Shaped beam pattern synthesis with desired nulling level and minimum sidelobe level

For the anti-interference/denoise purpose,it usually requires minimizing the sidelobe level(SLL)of a wide-beam pattern with a desired low nulling level(NL)in the nulling region.To realize such an objective,the shaped-beam pattern synthesis(SBPS)is the most commonly used approach.However,since the SBPS problem focuses on synthesizing a predetermined beam shape,the minimum SLL via this approach cannot ensure to obtain the maximum power gain.Conversely,it cannot obtain the lowest SLL with a certain power gain requirement.Based on such consideration,this paper tries to further minimize SLL of a wide-beam pattern with a desired low NL nulling region,by solving the power gain pattern synthesis(PGPS)problem.The PGPS problem selects the array excitation by directly optimizing the power gain.Hence,it has the potential to reduce SLL,when achieving the equal mainlobe power gain constraint via SBPS.An iterative algorithm which converts the primal optimization problem into convex sub-problems is proposed,resulting in an effective problem-solving scheme.Numerical simulations demonstrate the proposed algorithm can obtain about 10-dB lower SLL than the existing algorithms.

Pattern synthesis optimization of 3-D ODAR based on improved GA using LSFE method

Pattern synthesis in 3-D opportunistic digital array radar(ODAR) becomes complex when a multitude of antennas are considered to be randomly distributed in a three dimensional space.In order to obtain an optimal pattern,several freedoms must be constrained.A new pattern synthesis approach based on the improved genetic algorithm(GA) using the least square fitness estimation(LSFE) method is proposed.Parameters optimized by this method include antenna locations,stimulus states and phase weights.The new algorithm demonstrates that the fitness variation tendency of GA can be effectively predicted after several "eras" by the LSFE method.It is shown that by comparing the variation of LSFE curve slope,the GA operator can be adaptively modified to avoid premature convergence of the algorithm.The validity of the algorithm is verified using computer implementation.

Pattern Synthesis and Polarization Optimization of a Conical Array

A feasible method for synthesizing millimeter-wave conical array and optimizing low cross-polarization is proposed.Starting from the far-field superposition principle,an efficient approach including element mutual coupling and mounted platform effects is used to calculate the far-field patterns.A coordinate transform is applied to create polarization quantities,and a general process for the element polarized pattern transformation is performed.Corresponding numerical example is given and the desired sidelobe level and low cross-polarization are optimized.The numerical results indicate the proposed method is valid.

Array Antenna Pattern Synthesis Based on Selective Levy Flight Culture Wolf Pack Algorithm

Due to the shortcomings such as the premature convergence and the bad local optimal searching capability in traditional intelligence methods for pattern synthesis,a new type of wolf pack algorithm named Levy⁃Cultural Wolf Pack Algorithm(LCWPA)was designed on the basis of the Cultural Wolf Pack Algorithm(CWPA),which obeys the selective Levy flight.Because of the good overall management ability provided by the cultural algorithm in optimization process and the characteristics of excellent population diversity brought by Levy flight,the search efficiency of the new algorithm was greatly improved.When the algorithm was applied in the pattern synthesis of array antenna,the simulation results showed its high performance with multi⁃null and low side⁃lobe restrictions.In addition,the algorithm was superior to the Quantum Particle Swarm Optimization(QPSO),Particle Swarm Optimization(PSO),and Genetic Algorithm(GA)in optimization accuracy and operation speed,and is of very good generalization.

Hybrid alternate projection algorithm and its application for practical conformal array pattern synthesis

Based on the fabricated 12-element cavity-backed microstrip sector cylinder array,a novel hybrid alternate projection algorithm（HAPA）,which combines analytical method with numerical techniques effectively,is proposed for synthesizing the pattern of practical conformal array.The algorithm applies the variable direction aperture projection method with mutual coupling correction techniques to provide the good initial excitations of elements to the enhanced alternate projection algorithm（EAPA）.In order to do further optimization,which improves the convergent speed of the algorithm significantly.Finally,the HAPA has been applied to the fabricated sector cylinder array with mutual coupling considered.The results of synthesized patterns,such as low sidelobe with null points formed pattern,beam scanning with low sidelobe pattern and the shaped beam pattern are presented.It demonstrates the validity of HAPA in practical conformal array synthesis.

Beam Pattern Synthesis Based on Hybrid Optimization Algorithm

As conventional methods for beam pattern synthesis can not always obtain the desired optimum pattern for the arbitrary underwater acoustic sensor arrays,a hybrid numerical synthesis method based on adaptive principle and genetic algorithm was presented in this paper.First,based on the adaptive theory,a given array was supposed as an adaptive array and its sidelobes were reduced by assigning a number of interference signals in the sidelobe region.An initial beam pattern was obtained after several iterations and adjustments of the interference intensity,and based on its parameters,a desired pattern was created.Then,an objective function based on the difference between the designed and desired patterns can be constructed.The pattern can be optimized by using the genetic algorithm to minimize the objective function.A design example for a double-circular array demonstrates the effectiveness of this method.Compared with the approaches existing before,the proposed method can reduce the sidelobe effectively and achieve less synthesis magnitude error in the mainlobe.The method can search for optimum attainable pattern for the specific elements if the desired pattern can not be found.

