Chaos-Enhanced Whale Optimization Algorithm for Smart Beam Steering in Phased Array Antennas

Formulation of the problem. Many electronic applications (for example, satellite communications) impose significant restrictions on the weight and dimensions of the antenna devices used. In addition, the antennas used should have the lowest possible cost and simplicity of design. To solve these problems, it is proposed to use a method for reducing the number of antenna elements in phased antenna arrays based on the method of point sources. Purpose. The purpose of this work is to develop a method for reducing the number of antenna elements in phased antenna arrays while maintaining the parameters of their radiation patterns. Results. As a solution, it is proposed to place the antenna elements above the metal sheet at a distance 1.5–2 times smaller than the size of the antenna array itself, which will significantly reduce the number of elements of the latter without deteriorating its radiation pattern during wide-angle two-coordinate scanning of space with the main lobe. Practical significance. Obtained results can be used to create phased antenna arrays with a reduced number of elements, which will reduce the size, weight and cost of the device.

Three-dimensional path planning for autonomous underwater vehicles based on a whale optimization algorithm

This research investigates the optimal design of finite impulse response (FIR) low-pass digital filters using metaheuristic optimization. A key challenge in FIR design with the Kaiser window lies in reducing sidelobe levels while maintaining transition sharpness and filter stability. To address this, the Kaiser window parameter β was adaptively optimized using grey wolf optimization (GWO), whale optimization algorithm (WOA), and particle swarm optimization (PSO). Thirty filters were tested with β values ranging approximately from 1 to 5 to evaluate trade-offs among the methods. The results show that GWO achieved the strongest sidelobe suppression, reaching –58.65 dB at β = 5.67, although with transition bandwidth widening up to 0.148π rad/sample. PSO provided the sharpest selectivity, producing the narrowest transition bandwidth of 0.058π rad/sample at β = 1.2284, while still improving sidelobe attenuation to –55.27 dB at β = 5.2565. WOA offered balanced performance, with sidelobe attenuation improving from –28.38 dB at β = 1.6470 to –55.07 dB at β = 5.2312, and transition bandwidths up to 0.138π rad/sample. Across all methods, main lobe widths remained stable within 0.172–0.181π, indicating reliable filter performance. Overall, the study demonstrates that metaheuristic-based optimization enables adaptive β tuning, offering distinct strengths: GWO in sidelobe suppression, PSO in transition sharpness, and WOA in coefficient stability. These results provide practical insights for selecting suitable optimization strategies in communication, audio processing, and precision measurement applications where computational efficiency is critical

Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. Yet, the slow convergence speed issue in Whale Optimization Algorithm and Grey Wolf Optimizer could demote the performance of feature selection and classification accuracy. Therefore, to overcome this issue, a modified WOA (mWOA) and modified GWO (mGWO) for wrapper-based feature selection were proposed in this study. The proposed mWOA and mGWO were given a new inversed control parameter which was expected to enable more search area for the search agents in the early phase of the algorithms and resulted in a faster convergence speed. The objective of this comparative study is to investigate and compare the effectiveness of the inversed control parameter in the proposed methods against the original algorithms in terms of the number of selected features and the classification accuracy. The proposed methods were implemented in MATLAB where 12 datasets with different dimensionality from the UCI repository were used. kNN was chosen as the classifier to evaluate the classification accuracy of the selected features. Based on the experimental results, mGWO did not show significant improvements in feature reduction and maintained similar accuracy as the original GWO. On the contrary, mWOA outperformed the original WOA in terms of the two criteria mentioned even on high-dimensional datasets. Evaluating the execution time of the proposed methods, utilizing different classifiers, and hybridizing proposed methods with other metaheuristic algorithms to solve feature selection problems would be future works worth exploring.

An efficient double adaptive random spare reinforced whale optimization algorithm

In a practical space-borne active phased antenna array (APAA), main beam scanning angle (MBSA)-dependent low side lobe level (SLL) and taper loss are the ultimate and most critical performances. At some MBSA, extremely SLL in some local space is needed. The harsh limitation on APAA taper loss further complicates the problem seriously. In this paper, the main beam scanning space (MBSS) was divided into several subspaces. Instead of applying a single set of weights regardless of the MBSA, a separate set of weights is implemented independently in each subspace. This transforms the nearly unsolvable problem into multiple solvable problems. An array-decomposition approach is proposed to further reduce the number of synthesis parameters for each subspace. The entire array is simplified as an assembly of multiple sub-arrays. Each and every sub-array shares the same set of weights. The number of synthesis parameters is therefore reduced to the order of the subarray that the synthesis is much easier to solve without sacrificing too much synthesis performance. The proposed approach has been applied to solve concerned practical problem successfully.

Towards phased array antenna operating in Ku-band for satellite communications

To address the shortcomings of the whale optimization algorithm (WOA) in terms of insufficient global search ability and slow convergence speed, a differential evolution chaotic whale optimization algorithm (DECWOA) is proposed in this paper. Firstly, the initial population is generated by introducing the Sine chaos theory at the beginning of the algorithm to increase the population diversity. Secondly, new adaptive inertia weights are introduced into the individual whale position update formula to lay the foundation for the global search and improve the optimization performance of the algorithm. Finally, the differential variance algorithm is fused to improve the global search speed and accuracy of the whale optimization algorithm. The impact of various improvement strategies on the performance of the algorithm is analyzed using different kinds of test functions that are randomly selected. The particle swarm optimization algorithm (PSO), butterfly optimization algorithm (BOA), WOA, chaotic feedback adaptive whale optimization algorithm (CFAWOA), and DECWOA algorithm are compared for the optimal search performance. Experimental simulations are performed using MATLAB software, and the results show that the improved whale optimization algorithm has a better global optimization-seeking capability. The improved whale optimization algorithm is applied to the distribution network fault location of IEEE-33 nodes, and the effectiveness and accuracy of the distribution network fault zone location based on the multistrategy improved whale optimization algorithm is verified.

