Adaptive nulling in time-modulated antenna arrays

This paper introduces an application of the dandelion optimization (DO) algorithm in antenna arrays. This is the first time that the DO algorithm has been used for optimizing antenna arrays. For antenna array optimization, sidelobe level (SLL) and deep nulls are key technical indicators. A lower SLL can improve the signal-to-noise ratio and reduce the impact of clutter signals outside the main beam. Deep nulls need to be aligned with the direction of interference to eliminate the influence of interference sources. The combination of the two can effectively improve the anti-interference ability of the entire system. Therefore, antenna arrays with ultra-low sidelobes and ultra-deep nulls are currently hot in the field of antenna array design and are also some of the key technologies needed to achieve modern high-performance radar systems. As a new type of evolutionary algorithm inspired by nature, the DO algorithm is inspired by the wind propagation behavior of dandelions in nature. This algorithm iteratively updates the population from three stages of ascent, descent, and landing, ultimately finding the optimal position. It has good optimization ability in solving complex problems such as those involving nonlinearity, discreteness, and non-convexity, and the antenna array pattern synthesis optimization problem belongs to multivariate nonlinear problems. Therefore, the DO algorithm can be effectively applied in the field of antenna array optimization. In this work, we use the following method to obtain an optimized pattern of a linear array with the lowest sidelobe level (SLL), null placement in particular directions, and a lower notch in particular directions: by controlling the antenna array’s element spacing and leaving the phase unchanged to optimize the current amplitudes and by controlling the excitation current and phase fixation of the antenna array and changing the element spacing. In the first and second examples, different algorithms are used to reduce the SLL of the antenna. In the first example, the DO algorithm reduces the SLL to −33.37 dB, which is 2.67 dB, 2.67 dB, 3.77 dB, 2.74 dB, and 2.52 dB lower than five other algorithms. In the second example, the SLL optimized by the DO algorithm is −42.56 dB, which is 5.04 dB and 1.48 dB lower than two other algorithms. In both examples, the DO algorithm reduces the SLL lower than other algorithms when the main lobe of the antenna is not significantly widened. Examples 3, 4, and 5 use the DO algorithm to optimize the amplitude of the current, generating deep nulls and deep notches in specific directions. In Example 3, the DO algorithm obtains a depth of nulls equal to −187.6 dB, which is 66.7 dB and 44.3 dB lower than that of the flower pollination algorithm (FPA) and the chaotic colony predation algorithm (CCPA), respectively. In Example 4, the deep null obtained by the DO algorithm is as low as −98.69 dB, which is 6.67 dB lower than the deep null obtained by the grey wolf optimization (GWO) algorithm. In Example 5, the deep notch obtained by the DO algorithm is as low as −63.1 dB, which is 6.4 dB and 1.9 dB lower than the spider monkey optimization (SMO) algorithm and the grasshopper optimization algorithm (GOA), respectively. The data prove that the DO algorithm produces deeper nulls and notches than other algorithms. The last two examples involve reducing sidelobe levels and generating deep nulls by optimizing the spacing between elements. In Example 5, the SLL obtained using the DO algorithm is −22.8766 dB, which is 0.1998 dB lower than the lowest SLL of −22.6768 dB among other algorithms. In Example 6, the SLL obtained using the DO algorithm is −20.1012 dB, and the null depth is −125.1 dB, which is 1.592 dB lower than the SLL obtained by the cat swarm optimization (CSO) algorithm and 19.1 dB lower than the deep null obtained by the GWO algorithm, respectively. In summary, the results of six simulation experiments indicate that the DO algorithm has better optimization ability in linear array optimization than other evolutionary algorithms.

