Hemant Patidar

Comparative study of evolutionary algorithms for design of linear array of mutually coupled parallel dipole antennas including wide null placement

The authors in this paper present comparative study of three evolutionary algorithms such as quantum particle swarm optimization, backtracking search algorithm and cuckoo search algorithm for design of linear array of dipole antennas that will generate far-field radiation pattern in the horizontal plane with fixed value of peak side lobe level, voltage standing wave ratio and wide null depth. The performances of the above algorithms are judged here in terms of different antenna parameters like peak side lobe level, wide null depth and VSWR as well as statistical parameters such as best fitness value, mean and standard deviation. Mutual coupling between parallel dipole antennas has also been considered. Assuming the current distribution on each thin dipole to be sinusoidal, self and mutual impedances are calculated by induced EMF method. One example is presented to show the effectiveness of the proposed approach.

FAILURE CORRECTION OF LINEAR ANTENNA ARRAY BY CHANGING LENGTH AND SPACING OF FAILED ELEMENTS

This paper presents a new approach for linear antenna array failure correction using geometry optimization of the failed antenna elements. It is done by changing the length and spacing of failed elements while the spacing and length of remaining elements are fixed. The flower pollination algorithm based on the characteristic of flowering plants has been used to correct the radiation pattern of linear antenna array with desired side lobe level and minimum return loss. Simulations are performed using Matlab. Two examples are given to show the effectiveness of the proposed method. In addition, the obtained results from simulation on Matlab are also validated by the results obtained from FEKO analysis.

QPSO for Synthesis of Scanned Linear Array Antenna for Fixed Side Lobe Level and First Null Beam Width Including Wide Null Placement

In this research paper, quantum particle swarm optimization (QPSO) algorithm, an algorithm founded on the basic theory of particle cluster and properties of quantum mechanics, has been introduced for design of uniformly spaced scanned linear array antennas with definite value of sidelobe level (SLL), first null beam width (FNBW), and broad null depth. An effort is made such that these parameters are made equal to their related specific values. This is usually done by changing excitation current amplitude of the elements. The expression of array factor is derived by using the property of linear array antennas. One example has been presented with 35 isotropic antennas. Generated Pattern is scanned to an angle of 30°. The obtained results have shown that this technique is able to find required value of SLL, FNBW, and wide null depth. Although, the proposed method is developed and applied to a linear array of isotropic antennas; however, the principle can easily be applied to other types of arrays.