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Here, a high-precision mutual coupling coefficient estimation method is proposed that is more suitable for adaptive beamforming than traditional algorithms. According to the relationship between the designed transition matrix and the signal, the proposed algorithm selects the transition matrix corresponding to the high-power signal. The high-precision estimation of the mutual coupling coefficient is obtained by using the selected transition matrix estimation, which yields relatively good estimation accuracy for the mutual coupling coefficient when the desired signal-to-noise ratio (SNR) is low and relatively robust adaptive beamforming with unknown mutual coupling. Simulation results demonstrate the validity of the proposed method.

In this paper, we consider the problem of robust adaptive beamforming (RAB) for a linear array in the presence of gain-phase errors. By setting a few calibrated auxiliary elements on one side of a linear array, we propose a novel gain error and phase error estimation algorithm to calibrate gain-phase errors. According to the proposed estimation algorithm, the unknown gain error and phase error are jointly estimated by calculating the eigenvector corresponding to the minimum eigenvalue of the available transitional matrices. Furthermore, we calibrate the received data and compensate for the nonwhite noise caused by the calibration process. Then, the interference-plus-noise covariance matrix (INCM) is reconstructed based on the calibrated steering vector. By incorporating the reconstructed INCM with the minimum variance distortionless response principle, a novel robust adaptive beamformer for a linear array with gain-phase errors is designed. The proposed beamformer can obviously improve RAB performance in a linear array with gain-phase errors. The robustness and superiority of the designed beamformer are demonstrated in simulations.

High temperature sensor with robust performance, minimum footprint, and fast response is desirable for many applications in extreme environments. This article introduces a miniature high temperature sensor based on fiber Fabry-Perot interferometer. The interferometric cavity is directly fabricated on the tip of a 125 μm single-crystal sapphire fiber through femtosecond laser micromachining and CO2 laser welding with the sapphire fiber as a light-guiding element. The sensor has an all-sapphire structure to ensure both physical and chemical stability. The sensor was tested in the lab from room temperature up to 1455 °C and shows an excellent temperature response with 1.32 nm/ °C at room temperature and full-range average resolution of 0.68 °C. The thermal response of the sensor is evaluated via both numerical simulation and experiment. Owing to the small size and fast thermal diffusivity of sapphire, the thermal response time of ∼1.25 ms has been experimentally demonstrated.

Understanding the cytoarchitecture and wiring of the brain requires improved methods to record and stimulate large groups of neurons with cellular specificity. This requires miniaturized neural interfaces that integrate into brain tissue without altering its properties. Existing neural interface technologies have been shown to provide high-resolution electrophysiological recording with high signal-to-noise ratio. However, with single implantation, the physical properties of these devices limit their access to one, small brain region. To overcome this limitation, we developed a platform that provides three-dimensional coverage of brain tissue through multisite multifunctional fiber-based neural probes guided in a helical scaffold. Chronic recordings from the spatially expandable fiber probes demonstrate the ability of these fiber probes capturing brain activities with a single-unit resolution for long observation times. Furthermore, using Thy1-ChR2-YFP mice we demonstrate the application of our probes in simultaneous recording and optical/chemical modulation of brain activities across distant regions. Similarly, varying electrographic brain activities from different brain regions were detected by our customizable probes in a mouse model of epilepsy, suggesting the potential of using these probes for the investigation of brain disorders such as epilepsy. Ultimately, this technique enables three-dimensional manipulation and mapping of brain activities across distant regions in the deep brain with minimal tissue damage, which can bring new insights for deciphering complex brain functions and dynamics in the near future., Existing neural interfaces are limited in accessing one, small brain region. Here, the authors introduce a scaffold with helix hollow channels, which direct multisite multifunctional fibre probes into the brain at different angles, allowing for simultaneous recording and stimulation across distant regions.

