We put forward an optically transparent microwave absorber based on a conformal broadband metamaterial, which shows high angular stability. Our absorber is a double-layer sandwich structure mainly made of transparent polyvinyl chloride sheets and indium tin oxide films. To achieve wideband absorption and high angular stability, an impedance layer composed of square spiral elements is exploited to increase the absorption bandwidth. A compensation layer is then employed to address the mismatch between the impedance of the absorber and that of free space at high angular incidences. Experimental results show that a high light transmittance (69.4%), together with an adequate absorption bandwidth (85.7%) and angular stability (60°) may be achieved with planar and conformal configurations, including different curvatures.

Off-grid direction of arrival (OGDOA) estimation methods deal with the situations where true direction of arrivals (DOAs) are not on the discretized sampling grid. However, existing OGDOA estimation methods are faced with a tradeoff between density of initial grid and computational workload. Furthermore, these methods fail if more than one true DOA is located in a same grid interval. In order to speed up the OGDOA estimation methods and solve the problem of more than one DOA in one initial grid interval, a grid evolution direction of arrival (GEDOA) estimation method is proposed. Based on the combination of OGDOA estimation methods and grid refinement, this new approach makes the grid nonuniformly evolve from coarse to dense. The proposed method contains two subprocesses, i.e., learning process and fission process. The learning process aims to update locations of grid points and estimate DOAs. The fission process aims to generate new grid points and guarantees that there is only one DOA in a grid interval. The two processes iterate alternatively. Finally, an adaptive and nonuniform grid and an estimated spatial spectrum based on this grid are achieved. Compared with the previous methods, GEDOA has better computational efficiency because fewer grid points are used at each iteration. Furthermore, GEDOA has better resolution and lower MSE at relative high SNR. This is because that the evolved grid obtained by this new approach is information adaptive. Numerical simulations validate the effectiveness of the proposed method.

The accurate classification of activity patterns based on radar signatures is still an open problem and is key to detect anomalous behavior for security and health applications. This paper presents a novel iterative convolutional neural networks strategy with an autocorrelation pre-processing instead of the traditional micro-Doppler image pre-processing to classify activities or subjects accurately. The proposed strategy uses an iterative deep learning framework for the automatic definition and extraction of features. This is followed by a traditional supervised learning classifier to label the different activities. Using three human subjects and their real motion captured data, twelve thousand radar signatures were simulated by varying additive white Gaussian noise. Additionally, 6720 experimental radar signatures were captured with a frequency-modulated continuous radar at 5.8GHz with 400MHz of instantaneous bandwidth from seven activities using one subject and 4800 signatures from five subjects while walking. The simulated and experimental data were both used to validate our proposed method. With SNR varying from –20 to 20dB with 88.74% average accuracy at –10dB and 100% peak accuracy at 15dB. The proposed Iterative Convolutional Neural Networks followed with Random Forests (ICNNRF) does not only outperform the feature-based methods using micro-Doppler images but also the classification methods using other types of supervised classifiers after our proposed iterative convolutional neural network.

The paper focuses on the problem of maximizing the minimum power gain in a wide mainlobe for array antenna. To obtain the desired power gain pattern, current literatures solve the problem known as shaped beam pattern synthesis (SBPS) by setting the beam pattern expression as the cost function. The power gain in a certain direction of array antenna is comprehensively decided by the array radiated power density and the total radiated power. Both these two parameters are affected by the selection of array elements’ weights. However, the SBPS-based methods don’t take the total radiated power into account. Therefore the SBPS-based methods cannot obtain the power gain pattern directly and the optimal power gain pattern, consequently, cannot be guaranteed. To overcome this deficiency, this paper maximizes the minimum power gain in the desired wide mainlobe by directly setting the power gain expression as the cost function. Aiming at optimizing the cost function, the paper firstly sets up a power gain optimization problem which has concave form. Termed this optimization problem as the Power Gain Pattern Synthesis (PGPS) problem. The concave PGPS problem is then converted to a series of convex subproblems and an iterative algorithm is proposed to solve it efficiently. Solution to the PGPS problem is proved to be able to achieve higher minimum power gain in a desired wide mainlobe than the results from the SBPS-based algorithms. Simulations are carried out with both linear array antenna and planar array antenna. Comparisons with the existed SBPS-based algorithms validate the effectiveness and advantages of the proposed PGPSbased algorithm. Besides, further improvement on suppressing the sidelobe level for the PGPS problem is discussed.

A compact multimode monopole antenna for heptaband metal-rimmed smartphones is proposed. The metal bezel is kept unbroken and no lumped element is needed. To cover the low band, the bezel mode is excited by a capacitive coupling vertical plate, and a bandwidth enhancement technique is introduced for this mode. For the high band, printed multiple branches on both sides of substrate are well designed to obtain multiple modes to cover a wide band. With the proposed structure, the frequency bands can be widened by tuning and optimization. The new-type monopole occupies an area of 60×5×5 mm3 on a 120×60 mm2 system board, which has a narrow ground clearance and a low profile. A prototype is fabricated and measured to validate the proposed design. Measured results show that the proposed antenna has two impedance bands with S11 less than -6 dB, i.e., 23% for the low band (0.76-0.96 GHz) and 57% for the high band (1.51-2.72 GHz). The proposed monopole antenna is capable of covering the GSM/DCS/PCS/UMTS and LTE2300/2500 bands for modern metal-rimmed mobile phone applications.

An eight-element antenna system operating at sub 6 GHz is presented in this work for a future multiple-input multiple-output (MIMO) system based on a modified E-slot on the ground. The modified E-slot significantly lowers the coupling among the antenna components by suppressing the ground current effect. The design concept is validated by accurately measuring and carefully fabricating an eight-element MIMO antenna. The experimentation yields higher element isolation greater than −21 dB in the 3.5 GHz band and the desired band is achieved at −6 dB impedance bandwidth. The E-shape slot occupies an area of 17.8 mm × 5.6 mm designed on an FR-4 substrate with dimensions of 150 mm × 75 mm × 0.8 mm. We fed the I-antenna element with an L-shape micro-strip feedline, the size of the I-antenna is 20.4 × 5.2 mm², which operates in the (3.4–3.65 GHz) band. Moreover, our method obtained an envelope correlation coefficient (ECC) of <0.01 and an ergodic channel capacity of 43.50 bps/Hz. The ECC and ergodic channel capacity are important metrics for evaluating MIMO system performance. Results indicate that the proposed antenna system is a good option to be used in 5G mobile phone applications.