Known designs of Ka-band phased array antennas incorporate an optical feed or a radial waveguide feed. Significant disadvantage of an optical feed is microwave energy overflow through antenna aperture, which decreases aperture efficiency and increases a side lobe level. Optical feed requires additional space for feeding antenna location and increases overall antenna dimensions. The design of a phased array with a radial waveguide feed forces placement of the phase shifter control circuits outside the dimensions of the array and increases overall antenna dimensions. The purpose of the article is to design a Ka-band phased antenna array (PAA) with a waveguide feed with smallest overall dimensions and various aperture shapes. The manufactured prototype of PAA with a grid pitch of 6x6 mm and size of 300x40 mm showed acceptable results of the side lobe level, scanning sector ±45° and gain factor. Proposed Ka-band phased array antenna design allows one to construct the extremely compact radar of various types including airborne radars.

In this paper, the whale optimization algorithm (WOA) is introduced and applied to the synthesis of uniformly excited broadside linear unequally spaced arrays for sidelobe suppression with different aperture constraints. Two design examples of pattern synthesis with fixed and unfixed array aperture respectively have been chosen to illustrate the effectiveness and superiority of WOA when compared to synthesis techniques described in literature. The results show that the WOA achieves lowest maximum sidelobe level relative to other state-of-the-art algorithms in two design cases. The WOA results and convergence tests demonstrate superior applicability of this novel optimization algorithm.

Phased-array echosonographic systems, currently in use in medical diagnosis, employ pulses that are a few wavelengths long at the center frequency. Design of such systems requires that arrays be composed of as few elements as are consistent with acceptable resolution and low side lobes. This paper outlines the development of a model for the field of an idealized phased array. The model is an extension of elementary array theory which includes pulse parameters and beam steering. It is specialized for the generation of simple and useful directivity patterns that are applicable at point focal regions and in the farfield. The directivity-pattern function provides the basis for a method of designing linear arrays by nonuniform element spacing. Arrays designed by this method offer advantages over uniform linear arrays because of the smaller number of elements required for given azimuthal resolution and side-lobe level, and because of reduced element interaction.

This paper describes optimum antenna array structure for beamforming in smart antenna technology. Different examples of array structures are analysed by the use of newly developed optimization technique called Whale Optimization Algorithm (WOA). The design objective here has been considered to get the most favourable radiation patterns with sidelobe level (SLL) reduction by optimizing amplitude excitations, inter element spacings and phases of each elements of an array. The numerical and simulation results are compared with that obtained by most popular optimization technique, Particle Swarm Optimization (PSO), Ant Lion Optimization (ALO) and Cat Swarm Optimization (CSO) by building codes using MATLAB. The results show that WOA can exhibit relatively better performance than other algorithms for the antenna array synthesis examples and beamforming applications.

Phased array radar systems are used for a wide variety of applications including the precise tracking of airborne craft for air traffic control and providing accurate atmospheric condition information important in weather forecasting. Reducing the cost and size of these radar systems will open new fields to the use of this technology. Using phase control implemented through liquid crystal materials we have created a compact, phased array radar system operating in the microwave range. We report on the construction and testing of a linear, eight element phased array antenna system operating at 32 GHz with element phase controlled by a dual frequency nematic liquid crystal media used as a tunable dielectric. The system was designed using CST Design Studios and Ansys HFSS software. Dual frequency liquid crystals are used to improve beam steering response times. We demonstrate 42 millisecond beam switching times, defined as the time to change the beam focus from one point to another point, controllable beam formation, and beam steering profiles consistent with analytical results and simulation models. The device footprint is a square with sides 9.5 cm long and a thickness less than 2.5 mm. Such a module is easily stackable to create an 8 × 8 phased array system. Our design incorporates a modular construction using PCB for the antennas and input circuitry and a liquid crystal phase control cell with microwave glass substrates. This design simplifies design, construction, and testing as compared to on-glass designs. The device shows an improvement in point-to-point scanning speeds by a factor of 3 as compared to similar liquid crystal based devices and provides continuously variable tuning. Such a device can be used in a system for reduced visibility, directional range finding suitable for automobile collision avoidance systems and rotary wing aircraft landing aids.

A 1×4 phased array antenna in package is presented at 60 GHz frequency band. End-fire elements are double side dipoles which provide a near omni-directional beam in H-plane. In E-plane, the phased array facilitates ±45° beam steering which improves the spatial coverage. The achieved end-fire gain is 9.1 dBi and both impedance and gain bandwidths cover all WiGig channels. The wide bandwidth, high coverage, and high gain of the phased array make it a desirable candidate for multi-gigabit wireless communication.

In phased array antennas, the high side-lobe levels due to the amplitude quantization often need to be reduced to meet some requirements. In order to develop the digitalization of antenna arrays in phased array radars, the amplitude quantization of aperture distribution in array antennas is studied. In this paper, the random technique and a novel appropriate random technique are presented and used to reduce the side-lobe levels, and the side-lobe levels in the amplitude quantized array pattern are calculated. The reduction of side-lobe level due to amplitude quantization are introduced using the improving method and confirmed with computations, where the related parameters are modified and numerous patterns are computed and compared. The quasi-optimum patterns are also obtained and given.