This article aims to propose an alternate method of generating power-efficient sum-difference monopulse pattern using time-modulated antenna arrays. Time modulated antenna arrays have an added advantage of harmonics generation which can be controlled for simultaneous multipattern communication systems with suitable beamforming switching networks. In this work, a phase centered-based movement of predefined subarray cluster is applied in the proposed Beamforming Network (BFN) to produce simultaneous sum and difference patterns beneficial for monopulse radars. To enhance the efficiency of the switching network, a Single-Pole-Double-Throw (SPDT) based sequence is proposed. A 2N element symmetrically arranged linear antenna array is considered, and a suitable subarray cluster-controlled SPDT time scheme is implemented. The detailed comparison has been drawn between the phase-centered motion-based simple ON-OFF time scheme and the proposed enhanced SPDT-based harmonic BFN to show a superior monopulse performance.

In time-modulated antenna arrays (TMAAs), as a result of periodical switch-on and switch- ofi of the antenna elements, including operating frequency (termed as center frequency) signal, sideband signals are appeared at either sides of the center frequency in integer multiples of the modulation frequency. In this paper, it is shown that without using phase shifters, just by suitably controlling the on-time instants (OTIs) and on-time durations (OTDs) of a time-modulated linear antenna array (TMLAA) elements, simultaneously, along with a pencil beam pattern at the operating frequency, a shaped beam pattern can be obtained at both the flrst positive and negative harmonics of the time- modulation frequency. The important advantage of such a technique is that realization of multi-beam pattern in conventional antenna array (CAA) system generally requires complex feed network, whereas by using simple radio frequency (RF) switching circuit in the feed network of TMLAA, by virtue of the properties of harmonic radiations, synthesis of a shaped pattern at either (positive or negative) harmonic results in generating the same pattern in its opposite harmonic, and the synthesized patterns at difierent harmonics can be simultaneously used as independent communication channels. By employing a difierential evolution (DE) based optimization method, numerical results for a 16-element TMLAA with uniform excitation show that in conjunction with a pencil beam pattern at the center frequency, a ∞at-top or a cosec square pattern at flrst positive and negative sidebands of side-lobe levels (SLL) i20dB can be synthesized by suppressing the higher sideband level (SBL) to below i10dB.

This paper proposes a trapezoidal pulse-based ON-OFF switching approach for the optimum beamforming performance in a time-modulated linear antenna array (TMLAA). The Fourier series property is used to adjust the transient behaviour trapezoidal switching function (τn1) and constant slope (τn2) of the trapezoidal pulse to obtain the highest steering main beam of the fundamental and harmonic components of the radiation pattern. Also, the sidelobe level (SLL) and sideband level (SBL) are simultaneously lowered. Despite the fact that harmonic beams are typically thought of as an interfering radiated pattern in time-modulated antenna arrays, the shifted harmonic frequency can also be useful in a variety of contexts. The beam steering of the harmonic is made possible by the optimal adjustment of the switch time instant τn1 and τn2 of the trapezoidal pulse signal without any optimization of the excitation amplitude weights. The optimal switching ON and OFF duration is evaluated by utilizing an evolutionary algorithm called Cultural Algorithm (CA). The antenna radiation characteristics are changed by using a series of Radio Frequency (RF) switches to modulate the static excitations using a trapezoidal pulse sequence to alter the time-modulation. Toward this approach, unique cost functions are designed and simulated for the simultaneous reduction of SLL, SBL and harmonic beam steering in TMLAA. The proposed cost function-based CA algorithm is able to get beam steering as arbitrary beam steering, multi-beam steering and beam steering in a user-defined direction.

A novel optimization method for multiple beamforming with null steering is proposed. Firstly, an invasive weed optimization method is improved in order to optimize the search depth. In the process of the seed diffusion, the crossover operation of genetic algorithm is introduced to modify the seed individuals, which can meliorate the searching ability and convergence speed of the algorithm. Then, the harmonic beamforming technology based on time modulated antenna array is presented, and multiple objectives about peak power and null steering are built. Finally, the improved invasive weed optimization algorithm is used in null forming based on pattern synthesis of antenna array, and the element excitation amplitude of time modulated antenna array is set to the excitation value obtained by the improved optimization algorithm. The simulation results show that the improved invasive weed optimization algorithm is superior to the conventional algorithm in performance. The simulation results show that forming null in the specified direction can be achieved while generating multiple beams.

