜃 =20 (dB) pp. 7–15, 1995. Bandwidth (MHz) [10] J. M. Johnson and Y. Rahmat-Samii, “Genetic algorithms in engineering electromagnetics,” IEEE Antennas and Propagation Magazine,vol.39, no.4,pp. 7–21,1997. [11] Y. R. Samii and E. Michielssen, Electromagnetic Optimization by Genetic Algorithms, John Wiley & Sons, 1999. eTh layout of the patch antenna is illustrated in Figure 5, [12] A. Stefek, “Benchmarking of heuristic optimization methods,” while a summary of its performance results is tabulated in in Proceedings of the 14th MECHATRONIKA International Table 1. It is considered that the optimized patch antenna Symposium, Trencianske Teplice, Slovakia, June 2011. exhibits superior gain (5 dBi) compared to the literature and [13] S.A.Mitilineos, Mitigation of Multipath Fading Using Smart commercially available elements, with a low profile and easily Antenas [Ph.D. thesis], NTUA Press, Athens, Greece, October converted to a conformal antenna. It is worthwhile noting that similar performance is usually available from antennas [14] C. R. Houck, J. A. Joines, and M. G. Kay, “A genetic algorithm that are of signicfi antly larger dimensions. for function optimization: a MATLAB implementation,” Tech. Rep. NCSU-IE 95-09, 1995. 6. Conclusions 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 atypeofantennasthatneed 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. =13.45 cm International Journal of Rotating Machinery International Journal of Journal of The Scientific Journal of Distributed Engineering World Journal Sensors Sensor Networks Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 Volume 2014 Journal of Control Science and Engineering Advances in Civil Engineering Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 Submit your manuscripts at http://www.hindawi.com Journal of Journal of Electrical and Computer Robotics Engineering Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 VLSI Design Advances in OptoElectronics International Journal of Modelling & Aerospace International Journal of Simulation Navigation and in Engineering Engineering Observation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Volume 2014 http://www.hindawi.com Volume 2014 Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com http://www.hindawi.com Volume 2014 International Journal of Active and Passive International Journal of Antennas and Advances in Chemical Engineering Propagation Electronic Components Shock and Vibration Acoustics and Vibration Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation Hindawi Publishing Corporation http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014 http://www.hindawi.com Volume 2014

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