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Abstract-Phased array antenna produces highly directive beam along with high side lobe level (SLL) which causes interference in other directions and level of side lobe changes with beam steering. To mitigate such constraint, in this paper, particle swarm optimization (PSO) is applied along with Tchebyscheff distribution (TD) to the linear phased array antenna. Simulating radiation patterns of linear phased array antenna at different scanning angles, using Tchebyscheff distribution, particle swarm optimization and combined Tchebyscheff distribution with particle swarm optimization (TD-PSO) are compared. Maximum side lobe level is reduced by 11 dB using TD-PSO method than Tchebyscheff distribution method. Better SLL suppression was obtained using TD-PSO but with slight increase of the main null to null beamwidth, compared to TD array. The research work presented here may be useful for radio navigation and satellite communication where phased array antennas are widely used.Keyword -Tchebyscheff distribution, phased array, side lobe level, particle swarm optimization I. INTRODUCTION In phased array antenna resulting radiation pattern is steered at any particular direction by changing electronically the relative phase of feed current between the antenna elements in the array [1][2][3]. Phased array antenna is widely used for RADAR, satellite communication and other vehicular applications. The main drawback of phased array is higher side lobe level which changes with beam tilting and causes interference. Various methods of designing phased array with lower side lobe levels can be found in literature [4][5][6][7][8][9]. Statistically tapered amplitude arrays based on empirical or analytical formula found application in array synthesis methods to reduce side lobe level with maintaining the desired gain [4][5][6][7]. Tchebyscheff array is very well known optimal array pattern synthesizing method for the linear array where individual element fed with the current value equal to the Tchebyscheff coefficient and the resulting array pattern produces fixed lowest side lobe level for a particular beamwidth [7]. A method for finding optimum weights for minimizing side lobe level of arbitrary linear array is described in [6].There are various proposed strategies and methods where by tapering the feeding current amplitude of elements, side lobe levels are reduced [4-6, 8, 9]. One of the methods for side lobe suppression and beam control is to use optimization techniques. For antenna array applications, popular optimization techniques are genetic algorithm, ant colony optimization, simulated annealing, particle swarm optimization [10][11][12][13][14][15][16]. Differential equation with back tracking search algorithm is applied to reduce side lobe level of concentric circular array [10]. Null placing and minimizing the side lobe level during scanning of a linear array antenna using Pareto optimal synthesis procedure is described in [11]. Thinning is another technique of side lobe level reduction of linear array [16]. The problem of ...

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The flat-top radiation pattern is necessary to form an appropriate beam in a sectored cellular network and to pro vide users with best quality services. The flat-top pattern offers sufficient power and allows to minimize spillover of signal to adjacent sectors. The flat-top sector beam pattern is relied upon In sectored cellular networks, in multiple-input multiple-output (MIMO) systems and ensures a nearly constant gain in the desired cellular sector. This paper presents a comparison of such optimization techniques as real-coded genetic algorithm (RGA) and particle swarm optimization (PSO), used in cellular networks in order to achieve optimum flat-top sector patterns. The individual parameters of flat-top sector beams, such as cellular coverage, ripples in the flat-top beam, spillover of radiation to the adjacent sectors and side lobe level (SLL) are investigated through optimization performed for 40◦ and 60◦ sectors. These parameters are used to compare the performance of the optimized RGA and PSO algorithms. Overall, PSO outperforms the RGA algorithm.

A new approach has been considered to detect threat item among multiple concealed objects by analyzing the delayed time-response of the objects, that would be illuminated by an ultra wide band radar. It was observed that the reflected wave, from the target, produced a delayed damped sinusoidal oscillation, that contained aspect independent complex natural resonances, which was unique for any individual object. A generalized pencil of function is applied for signal processing to extract poles from the scattered late time response of different objects. Application of hamming window function improves discrimination and detection of poles of multiple objects. Determination of the presence of a particular pole or concealed threat is observed upon using this proposed methodology.