Reduction of Sidelobes of the power pattern of Antenna Array with time modulation technique called time modulated antenna array (TMAA). Amplitude and spacing is used as optimizing variables for the reduction of side lobe level (SLL) of TMLAAs. The switching time sequence of each element of array is predefined. The method is demonstrated in the course of 12, 16, 20 element TMLAAs. Different outcomes are offered to explain the reward of this method deeming optimal SLL reduction, as compared to non-optimized TMLAAs.

This research presents the design of time-modulated antenna arrays with UWB performance. The antenna arrays consider a linear topology with eight UWB disk-notch patch antennas. The technological problem is to find out the optimum antenna positions and/or time sequences to reduce the side lobes and the sidebands in all of the UWB frequency ranges. The design process is formulated as a bacterial foraging optimization. The results show that the uniform array generates a better SLL performance whereas the non-uniform array obtains a wider bandwidth. The uniform array obtains an SLL < -20 dB from 3.37 GHz to 4.8 GHz and the non-uniform array generates an SLL < -7 dB from 2.97 GHz to 5.26 GHz. The sideband levels are very similar for both cases with a value of around -17 dB.

An improved procedure to lessen side lobe levels (SLLs) and side band levels (SBLs) in time modulated linear antenna arrays (TMLAAs) by using the optimization process. In that optimization process we give the discrete values of static excitation amplitudes and phase of continuous values of on-time duration of the elements of antenna array. We used the particle swarm optimization (PSO) technique to reduce the maximum of SLLs and SBLs to a pre defined desired value of antenna element. This has been optimized in a way that the discrete values of input excitation amplitude are obtained by PSO algorithm. The simulation result of time-modulated linear antenna array (TMLAA) is presented by reducing SLL and SBLmax to below −40 dB and to −35 dB respectively by taking 30 elements.

Adaptive blind nulling using an antenna array is an effective method to mitigate interferences in global navigation satellite system (GNSS) receivers. Compared with beam-forming techniques, it has the advantage that measuring the orientation of the antenna is not needed, thus saves the cost of equipping an inertial measurement unit (IMU). However, since the satellite direction information is absent, pre-existing methods of mitigating the measurement biases induced by the adaptive array algorithms are no more applicable, which makes the accuracy requirements not met in high-precision applications. To this end, a blind nulling algorithm using spatial-temporal adaptive processing (STAP) without measurement biases is proposed. This algorithm utilizes the symmetry of the array manifold, and sacrifices nearly half of both the spatial and temporal degrees of freedom (DOF) to gain the bias-free feature in all directions. Effectiveness of this method is verified by theoretical analysis and simulation results.

An adaptive nulling system has been designed for a space-based radar incorporating a phased array fed Cassegrain antenna. Auxiliaries are formed by reusing elements from the main antenna array feed together with an external horn antenna. Antenna patterns for the main antenna and for the auxiliaries are calculated using a physical optics-based reflector code. Nulling performance is calculated using an Applebaum array model, and results using array element reuse and external horn auxiliaries are compared. Using both types of auxiliaries together is considered. It is found that the array element reuse auxiliaries provide sufficient sidelobe coverage in most cases. Performance is found to degrade when jammers are at far-out sidelobe locations, and when multiple jammers are present. Optimal performance may be obtained with a combination of reuse and external horn auxiliaries. >

In this research paper, quantum particle swarm optimization (QPSO) algorithm, an algorithm founded on the basic theory of particle cluster and properties of quantum mechanics, has been introduced for design of uniformly spaced scanned linear array antennas with definite value of sidelobe level (SLL), first null beam width (FNBW), and broad null depth. An effort is made such that these parameters are made equal to their related specific values. This is usually done by changing excitation current amplitude of the elements. The expression of array factor is derived by using the property of linear array antennas. One example has been presented with 35 isotropic antennas. Generated Pattern is scanned to an angle of 30°. The obtained results have shown that this technique is able to find required value of SLL, FNBW, and wide null depth. Although, the proposed method is developed and applied to a linear array of isotropic antennas; however, the principle can easily be applied to other types of arrays.

