This paper introduces a hybrid optimization method, which combines particle swarm optimization and genetic algorithm for antenna array pattern synthesis. The algorithm first removes a quarter of the individuals with a...
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ISBN:
(纸本)9789811903908;9789811903892
This paper introduces a hybrid optimization method, which combines particle swarm optimization and genetic algorithm for antenna array pattern synthesis. The algorithm first removes a quarter of the individuals with a lower fitness value, and copies the remaining individuals with a middle third of the fitness values to form a new population. Then particle swarm optimization and genetic algorithm are carried out, and particle swarm thinking is introduced into mutation operator. This algorithm can better solve the optimization problems of multidimensional and nonlinear problems. The excitation amplitude and phase of the array elements are optimized to achieve the desired low sidelobe level and deep zeros. Our empirical results show that, the proposed method outperforms existing methods according to convergency, efficiency and optimization.
The proposed method allows very rapid synthesis of large antennaarrays, affording footprint patterns of satisfactory quality. It is possible to reduce the number of array elements by reducing the number of filled nul...
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ISBN:
(纸本)9781424449682
The proposed method allows very rapid synthesis of large antennaarrays, affording footprint patterns of satisfactory quality. It is possible to reduce the number of array elements by reducing the number of filled nulls of the modified Elliott-Stern pattern that is sampled at the expense of reducing of the average slope of the pattern (dropoff rate) and a small reduction in the pattern directivity. Furthermore, by combination of the Elliott-Stern method and a 3D version of Woodward-Lawson method it is possible to perform rapid synthesis of irregular footprints generated by conformal arrays that are too large to allow direct optimization of array excitations by numerical methods.
A novel approach to arbitrary arraypatternsynthesis is proposed. It is based on the minimax algorithm originally developed for mismatched filter design for radars with pulse compression. The proposed approach allows...
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A novel approach to arbitrary arraypatternsynthesis is proposed. It is based on the minimax algorithm originally developed for mismatched filter design for radars with pulse compression. The proposed approach allows the user to define the pattern mainlobe beam width and the sidelobe envelope shape.
This article presents a versatile patternsynthesis algorithm for controlling the sidelobe level and nulling region for circular antennaarrays. Nonuniform fast Fourier transform using the min-max interpolation method...
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This article presents a versatile patternsynthesis algorithm for controlling the sidelobe level and nulling region for circular antennaarrays. Nonuniform fast Fourier transform using the min-max interpolation method is utilized to overcome the nonlinear feature of circular arrays. The major advantage of the proposed algorithm is low complexity, which is key for hardware implementation. Moreover, the proposed algorithm functions well in amplitude-only patternsynthesis, which may be required for low-cost array systems using attenuators instead of complete amplitude and phase adjustment modules. Additionally, element failure of antennaarrays can be minimized in practical operations by resynthesizing the pattern by using the remaining antennas to achieve satisfactory performance. Simulation results indicate the lower complexity and higher versatility of the proposed algorithm compared with the conventional methods.
A method to carry oat the patternsynthesis of arbitrary arrayantennas is presented This method uses the simulated annealing technique to calculate the power interferences described in the Olen-Compton method Its app...
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A method to carry oat the patternsynthesis of arbitrary arrayantennas is presented This method uses the simulated annealing technique to calculate the power interferences described in the Olen-Compton method Its application to a linens array of 16 unequally spaced nonidentical elements and to a circular are array of 25 axial dipoles is shown in order to illustrate its efficiency and accuracy. (C) 1999 John Wiley & Sons, Inc.
作者:
Chen, JieYin, YingzengXian Aeronaut Univ
Sch Elect Engn 259 Xian West Second Ring Rd Xian 710077 Peoples R China Xidian Univ
Sch Elect Engn Natl Key Lab Antenna & Microwave Technol Xian Peoples R China
A novel equation for array beam patternsynthesis is presented. The expected pattern total power is set to a fixed value, under this constraint, the difference between the main beam total power and the other part tota...
