A current-mode ultrasound beamformer (BF) is proposed. Each channel of BF converts the echo voltage signal into current and performs uniform sampling. The sampled current of each channel is injected into one of the memory capacitors depending on a delay profile at time instance when the echo signal is sampled. Since multiple currents can be simultaneously added in parallel, multiple signal currents in parallel can be injected into one shared capacitor. By using this inherent characteristic of current-mode operation, BF of this work has a 1D memory structure unlike a 2D memory structure of other prior BFs. The proposed memory structure allows simultaneous access from multiple channels and sequential read-out operation. The proposed architecture of BF was verified by simulating an eight-channel BF using a high-voltage 0.18 μm CMOS process. Symmetric and linear delay profiles are applied to the designed BF and an output waveform of BF shows a good agreement with the derived channel gain equation. The BF consumes 220 μW/channel during receiving mode.

In the presence of steering vector (SV) mismatch, a novel iterative variable loading robust adaptive beamforming approach is presented in a new perspective. The proposed method searches for the desired array SV iteratively based on the relationship between the optimal weight vector and the assumed SV of standard Capon beamformer, which avoids any Lagrange multiplier methodology or the convex optimisation methods in each iteration. Simulation results demonstrate the superior performance of the proposed method.

The problem of synthesising a sparse linear array with multiple patterns is formulated as an extended reweighted -norm minimisation with multiple convex constraints. Synthesis results show that the proposed method can find the common sparse element positions with optimised excitations for multiple-pattern requirements, and the mainlobe, sidelobe as well as nulling region for each pattern can be accurately controlled.

A 247 mg weight coin-size piezoelectric-driven micro air vehicle (MAV) with four symmetrical distributed bionic flexible wings is presented. The MAV is planar designed and monolithic fabricated via film printed circuit, graphic lasering and lamination process, and is able to be self-assembled by using shape memory polymer (SMP). The SMP can be heated by the flexible circuit and shrink at a large strain, resulting in the self-folding of hinges and self-assembly of MAV from 2D shape into 3D shape. The flexible four-bar mechanism converts the slight vibration of lead zirconate titanate (PZT) actuator into flexible wings’ reciprocation, thereby generating lift force. The response characteristics and motion behaviour of the MAV are experimentally tested. Results suggest that the prototype can be self-assembled to the designed position and achieve a 23.5° reciprocating angle at 134 Hz resonance frequency under 280 V driving signals.

Diabetes is a chronic disease where millions of sufferers invasively prick their skin over the course of a day to take blood samples. Non-invasive glucose monitoring would bring relief to diabetics because it offers reduced skin damage. Microwave sensors are becoming a good choice for non-invasive glucose monitoring. This Letter presents two designs based on microwave sensors. The sensors have elliptical shapes and consist of a patch reflector and dielectric resonator (DR) that resemble a human thumb. A four-layer thumb model is presented, with a focus on the permittivity of the blood layer. The thumb was moved to various positions on the two microwave sensors to observe the effect it had on the frequency shift with various blood permittivity values. Observations showed that the elliptical DR sensor was less sensitive to errors and thumb positioning when taking glucose measurements than the elliptical patch sensor. The elliptical DR had an error of 55 MHz from the centre frequency, whereas that of the elliptical patch was 140 MHz. The effects of thumbs with various blood permittivity values were explored and explained.

This Letter proposes a low-cost, single event double-upset tolerant latch which utilises interlocked nodes to keep data, clock gating (CG) in Muller C-element (MCE) to turn off the storage cell, a three-input MCE to block the soft error from the storage cell and a weak keeper to prevent high impedance state. The storage cell in the proposed latch has better reliability than the conventional triple path dual-interlocked storage cell (TPDICE). Most up-to-date single event double-upset (SEDU) tolerant latches are carried out with too large cost penalties. The proposed one saves up to 93.32% area-power-delay product (APDP) compared with one up-to-date SEDU tolerant latch and even saves 36.36% APDP compared with only single event upset (SEU) tolerant latch in the referential. Simulation results have verified SEU and SEDU tolerance of the proposed latch.

A precharge free dynamic content addressable memory (DCAM) is introduced for low-power and high-speed search applications. Elimination of precharge prior to search allows hardware engine to perform more number of searches within the stipulated time. The proposed DCAM cell not only removes precharge of matchline (ML) but also utilises decoupling of bitline and searchline so that unwanted capacitive couplings are minimised at charge storage nodes. A 512 bit of the proposed scheme is implemented using 45 nm CMOS technology and its efficacy is verified and proved through rigorous variations with 1000-point Monte-Carlo sampling of ML voltage as well as multi-search dissipation analysis.