In this article, a metasurface (MS) is placed as superstrate to counteract the effect of mutual coupling in linear antenna array in X-band. The metasurface is single layered and consist of single split ring resonator (SRR) and two I-shaped structures. The proposed metasurface can curb the interactions between adjacent antenna elements by collimating the electric field and reduce horizontal magnetic field interactions due to its negative refractive index and mu-near-zero property. The functioning of metasurface is tested by placing it above a 1×3 patch antenna. The experimental measurement shows an isolation below -25 dB in the 5.12% operational bandwidth with maximum isolation of -38.2 dB for an edge-to-edge distance of only 0.16λo. The active radiation pattern indicates an improved cross-polarization levels to below -30 dB, in both the orthogonal planes. The performance of MS is further tested for a 1×7 linear array where a 9.2 dB reduction in coupling value is observed. On placing the MS on the array there is no change in the operational bandwidth indicating that no modifications is needed in the antenna array geometry making it a preferable and easily transferrable solution to already existing antenna array.

The pattern synthesis technique of antenna arrays has a wide range of applications in radar and communication systems, which is an important research direction in the field of smart antennas. In order to improve the optimization performance of pattern synthesis of linear antenna arrays, an optimization method based on the Modified RIME Optimization Algorithm (MRIME) is proposed. RIME is a new heuristic algorithm inspired by the condensation process of frost ice in nature, which has a unique update mechanism with strong convergence as well as randomization. In the present work, MRIME is used for optimal pattern synthesis of a linear antenna array (LAA). One part of the present study is to optimize the side lobe level by optimizing the antenna current amplitude while maintaining a uniform spacing; the other part is to optimize the antenna position while assuming a uniform excitation in the synthesis of a sparse LAA, where constraints are imposed on the spacing of the array elements and aperture length, and suppression of the side lobe level with the position of the zeros in the specified direction is also achieved. In this article, simulation experiments for uniform linear arrays as well as sparse linear arrays are presented in detail, and the results show that the MRIME optimization algorithm outperforms most of the existing evolutionary classes of optimization algorithms in optimizing the side lobe level. This illustrates the potential of utilizing the MRIME optimization algorithm for antenna arrays and various other electromagnetism-related challenges.

In this paper, the pattern nulling of a linear array for interference cancellation is derived by phase-only perturbations using memetic algorithm. It is proposed to improve the search ability of genetic algorithms. Memetic algorithm is a kind of an improved type of the traditional genetic algorithm. By using local search procedure, it can avoid the shortcoming of the traditional genetic algorithm, whose termination criteria are set up by using the trial and error method. The memetic algorithm is applied to find the pattern nulling of the proposed adaptive antenna. This design for radiation pattern nulling of an adaptive antenna can suppress interference by placing nulls at the directions of the interfering sources, i.e., to increase the Signal to Interference Ratio (SIR). This proposed method is that an innovative adaptive antenna optimization technique is also able to solve the multipath problem which exists in practical wireless communication systems. The example is provided to justify the proposed phase-only perturbations approach based on memetic algorithms. Computer simulation results are given to demonstrate the effectiveness of the proposed method.

The design of an effective antenna array is a major challenge encountered in most communication systems. A much-needed requirement is obtaining a directional and high-gain radiation pattern. This study deals with the design of a linear antenna array that radiates with reduced peak-side lobe levels (PSLL), decreases side-lobe average power with and without the first null beamwidth (FNBW) constraint, places deep nulls in the desired direction, and minimizes the close-in-side lobe levels (CSLL). The nature-inspired metaheuristic algorithm multi-verse optimization (MVO) is explored with other state-of-the-art algorithms to optimize the parameters of the antenna array. MVO is a global search method that is less prone to being stuck in the local optimal solution, providing a better alternative for beam-pattern synthesis. Eleven design examples have been demonstrated, which optimizes the amplitude and position of antenna array elements. The simulation results illustrate that MVO outperforms other algorithms in all the design examples and greatly enhances the radiation characteristics, thus promoting industrial innovation in antenna array design. In addition, the MVO algorithm’s performance was validated using the Wilcoxon non-parametric test.