Linear array synthesis with minimum side lobe level and null control using wind driven optimization

Abstract

This paper presents synthesis of unequally spaced linear array antenna with minimum sidelobe suppression, desired beamwidth and null control using wind driven optimization (WDO) algorithm. The WDO technique is nature-inspired, population based iterative heuristic global optimization algorithm for multidimensional and multimodal problems. The array synthesis objective function is formulated and then optimizes elements location using WDO algorithm to achieve the goal of minimum sidelobe level (SLL) suppression, desired beamwidth and null placement in certain direction. The results of the WDO algorithm are validated by comparing with results obtained using PSO and other evolutionary algorithm as reported in literature for linear array (N=10). The synthesis results such as radiation pattern and convergence graph show that WDO algorithm performs far better than the common PSO, CLPSO and other evolutionary algorithms. Keywords-Antenna array, particle swarm optimization (PSO), wind driven optimization (WDO), linear array design, null control, sidelobe level suppression (SLL), comprehensive learning particle swarm optimization (CLPSO), evolutionary programming, interference.

Quantum Wind Driven Optimization for Unmanned Combat Air Vehicle Path Planning

“…In the second test instance, UCAV starts at (10,15) and finishes at (80,75). In this battlefield environment, there are eight threat centers.…”

“…Because the WDO algorithm has only a few parameters that need to be controlled, and it is very easy to implement, it has received much attention by various scholars since it was put forward. In recent years, the WDO algorithm has also been applied in many fields, for instance, in satellite image segmentation for multilevel thresholding [11], cloud resource allocation scheme [12], collision avoidance for dynamic environments [13], design of two-channel filter bank [14], synthesis of linear array antenna [15], and so on.…”

A novel hybrid IWO/WDO algorithm for nulling pattern synthesis of uniformly spaced linear and non-uniform circular array antenna

“…Various nulling methods such as the position-only [1][2][3][4], excitation amplitude-only [5][6][7], the phase-only and complex (both the phase and the amplitude) control [8] are used to suppress interference from unwanted signal while receiving the signal from the desired direction. If the direction of arrival of the interference signal is not exactly known or its locality is not fixed and may be slowly changing with respect to time, the broad nulls on the side lobe region of the array pattern can be required to increase signal-to-noise ratio and minimize interference.…”

“…If the direction of arrival of the interference signal is not exactly known or its locality is not fixed and may be slowly changing with respect to time, the broad nulls on the side lobe region of the array pattern can be required to increase signal-to-noise ratio and minimize interference. It has been widely studied in the last few decades utilizing various optimization methods [1][2][3][4][5][6][7][8]12,13]. Also, deterministic approach (as opposed to random-based meta-heuristics) to sparse array synthesis is actively studied [22].…”

“…Since 1970s various evolutionary algorithms have emerged, such as Particle Swarm Optimization (PSO) [1], Wind Driven Optimization [2][3][4], Bacterial Foraging Optimization (BFO) [5], BEES Algorithm [6], Plant Growth Simulation Algorithm (PGSA) [7], Modified Touring Ant Colony Optimization Algorithm (MTACO) [8], Invasive Weed Optimization [9][10][11], Backtracking Search Algorithm (BSA) [13], Genetic Algorithm (GA) [14], Cuckoo Search Algorithm (COA) [17,21] and many others. They have been successfully implemented for solving multi-dimensional and multimodal problems such as the ULA and NUCA array pattern synthesis to ensure maximal SLL suppression, null control subject to constraint on beam width.…”