Sparse arrays, which can localize multiple sources with less physical sensors, have attracted more attention since they were proposed. However, for optimal performance of sparse arrays, it is usually assumed that the circumstances are ideal. But in practice, the performance of sparse arrays will suffer from the model errors like mutual coupling, gain and phase error, and sensor’s location error, which causes severe performance degradation or even failure of the direction of arrival (DOA) estimation algorithms. In this study, we follow with interest and propose a covariance-based sparse representation method in the presence of gain and phase errors, where a generalized nested array is employed. The proposed strategy not only enhances the degrees of freedom (DOFs) to deal with more sources but also obtains more accurate DOA estimations despite gain and phase errors. The Cramer–Rao bound (CRB) derivation is analyzed to demonstrate the robustness of the method. Finally, numerical examples illustrate the effectiveness of the proposed method from DOA estimation.

This paper reports a miniature all-sapphire high temperature fiber sensor based on fiber Fabry-Perot interferometer fabricated by femtosecond laser micromachining and CO2 laser welding. The sensor was tested to 1455°C with up to 5.38 nm/°C sensitivity.

Phase extraction of interferometry is a crucial step of optical measurement. In this paper, a machine learning method is proposed to extract the phase from the interferometric signal with the least squares support vector machine, which eliminates the phase unwrapping procedure and enhances the phase measuring accuracy greatly when compared with traditional phase unwrapping methods. Furthermore, it can also work well in the undersampling situation to some extent. Our method is capable of extracting both linear and nonlinear phases. A Michelson interferometer was constructed to demonstrate the validity of the method proposed, which can be potentially applied in many significant fields.

A thermal stress measuring method based on the digital shearing speckle pattern interferometry (DSSPI) is proposed in this paper. The concept of the method is that the thermal inequality leading to the deformation of the object surface will be recorded by the shearing speckle pattern, which is captured by CCD and analyzed in computer subsequently. This system making use of Wollaston prism has obvious advantages in non-contact, instantaneity, high-efficiency, low-cost, robustness and simplicity. The principle of the method is elucidated, and related experimental results with the simulation of finite element method (FEM) in contrast are presented.

The rank-deficiency and subspace leakage caused by multipath effect are the main factors that lead to performance breakdown of direction of arrival (DOA) estimation in low-altitude environment. In this paper, we propose an orthogonal projection method based on signal subspace to overcome the negative effects of multipath. First, the signal covariance matrix is recovered to full-rank by forward and backward spatial smoothing (FBSS). Then, based on the least square technique, the signal subspace is used to establish the orthogonal projection matrix. Thereby the cross covariance matrices of signal and noise parts can be estimated and eliminated to modify the sample covariance matrix. Compared with the conventional methods that only dispose rank-deficiency, the proposed method has better performances in low-altitude environment. Besides, compared with the former orthogonal projection method based on steering matrix, this method reduces the computational complexity without iterative scheme. These conclusions are verified by simulations.

A kind of sample tube pressure-keeping cutting device is designed, which is feasible from the perspective of manufacturing and assembly, and the relevant Ansys simulation is carried out to verify the rationality of the structure. The biggest breakthrough is that one installation can realize multiple cutting of sampling pipes, eliminating the step of cleaning sea mud in the pipes. In addition, the redesign of the cutting knife and the re-selection of the outer cylinder material reduced the overall size to 71.9% and the mass to 22.3%. Anti-sludge blocking design was carried out, thus realizing long-term use design.

Based on MATLAB, coordinate transformation and the b-spline curve are used to fitting data to obtain the propeller blade curve, which is simply used as the cleaning track. And a smooth trajectory of the cleaning manipulator is constructed by using the cubic interpolation method of quaternion sphere to achieve the continuity of 3d rotation and smoothness of the robot motion in the task space.