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A novel equation for array beam patternsynthesis is presented. The expected pattern total power is set to a fixed value, under this constraint, the difference between the main beam total power and the other part total power is maximized to achieve the arraypatternsynthesis. To solve the proposed patternsynthesis equation, which cannot be solved by any published traditional method, based on the Lagrange multiplier method, it is transformed into a new equation in which the array element excitation vector is the eigenvector of a matrix. Thus, the array element excitation vector can be obtained by matrix eigenvalue decomposition. Three array architectures using the method are taken as examples to show its advantages. Simulation results of the examples show that the method has better performance than other methods. The method is a noniterative approach, so it requires less computational volume to complete the patternsynthesis process. In addition, through eigenvalue decomposition, multiple eigenvectors can provide other different solutions of array elements current excitations, which can be applied in different areas.
A hybrid approach to the synthesis of excitations and locations of nonuniformly spaced arrays in order to achieve optimal focusing in any given direction is proposed and discussed. The approach takes definite advantag...
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A hybrid approach to the synthesis of excitations and locations of nonuniformly spaced arrays in order to achieve optimal focusing in any given direction is proposed and discussed. The approach takes definite advantage from the convexity of the problem with respect to excitation variables, and exploits a Simulated Annealing procedure as far as location variables are concerned. The corresponding synthesized patterns outperform previously known results in standard benchmark problems.
Footprint patterns can be efficiently synthesized by means of planar arrays with hundreds or thousands of elements: an efficient combination of Woodward-Lawson and Orchard-Elliott-Stern roots optimization procedure is...
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Footprint patterns can be efficiently synthesized by means of planar arrays with hundreds or thousands of elements: an efficient combination of Woodward-Lawson and Orchard-Elliott-Stern roots optimization procedure is suggested. This hybrid technique is applied to a footprint covering Europe by using planar arrays with isotropic elements and linearly polarized circular patches. The proposed method keeps under control both the side lobe and ripple level of the synthesized pattern.
A conventional antennaarraypattern design is based on the amplitude of the radiation pattern, as the angular phase properties of the radiation pattern are generally not considered interesting. This paper discusses a...
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A conventional antennaarraypattern design is based on the amplitude of the radiation pattern, as the angular phase properties of the radiation pattern are generally not considered interesting. This paper discusses a different kind of a design method, where the phase pattern has its significance ns a factor behind the multiplicity of the amplitude pattern. The design method can be used in the planning process of base-station antennaarrays for mobile communications. (C) 2000 John Wiley & Sons, Inc.
Particle swarm optimization (PSO) is a well-known swarm intelligence algorithm inspired by the foraging behavior of bird flocking. PSO has been widely used in many optimization and engineering problems due to its simp...
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Particle swarm optimization (PSO) is a well-known swarm intelligence algorithm inspired by the foraging behavior of bird flocking. PSO has been widely used in many optimization and engineering problems due to its simplicity and efficiency, even though there still exist some disadvantages. The standard PSO often suffers with premature convergence or slow convergence when the optimization problem is multimodal or high-dimensional. To overcome these drawbacks, an ecosystem PSO (ESPSO) inspired by the characteristic that a natural ecosystem can excellently keep the biological diversity and make the whole ecosystem be in a dynamic balance is presented in this paper. ESPSO not only prevents the algorithm trapping into local optima but also balances the exploration and exploitation in both unimodal and multimodal problems as compared to other PSO variants. Twenty benchmark functions including unimodal functions and multimodal nonlinear functions are used to test the searching ability of ESPSO. Experimental results show that ESPSO considerably improves the searching accuracy, the algorithm reliability and the searching efficiency in comparison with other six well-known PSO variants and four evolutionary algorithms. Moreover, ESPSO was successfully applied to the antenna array pattern synthesis design and gained satisfactory results.
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