A modified turn algorithm based novel collision avoidance method for ground vehicles is proposed. Given two points in the plane, the proposed algorithm provides an effective path for collision avoidance in terms of curvature change. As this method alleviates sudden curvature changes and side-slip of the vehicle, it improves the overall driving performance. Further, the non-linear estimator for time-to-collision is introduced in order to improve the performance of collision avoidance. Simulation results demonstrate the superior performance of the proposed algorithm over the existing lane change algorithm.

A novel tone mapping algorithm and hardware implementation for displaying wide dynamic range (WDR) images are proposed. The algorithm processes WDR images in a pixel-by-pixel fashion in the logarithmic domain, and it uses the block-interpolated minimum and maximum pixel values. The hardware implementation can achieve real-time processing of WDR images and is resource-efficient. Experimental results show that the proposed algorithm and hardware implementation can produce images with good brightness and high contrast.

A new image encryption method based on permutation–diffusion architecture is proposed. Permutation and diffusion operations are performed row-wise and column-wise on input image. To permute and diffuse the pixels, Lorenz-like chaotic system with varying bifurcation parameter is used to generate six random sequences. Initially, three sequences help in change the pixel’s position and next three used to diffuse the pixels. The main benefit of this method is that it is more sensitive to input image. Since input parameters required for secure key generation depend upon the input image.

With increasing markets for fingerprint authentication, there are also increasing concerns about spoofs or synthetically produced fingerprint identifications that can bypass the authentication process. In this Letter, the authors introduce a new convolutional neural networks (CNNs) architecture for fingerprint liveness detection problem that can provide a more robust framework for network training and detection than previous methods. The proposed method employs squared regression error for each receptive field without the usage of the fully connected layer. Such structure provides following advantages from the previous liveness fingerprint CNN. First, unlike the previous techniques which rely on the pre-trained features, the proposed CNN can be trained directly from fingerprints as the loss is minimised for each receptive field. Second, in contrast to the cross-entropy layer, the squared error layer allows them to set up a threshold value that can control the acceptable level of false positives or false negatives. Third, the absence of a fully connected layer allows them to crop the input fingerprints such that a trade-off between accuracy and computation time can be made without the negative effects of re-scaling. The proposed CNN is shown to provide higher accuracy for three out of four datasets when evaluated against the state-of-the-art method.

This Letter investigates traffic matrix (TM) prediction that is widely used in various network management tasks. To fastly and accurately attain timely TM estimation in large-scale networks, the authors propose a deep architecture based on LSTM recurrent neural networks (RNNs) to model the spatio-temporal features of network traffic and then propose a novel TM prediction approach based on deep LSTM RNNs and a linear regression model. By training and validating it on real-world data from Abilene network, the authors show that the proposed TM prediction approach can achieve state-of-the-art TM prediction performance.

A new bipolar junction transistor-based temperature sensor with duty-cycle-modulated output is presented. By employing a capacitor-reused voltage to the duty-cycle converter, the proposed design achieves both area and energy efficiencies simultaneously. The self-controlled chopping, dynamic element matching and digital-assisted calibration techniques are applied as well to further improve the accuracy. Fabricated in a standard 0.13 μm CMOS process, the proposed sensor achieves the measured 3 inaccuracy of from to after one-point calibration while occupying a silicon area of 0.073 mm².

Three types of commercially available conductive three-dimensional (3D) printing filament are electrically characterised for use in 3D-printed functional devices. The three plastics were carbon dispersed acrylonitrile butadiene styrene, carbon dispersed polylactic acid (PLA) and graphene dispersed PLA. The method of 3D printing used was material extrusion and prints were made in both single and dual extrusion modes. The plastics were found to be piezoresistive, enabling them to be characterised as strain sensors. The electrical characteristics of these materials enabled the measurement of strain using low cost, readily available prototyping equipment and minimising the requirement for dedicated instrumentation components (e.g. Wheatstone bridges). Increasing the thickness of the plastics improved conductivity. However, this also decreased the reliability and reproducibility of strain sensor data due to a complex internal 3D structure. The recommendation for reliable use in prototyping and manufacturing is to print tracking under 0.8 mm thickness, thus producing resistance measurements that are predictable and follow a linear regression up to R ² = 0.9991. A dual extruded 3D print was fabricated as a final demonstration. A force sensing resistor interface was created. The final demonstration uses a PIC18F45K20 microcontroller to process sensor inputs, outputting to an alphanumeric LCD.

