A Novel Hybrid IWO/WDO Algorithm for Interference Minimization of Uniformly Excited Linear Sparse Array by Position-Only Control

Abstract

This letter introduces a novel, fast, efficient and global optimization algorithm called hybrid invasive weed optimization and wind driven optimization (IWO/WDO). The proposed algorithm is implemented to synthesize the uniformly excited ( ) linear sparse array pattern having a minimum side lobe level (SLL), and null control with constraint on beam width to minimize the interference effect by optimizing the element position-only. Three examples of (N=10, 28, and 32) element linear array synthesis are considered to illustrate the efficacy of the proposed algorithm. The results are compared with those obtained by IWO, WDO, PSO, CLPSO, DE and BBO algorithms. Simulation studies demonstrate that this algorithm achieves minimum SLL of -23.5 dB, -13.22 dB, and -19.7 dB as compared to -17.35 dB, -10.5 dB and -15.70 dB obtained by the IWO algorithm for 10, 28, and 32 elements array respectively. Also, it yields a null depth level (NDL) larger than -84.5 dB in all cases. The learning characteristics show a faster convergence at around 100 iterations. The simulation results demonstrate the improved performance of hybrid IWO/WDO algorithm compared to other six algorithms in terms of null control, minimum SLL, beam width control and the rate of convergence. Index Terms-Array pattern synthesis, linear array, invasive weed optimization (IWO), wind driven optimization (WDO), electromagnetic interference, hybrid IWO/WDO.

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

“…The fitness function [4] for above criteria is given as, in which K is the number of required null directions, C dB is desired NDL in dB, and  k is the direction of the kth null. In Eq.…”

“…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.…”

“…Hence, it was found that the performance of an IWO algorithm to solve a given problem depends heavily on its initial parameters and these parameters should be carefully selected according to the problem to be solved. To overcome these two problems, a novel hybrid IWO/WDO algorithm is proposed and implemented in linear sparse array pattern synthesis [4]. In hybrid algorithm, WDO technique is utilized to effectively initialize the position of seeds and subsequent processing is done by IWO method.…”