Yilong Lu

Sidelobe reduction in array-pattern synthesis using genetic algorithm

A simple and flexible genetic algorithm (GA) for pattern synthesis of antenna array with arbitrary geometric configuration is presented. Unlike conventional GA using binary coding and binary crossover, this approach directly represents the array excitation weighting vectors as complex number chromosomes and uses decimal linear crossover without a crossover site. Compared with conventional GAs, this approach has a few advantages: giving a clearer and simpler representation of the problem, simplifying chromosome construction, and totally avoiding binary encoding and decoding so as to simplify software programming and to reduce CPU time. This method also allows us to impose constraints on phases and magnitudes of complex excitation coefficients for preferable implementation in practice using digital phase shifters and digital attenuators. Successful applications show that the approach can be used as a general tool for pattern synthesis of arbitrary arrays.

Array failure correction with a genetic algorithm

A flexible approach using the genetic algorithm (GA) is proposed for array failure correction in digital beamforming of arbitrary arrays. In this approach, beamforming weights of an array are represented directly by a vector of complex numbers. The decimal linear crossover is employed so that no binary coding and decoding is necessary. Three mating schemes, adjacent-fitness-paring (AFP), best-mate-worst (BMW), and emperor-selective (EMS), are proposed and their performances are studied. Near-solutions from other analytic or heuristic techniques may be injected into the initial population to speed up convergence. Numerical examples of single- and multiple-element failure correction are presented to show the effectiveness of the approach.

Maximum likelihood DOA estimation in unknown colored noise fields

Direction-of-arrival (DOA) estimation in unknown noise environments is an important but challenging problem. Several methods based on maximum likelihood (ML) criteria and parameterization of signals or noise covariances have been established. Generally, to obtain the exact ML (EML) solutions, the DOAs must be jointly estimated along with other noise or signal parameters by optimizing a complicated nonlinear function over a high-dimensional problem space. Although the computation complexity can be reduced via derivation of suboptimal approximate ML (AML) functions using large sample assumption or least square criteria, nevertheless the AML estimators still require multi-dimensional search and the accuracy is lost to some extent. A particle swarm optimization (PSO) based solution is proposed here to compute the EML functions and explore the potential superior performances. A key characteristic of PSO is that the algorithm itself is highly robust yet remarkably simple to implement, while processing similar capabilities as other evolutionary algorithms such as the genetic algorithm (GA). Simulation results confirm the advantage of paring PSO with EML, and the PSO-EML estimator is shown to significantly outperform AML-based techniques in various scenarios at less computational costs.

Particle swarm optimization and finite-element based approach for microwave filter design

A novel approach is proposed for compact planar microwave filter design. The powerful particle swarm optimization (PSO) and finite-element method (FEM) are combined together to allow optimal filter design with arbitrary geometries. This approach is much more flexible than traditional ones. An example using this PSO-FEM approach shows that this approach is effective to make the structure variation converge to the desired target and the final optimal filter structure has much smaller size.

Vectorial finite element modelling of 2D leaky waveguides

An accurate finite element method is described for the analysis of leaky optical waveguides with arbitrary cross-section and inhomogeneous anisotropic dielectrics including loss or gain. The method leads to the iterative solution of a nonlinear matrix eigenvalue problem without compromising the sparsity of the resultant matrices which depend only on the mesh topology. >

An efficient finite element solution of inhomogeneous anisotropic and lossy dielectric waveguides

An efficient finite element method is presented for the full wave analysis of dielectric waveguides. This method has four major features: (1) the ability to treat a wide range of dielectric waveguide problems with arbitrarily shaped cross section, inhomogeneity, transverse-anisotropy, and significant loss (or gain); (2) total elimination of spurious solutions; (3) direct solution for the (complex) propagation constant at a specified frequency; and (4) the use of only two components of the magnetic field, thus maximizing the numerical efficiency of solution. The resultant matrix eigenvalue problem is of canonical form and is solved with an efficient method, specially developed for this purpose, taking full advantage of the sparsity of the matrices. Numerical results are shown for a variety of microwave and optical waveguides including anisotropy and losses. These examples also include closed and open structures. The computational results agree very well with analytical and previously published results. >

Miniaturization of Planar Monopole Antenna for Ultrawideband Radios

The miniaturization is described of a beveled planar monopole antenna in low temperature coflred ceramic technology for integration with ultrawideband radios. We demonstrate through simulations that a 40% reduction in size can be realized by simply exploiting its structural symmetry. We find that the miniaturized beveled planar monopole antenna exhibits wider impedance bandwidth, higher cross-polar radiation, and slightly lower gain at higher frequencies as compared with its un-miniaturized counterpart. We confirm the miniaturization with the measurements of both un-miniaturized and miniaturized beveled monopole antennas. The miniaturized beveled monopole antenna of size 17 × 10 × 1 mm3 has achieved impedance bandwidth of 8.25 GHz from 2.85 to 11.1 GHz, gain from -5.6 to 2.3 dBi, and broad patterns. Both frequency domain and time domain characteristics of the beveled monopole antennas are also carefully investigated with a normalized measured transfer function.

Dual Grid Array Antennas in a Thin-Profile Package for Flip-Chip Interconnection to Highly Integrated 60-GHz Radios

We examine the current development of highly integrated 60-GHz radios with an interest in antenna-circuit interfaces. We design and analyze grid array antennas with special attention to the differential feeding and the patterned ground plane. More importantly, we integrate two grid array antennas in a package; propose the way of assembling it to the system printed circuit board; and demonstrate a total solution of low cost and thin profile to highly integrated 60-GHz radios. We show that the package in low temperature cofired ceramic (LTCC) technology measures only 13×13×0.575 mm3 ; can carry a 60-GHz radio die of current and future sizes with flip-chip bonding; and achieves good antenna performance in the 60-GHz band with maximum gain of 13.5 and 14.5 dBi for the single-ended and differential antennas, respectively.

Improving the performance of GA-ML DOA estimator with a resampling scheme

The maximum likelihood (ML) direction of arrival (DOA) estimator computed by genetic algorithm (GA) for the exact global solution gives a superior performance compared to other methods. In this paper, we present a resampling-based scheme to improve its ability to resolve closely spaced sources, and to enhance its global convergence. For this purpose, multiple GA-ML estimators are constructed in a parallel manner based on resampling of a single data set, then those estimates are involved into a competition, and successful results are selected and combined to generate a more accurate estimate. Numerical studies demonstrate that the proposed scheme provides less DOA estimation root-mean-squared error (RMSE), higher source resolution probability and lower resolution threshold signal-to-noise ratio (SNR) than some popular approaches including GA-ML; and this technique is not sensitive to the array geometry, source correlation, and etc.

Compensation for the mutual coupling effect in the ESPRIT direction finding algorithm by using a more effective method

An effective method is introduced to compensate for the mutual coupling effect in the estimation of signal parameter via rotational invariance techniques (ESPRIT) direction finding algorithm. The compensation method seeks to quantify the mutual coupling more accurately by using a new mutual impedance. Study of two closely spaced arriving signals shows that the high-resolution capability of ESPRIT can be achieved only when the mutual coupling effect is compensated for by using our new compensation method. Critical situations with a large signal level difference, with an increased mutual coupling effect resulting from a more compact-size antenna array, and with signals coming from a nonhorizontal elevation angle are also studied using the ESPRIT algorithm. Results show that the new compensation method, when applied to ESPRIT, is more accurate, more robust, and more flexible than the previous open-circuit voltage method.