A novel three-line-microstrip compact impedance tuner is presented. It is based on a multimodal structure wherein six variable capacitances, implemented with two parallel-connected varactors each, create multiple interactions among the three-line-microstrip modes in a reduced circuit area. Experimental results show better-than-70% coverage of the Smith chart in an 85% frequency bandwidth from 1.4 to 3.2 GHz.

A modified series combining transformer incorporating an autotransformer for the dual-mode operation to improve efficiency performance in the low-output power region is presented. The dual-mode CMOS power amplifier (PA) with the proposed reconfigurable transformer is fabricated using 40-nm CMOS technology. Compared with other dual-mode WLAN CMOS PAs, the proposed PA achieves high-efficiency performance in both high-power and low-power modes; in dual-mode operation, the PA has average output power levels of 19.2 and 15.2 dBm with power added efficiencies of 17.3 and 14.4%, respectively, while satisfying the error vector magnitude requirements of WLAN 802.11g signals.

A new approach for the filtering crossover design is proposed in this Letter. This approach is based on the mixed electric and magnetic coupling. A compact filtering crossover constructed by the short stub loaded resonator is presented according to the proposed approach. By using a short stub loaded resonator the filtering response is achieved and by using the cancelling effect between the electric coupling and magnetic coupling, the isolation between two signal paths is achieved. A filtering crossover is fabricated for demonstration. The measured result presents good agreement with the simulated result.

A type of wide-band signal-interference planar duplexer with single- and dual-band channels is presented. It exploits transversal-signal-interference-section-based channels with contiguous single- and dual-passband filtering transfer functions. Furthermore, by ending the dual-band channel in a reference-impedance resistor, a wide-band bandpass filter (BPF) with quasi-absorptive stopbands is realised. As experimental validation, microstrip prototypes of a duplexer and a two-stage quasi-absorptive BPF that operate in the 1.6–4.4 GHz range are built and tested.

An all-optical AND gate using photonic-crystal quantum dot semiconductor optical amplifiers is designed and its performance is evaluated. The input–output characteristics of the gate are simulated using a rate equation model and it is found that the gate can achieve a maximum of ∼9 dB extinction ratio at 160 Gb/s. The proposed gate is compared with quantum dot semiconductor optical amplifiers AND gate to evaluate its effectiveness with regard to signal quality, device size, and power consumption.

Distributed-feedback ridge-waveguide lasers emitting around 670 nm have been fabricated and experimentally characterised. Wavelength stabilisation is provided by 40th Bragg order surface gratings dry-etched into the p-GaAs–AlGaAs–AlGaInP layer structure. The large grating period of 4.2 µm allows the injection of the current between the grooves of the grating without sacrificing the electrical and optical properties noticeably. The 1.5 mm long devices achieve an output power of 50 mW at an injection current of 180 mA. The side mode suppression ratio is 50 dB at 150 mA.

Control and manipulation of polarisation is an important topic for imaging and light matter interactions. In the infrared regime, the large wavelengths make wire grid polarisers (WGPs) a viable option, as it is possible to create periodic arrays of metallic wires at that scale. The recent advent of metamaterials has spurred an increase in non-traditional polariser motifs centred around more complicated repeat units, which potentially provide more functionality. The authors explore the use of 2D arrays of single and back-to-back vertically oriented cross dipoles arranged in a cubic in-plane silicon matrix. They show that both single and back-to-back versions have higher rejection ratios and larger bandwidths than either WGPs or 2D arrays of linear dipoles.

A low-power pulse width modulation (PWM) control circuit for high-frequency switching direct current (DC)–DC converters based on a one-shot circuit is proposed. The proposed PWM control circuit eliminates the use of a high-power comparator and ramp generator that is conventionally used to generate the PWM waveform. The design is validated through simulation in a 0.13-μm process. The proposed circuit operating at 20 MHz demonstrates greater than 20× reduction in power consumption compared with the conventional PWM circuit over a duty-cycle range of 10–90%.

