Design of Linear Phased Array for Interference Suppression Using Array Polynomial Method and Particle Swarm Optimization

Abstract

In this work, a linear phased array pattern design with null steering is achieved using the array polynomial technique and the Particle Swarm Optimization (PSO) algorithm. The null steering for interference suppression is obtained by controlling some of the roots on the Schelkunoff's unit circle while keeping the roots responsible for the main beam unchanged. The rest of the roots are controlled to minimize the Side Lobe Level (SLL) of the array pattern using the PSO algorithm. It has been demonstrated that this technique achieved more than 50% reduction in the parameters needed to be optimized compared with the conventional complex coefficients optimization techniques. Consequently, the fitness function is only responsible for the SLL as the prescribed controlled nulls and the mainbeam characteristics are solved analytically. The simulated results show the effectiveness of the proposed technique.

A non-revisiting artificial bee colony algorithm for phased array synthesis

“…Li et al proposed an improved PSO for electromagnetic applications with better results obtained compared with PSO and genetic algorithm (GA) [6]. Abu-Al-Nadi et al used array polynomial method and PSO to design linear phased arrays [9]. Simulation results show that this method could reduce more than half parameters of synthesis problems compared with conventional methods.…”

“…The degradation of sidelobe level of array pattern becomes a severe question if sidelobe region was set null. This problem would be worse if the number of setting nulls increased and close to the main beam [9,10]. Thus, the synthesis of phased arrays is highly difficult, and effective and reliable algorithms which can find promising solutions are urgently needed.…”

Array Pattern Synthesis Using Particle Swarm Optimization with Dynamic Inertia Weight

“…Compared with equally spaced arrays, unequally spaced arrays with optimally spaced sensors have advantages including their capability of achieving higher spatial resolutions or lower sidelobe, or we can use fewer sensors to meet similar pattern specifications by carefully designing the locations of array sensors [4][5][6]. By changing the amplitudes and phases of the array elements' complex weights without any physical changes in the array, the method becomes suitable for adaptive processing applications in which the array pattern is dynamically adapted to the environments [7][8][9][10].…”

Array Pattern Synthesis Using a Digital Position Shift Method

“…Aperiodic arrays with optimally spaced sensors have the advantage of achieving higher spatial resolutions or lower sidelobe. On the other hand, many techniques proposed in the literatures adjust the weight coefficients when deriving the solution to beam pattern synthesis [9]- [11]. Phase-only control widely used in phased arrays to provide beam scanning are less expensive to produce, and also, are more likely to minimize excitation errors and preserve coherence [10].…”