Excitation Phases Of Elements Research Articles

A Diagnosing Method for Phased Antenna Array Element Excitation Amplitude and Phase Failures Using Random Binary Matrices

A diagnosing method for phased antenna array element failures is proposed. The element excitation amplitudes and phases are reconstructed by a compressed sensing based approach, in which the radiated electric fields of the array are sampled by a single fixed receiving antenna. The diagnosing can be processed when the phased array is still in service. Particularly, it can be specialized for detecting faults only. Element excitation phases are designed to follow Bernoulli distribution, which is difficult to be realized in conventional geometric sampling methods. It is capable to provide effective and simultaneous detection for different types of failures with phase control means that are simpler comparing with other methods in which excitation phase adjustment is required. Especially, a two-step detection strategy is proposed to effectively detect phase failures due to faultily short-circuited phase shifters. Numerical results illustrate the effective sensing range of a single receiving antenna. Full-wave simulations validate the diagnosing performance in the presence of mutual couplings between array elements.

Real-Time Phase-Only Nulling Based on Deep Neural Network With Robustness

Phase-only nulling under sidelobe and mainlobe constraints is a problem of interest in array synthesis which is a nonlinear problem without analytical solution. To reduce the computational cost of phase-only array nulling on-line, this paper proposes a real-time phase-only array synthesis method based on the deep neural network. The on-line real-time prediction of element excitation phase is achieved by the trained neural network which can be done off-line. The performance of the trained neural network is related with the number of data. Firstly, in order to obtain a large enough database for the deep neural network efficiently, a multi-task phase-only array synthesis model with nulling operation and sidelobe control is relaxed to a convex problem and solved by direct iterative rank refinement. Then, the deep neural network is devised to emulate the phase array nulling behavior. This is carried out by the design of the structure of the network, the dataset structure and the loss function of the network. To validate the performance of the deep neural network, the phase-only nulling of 10-element and 16-element linear array based on the deep neural network is realized and tested. Experimental results demonstrate that the proposed real-time array synthesis method not only satisfies the desired array pattern property but also shows robustness to the array imperfections. Robustness is validated with Monte Carlo test.

Multi‐beam pattern synthesis algorithm based on kernel principal component analysis and semi‐definite relaxation

In this study, a novel multi-beam pattern synthesis algorithm is proposed. The algorithm is divided into three steps. First, the pattern synthesis is performed for each beam without element excitation amplitude constraints, and form a element excitations amplitude matrix (EEAM). Second, the kernel principal component analysis (KPCA) technique is used to acquire a group of common element excitation amplitudes (CEEA). Finally, the semi-definite relaxation technique is employed to obtain the element excitation phase of each beam. The KPCA is a kind of principal component extraction method. Compared with the traditional method, the kernel function and the kernel parameter selection criterion used in the proposed study are designed to ensure that the extracted principal component can hold more than 80% of the information of the EEAM, which means that the acquired CEEA can bestly characterise the EEAM, hence resulting in a better synthesised pattern. In addition, the use of KPCA is a quasi-analytical process, which also speeds up the overall algorithm. Compared to the iterative multi-beam pattern synthesis algorithm, nearly half of the synthesis time is reduced. Through several sets of synthesised examples, and compared with some classical algorithms, this algorithm proves its superiority in the comprehensive effect and calculation time.

DESIGN OF DUAL PATTERN CONCENTRIC RING ARRAY ANTENNA USING DIFFERENTIAL EVOLUTION ALGORITHM WITH NOVEL EVOLUTIONARY OPERATORS