To ensure the stable operation of Experimental Advanced Superconducting Tokamak (EAST) fast control power supply, a new alternating current insulation monitoring technique is presented in this Letter which is suitable for the high-frequency and high-voltage working environment of EAST fast control power supply. The method uses alternately switching resistance in an unbalanced bridge to change the voltage, and detects the voltage in real time, then calculates the insulation resistance. The simulation platform based on Simulink was built to carry out real-time insulation monitoring analysis of EAST fast control power supply as voltage input, the waveforms of which were consistent with the expected. Through experimental verification, the new method can work well for EAST fast control power supply.

A parallel direct current (DC) to DC converter is presented for medium power applications. The studied converter includes three half-bridge circuits with sharing two power switches at high-voltage side to reduce switch counts. Three half-bridge circuits are connected by primary-parallel and secondary-parallel to reduce the current stress of power devices at low-voltage side. Each half-bridge circuit supplies one-third of the total power to the output load. Asymmetric pulse-width modulation is employed to generate the gated signals of the switches and regulate the output voltage. Based on the resonant behaviour of the output capacitance of power switches and the leakage inductance of the transformer, the zero-voltage switching turn-on of power switches can be achieved. Current doubler rectifier topology is adopted at the low-voltage side to have the advantage of low ripple current at output capacitor. A laboratory prototype with 1440 W power is built to verify theory analysis and effectiveness of the studied converter.

Spatial frequency adaptive processing (SFAP) is the dimension-reduced alternative of spatial temporal adaptive processing (STAP), which can achieve good interference mitigation capability with less computational cost. However, just as STAP, the biases of the ranging code phase and carrier phase induced by the adaptive array restrict SFAP from being applied in high-precision global navigation satellite system receivers. To address this issue, a new data-oriented calibration method is proposed. Unlike previous bias reduction methods, which compensate the measurement biases with estimated values in the tracking loop, this method carries out calibration directly on the received data in the frequency domain, thus avoids modification to the rest parts of the receiver other than the SFAP module. The calibration value in each frequency bin is determined from the transfer function of the SFAP array. Simulations are performed on a practical array antenna designed by the high-frequency structure simulator software with high fidelity, and the results verify the effectiveness of this method.

Entropy score is defined to be a metric indicating the class separation, which is then used in feature selection process to improve the moment-based classification performance of synthetic aperture radar (SAR) images. Feature extraction is performed over each SAR image by employing different moment methods to enrich the feature space before feature selection. Fusing all the features coming from different moment methods into a single vector is not feasible since the vector will have high dimensionality and embedded redundancies due to correlations among features. To reduce the dimensionality of feature space and increase the discrimination capability of the feature vector, a unique approach based on entropy score selecting top k methods for each feature coefficient is proposed. Experimental results verify the improvement of the accuracy on SAR image classification over the state-of-the-art.

A method to infer the terrain of unobserved fields as well as navigation paths using vibrations from vehicle–terrain interactions is presented. The relationships between adjacent terrain grids and robot paths are modelled by Markov random field (MRF) for inferring the classes of unobserved field. In order to approximate the complex likelihood of vibration features as a tractable distribution, a variational auto-encoder is adopted. By projecting intractable features to the latent space, an approximated likelihood that gives similar performance to a neural network classifier is obtained. Then the numerical maximum a posterior inference for MRF is obtained. The result of inferred terrain maps are compared with that from the feature likelihood as a Gaussian-mixture model.

Geolocating a stationary ground source using the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements from more than two sensors with random location errors is considered. The source altitude is known and a constrained weighted least square (WLS) problem is formulated for the geolocation task. The optimisation problem is solved by searching for the source-reference sensor distance in its feasible region and the source position estimate minimising the cost function. Simulations show the improved robustness of the proposed method over two existing solutions under high noise levels.

A new autonomous distributed link scheduling scheme, SINBADLinQ, for device-to-device networks is proposed. SINBADLinQ operates with a modified signal-to-inference-plus-noise ratio. The new link scheduling scheme outperforms recently proposed ITLinQ and ITLinQ+ with or without global scheduling information sharing.

Physical layer security is a promising approach to establish secure communications based on the characteristics of wireless channels. A spatial signature based secure multiple-input single-output (MISO) orthogonal frequency division multiplexing (OFDM) system is proposed to disrupt the reception of a passive eavesdropper by holding two practically relevant assumptions: a limited feedback link for legitimate node and the unavailability of channel state information of eavesdropper. The proposed algorithm achieves a higher average secrecy rate than the conventional secure MISO-OFDM systems in presence of a limited feedback link.