Formulation of Optimization Problems with Radiation Field Phases as Design Variables for Pattern Synthesis of Linear Antenna Arrays

Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these problems.This paper does not propose a new EA,but does construct a new form of optimization problems.The new optimization formulation has two differences from the common ones.One is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the designed.This difference is beneficial to decrease complexity in some sense.The second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation parameters.This difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are validated.The results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.

Phase-only pattern synthesis based on gradient-descent optimization

By applying phase-only technique in array antenna pattern synthesis, antenna arrays can form desired patterns with the use of phase shifters only. A novel phase-only pattern synthesis algorithm is proposed for the passive phased array seeker. This algorithm synthesizes the main beam of the antenna pattern through least-squares approximation, thus minimizing the errors between the actual and the desired main beams. The synthesis problem can be solved by applying gradient-descent optimization. The item for suppressing side lobes is added to the above synthesis problem. To obtain a side lobe level as low as possible, the algorithm assigns different weights to different directions in the side lobe region. The algorithm is run repeatedly and the weights are adjusted adaptively according to the normalized power in the side lobe directions. Detailed examples are presented to demonstrate the accuracy and effectiveness of the proposed approach.

Pattern synthesis of antennas based on a modified particle swarm optimization algorithm

In order to overcome the drawbacks of standard particle swarm optimization(PSO)algorithm,such as prematurity and easily trapping in local optimum,a modified PSO algorithm is proposed,in which special techniques,as global best perturbation and inertia weight jump threshold are adopted.The convergence speed and accuracy of the algo-rithm are improved.The test by some benchmark problems shows that the proposed algorithm achieves relatively higher performance.Thereafter,the applications of the modified PSO in the radiation pattern synthesis of antenna arrays are presented.

Space-borne antenna adaptive anti-jamming method based on gradient-genetic algorithm

A novel space-borne antenna adaptive anti-jamming method based on the genetic algorithm （GA）, which is combined with gradient-like reproduction operators is presented, to search for the best weight for pattern synthesis in radio frequency （RF）. Combined, the GA＇s the capability of the whole searching is, but not limited by selection of the initial parameter, with the gradient algorithm＇s advantage of fast searching. The proposed method requires a smaller sized initial population and lower computational complexity. Therefore, it is flexible to implement this method in the real-time systems. By using the proposed algorithm, the designer can efficiently control both main-lobe shaping and side-lobe level. Simulation results based on the spot survey data show that the algorithm proposed is efficient and feasible.

Optimal Design of Wireless Power Transmission Systems Using Antenna Arrays

Three design methods for wireless power transmission(WPT)systems using antenna arrays have been investigated.The three methods,corresponding to three common application scenarios of WPT systems,are based on the method of maximum power transmission efficiency(MMPTE)between two antenna arrays.They are unconstrained MMPTE,weighted MMPTE,and constrained MMPTE.To demonstrate the optimal design process with the three methods,a WPT system operating at 2.45 GHz is designed,simulated,and fabricated,in which the transmitting(Tx)array,consisting of 36 microstrip patch elements,is configured as a square and the receiving(Rx)array,consisting of 5 patch elements,is configured as an L shape.The power transmission efficiency(PTE)is then maximized for the three application scenarios,which yields the maximum possible PTEs and the optimized distributions of excitations for both Tx and Rx arrays.The feeding networks are then built based on the optimized distributions of excitations.Simulations and experiments reveal that the unconstrained MMPTE,which corresponds to the application scenario where no radiation pattern shaping is involved,yields the highest PTE.The next highest PTE belongs to the weighted MMPTE,where the power levels at all the receiving elements are imposed to be equal.The constrained MMPTE has the lowest PTE,corresponding to the scenario in which the radiated power pattern is assumed to be flat along with the Rx array.

Texture Pattern Generation Using Clonal Mosaic

In this paper, an effective system for synthesizing animal skin patterns on arbitrary polygonal surfaces is developed. To accomplish the task, a system inspired by the Clonal Mosaic （CM） model is proposed. The CM model simulates cells＇ reactions on arbitrary surface. By controlling the division, mutation and repulsion of cells, a regulated spatial arrangement of cells is formed. This arrangement of cells shows appealing result, which is comparable with those natural patterns observed from animal skin. However, a typical CM simulation process incurs high computational cost, where the distances among ceils across a polygonal surface are measured and the movements of cells are constrained on the surface. In this framework, an approach is proposed to transform each of the original 3D geometrical planes of the surface into its Canonical Reference Plane Structure. This structure helps to simplify a 3D computational problem into a more manageable 2D problem. Furthermore, the concept of Local Relaxation is developed to optimally enhance the relaxation process for a typical CM simulation. The performances of the proposed solution methods have been verified with extensive experimental results.