Concentric ring antenna arrays with the ability to produce dual pattern have many applications in communications and radar engineering. In this paper, we represent a new method for design of an optimized reconflgurable concentric ring array with dual pattern of desired speciflcations. Here, our goal is to flnd a suitable common element excitation amplitude distribution and two difierent element excitation phase distributions for two desired radiation patterns. For this purpose, we have proposed a novel objective function which is completely difierent from the traditional objective functions usually used in antenna design problems. For the optimization procedure, we have developed a modifled Difierential Evolution (DE) algorithm, denoted as DE rBM 2SX, which employs new kinds of crossover and mutation operators to overcome some drawbacks of the classical DE on single-objective fltness landscapes. We consider three types of dual pattern | pencil beam+pencil beam, pencil beam+∞at-top beam, ∞at-top beam+∞at-top beam. The simulation results obtained by applying our proposed method clearly indicate that our method is very convenient to obtain radiation patterns of desired speciflcations. We compare results of the modifled DE algorithm with those of another state-of-the-art improved variant of DE, called JADE and a state-of- the-art variant of the Particle Swarm Optimization (PSO) algorithm called Comprehensive Learning Particle Swarm Optimizer (CLPSO). Such comparisons re∞ect that the proposed algorithm is more e-cient than JADE or CLPSO in flnding optimum conflguration of the dual pattern concentric ring array antenna.

Interference suppression of linear antenna arrays by phase-only control using a clonal selection algorithm

In this paper, an efficient technique based on clonal selection algorithm (CLONALG) for linear antenna array pattern synthesis with null steering by controlling only the element excitation phases is presented. The CLONALG is an evolutionary computation method inspired by the clonal selection principle of human immune system. To show the versatility and flexibility of the proposed CLONALG, some examples of Chebyshev array pattern with the imposed single, multiple and broad nulls are given. The sensitivity of the nulling patterns due to small variations of the element phases is also investigated.

DEVELOPMENT OF A 10 GHz PHASED ARRAY CYLINDRICAL ANTENNA SYSTEM IN CORPORATING IF PHASE PROCESSING

This paper presents an experimental Phased Array Antenna System operating at 10 GHz. Geometry of the antenna array is cylindrical. Antenna element excitation phases are adjusted at the intermediate frequency stage. Antenna element excitation amplitudes are taken to be constant. A least squares technique is used for phase computation and radiation pattern synthesis. The obtained radiation patterns provide steerable main lobes and nulls at predefined directions including control of the side lobes at specified levels. Units of the system are presented in detail and their architecture is explained. A phase calibration is used to compensate the system. Measurements of radiation patterns are presented and are compared with calculated patterns.

Radiation pattern synthesis for arrays of conformal antennas mounted on arbitrarily-shaped three-dimensional platforms using genetic algorithms

A domain-decomposition/reciprocity procedure is presented which allows the radiation patterns of microstrip patch antennas mounted on arbitrarily-shaped three-dimensional perfectly electric conducting (PEC) platforms to be computed accurately as well as efficiently. The utility of this technique is demonstrated by considering an example consisting of a nine-element conformal array of microstrip patch antennas mounted axially along a finite-length PEC circular cylinder. It is shown that the elements close to the ends of the cylinder have significantly different patterns than those close to the center of the cylinder. The results from this example suggest that the common practice where all the individual element patterns are assumed identical is not always valid and, in fact, can lead to significant performance degradation in the design of conformal phased arrays. This observation is supported by the fact that an attempt to steer the main beam of the nine-element conformal array to an angle /spl theta//sub 0/=60/spl deg/ using a standard uniform progressive phase shifting technique proves unsuccessful. Next a genetic algorithm (GA) synthesis procedure is introduced that is capable of determining the optimal set of element excitation phases required to yield a desired or specified far-field radiation pattern. The results of this GA phase-only optimization are shown to yield the desired main beam steered to the correct angle for this nine-element linear array mounted on a circularly cylindrical platform. The GA radiation pattern synthesis procedure introduced appears to be a highly effective means of correcting for platform effects on the individual element patterns of a conformal phased array.

Phase-only synthesis of antenna array amplitude pattern

An iterative method for arbitrary antenna array amplitude radiation pattern phase- only synthesis is presented. The problem is solved in RMS approximation and is reduced to minimization of a non-negative functional by element excitation phases (sequentially by one element phase or by two element phases at each iteration) and by the phase of the given amplitude pattern.

Fast iterative methods for phase-only synthesisof antenna array pattern nulls

Two iterative methods for arbitrary antenna array pattern null phase synthesis are presented. The problem is solved in RMS approximation and is reduced to minimisation of non-negative functionals by element excitation phases. The methods are based on its numerical-analytical minimisation by one phase or by two phases on each iteration.