Triboelectric generators and sensors have a great potential as self-powered wearable devices for energy harvesting, biomedical monitoring, and recording human activity. Here, we report a process for 3D printing stretchable membranes, meshes, and hollow 3D structures on planar, rotating, and non-planar anatomical substrates using elastomeric metal-core triboelectric nanogenerator (TENG) fibers. The triboelectric performance of single 3D-printed elastomeric metal-core silicone-copper (Cu) (cladding-core) fibers and 3D-printed membranes was quantified by cyclic loading tests, which showed maximum power densities of 31.39 and 23.94 mW m−2, respectively. The utility of the flexible silicone-Cu TENG fibers and 3D printing process was demonstrated through applications to wearable mechanosensors for organ and human activity monitoring, specifically, monitoring of perfused organs and speech recognition in the absence of sound production by the speaker (i.e., ‘silent speech’), respectively. 3D-printed wearable triboelectric mechanosensors, in the form of stretchable form-fitting meshes and membranes, in combination with machine-learning signal processing algorithms, enabled real-time monitoring of perfusion-induced kidney edema and speech recognition in the absence of sound production by human subjects (99% word classification accuracy). Overall, this work expands the conductive and functional materials palette for 3D printing and encourages the use of 3D-printed triboelectric devices for self-powered sensing applications in biomanufacturing, medicine, and defense.

In the era of the internet of things (IoTs), it is desired to equip the decentralized electronics with distributed power sources. The fiber-based triboelectric nanogenerator (FTENG) provides one of the soundest solutions due to its high efficiency, easy deployment, excellent wearability, low cost, and eco-friendliness. Compared with other forms of TENGs, it can be woven into fabrics as wearable devices, offering good compactness and comfortability. However, the industrial-loom-compatible FTENGs have yet to be fabricated; the fiber diameter and length are typical challenges in the large scale weaving. In this paper, the thermal drawing process (TDP) is introduced to produce FTENGs that are compatible with industrial looms. The diameter of the polymer-cladding and metal-core fiber has been reduced to ~350 μm, and the length of a single fiber has been scaled up to sub-kilometer. Both hand-woven and loom-woven swatches are demonstrated, showing good flexibility, stretchability, power density, stability, washability, and breathability. Besides serving as power sources, such swatches have been used as self-powered sensors for body motion monitoring and communication. These applications show that the thermally drawn FTENGs can serve as powerful and reliable wearable devices in modern electronics.

Due to the superiority in target detection, anti-jamming and parameter estimation of targets, Multiple-input multiple-output (MIMO) radar has attracted wide attention. However, the good performance of direction finding is achieved on the assumption that all the elements of the antenna are in ideal circumstances. In practice, the elements will suffer from some uncertainties caused by electromagnetic environment such as mutual coupling and amplitude and phase error, which will lead to performance decreases or even failure. A novel antenna array geometry for nested MIMO radar, which both lowers the impact of mutual coupling and extends the degrees of freedom (DOF), is discussed. The signal model and structure of mutual coupling matrix are constructed by utilizing the geometry, selection matrices are constructed to maintain the Vandermonde characteristic of the manifold matrix of arrays, and the directions-of-arrival (DOAs) is estimated by utilizing the Spatial Smoothing MUSIC (Multiple Signal Classification) algorithm. Theoretical derivation indicates the superior performance in direction finding and mutual coupling calibration of the proposed method. Simulation results demonstrate the correctness.

Buoys traditional uses battery for energy supplement, which may have shortcomings, such as short working life, inconvenient battery replacement, etc. Therefore, renewable energy analysis becomes a hot topic. In this regard, this research proposed an energy capture device located in the buoy. It collects the kinetic energy of the buoy and stores it in an accumulator when the buoy floats on the sea surface. The hydrodynamic characteristics of the device under the fourth-order sea conditions are study by using CFD numerical simulation. It is evident that the proposed device has energy capture function.

Nested array can expand the degrees of freedom (DOF) from difference coarray perspective, but suffering from the performance degradation of direction of arrival (DOA) estimation in unknown non-uniform noise. In this paper, a novel diagonal reloading (DR) based DOA estimation algorithm is proposed using a recently developed nested MIMO array. The elements in the main diagonal of the sample covariance matrix are eliminated; next the smallest MN-K eigenvalues of the revised matrix are obtained and averaged to estimate the sum value of the signal power. Further the estimated sum value is filled into the main diagonal of the revised matrix for estimating the signal covariance matrix. In this case, the negative effect of noise is eliminated without losing the useful information of the signal matrix. Besides, the degrees of freedom are expanded obviously, resulting in the performance improvement. Several simulations are conducted to demonstrate the effectiveness of the proposed algorithm.

A heterodyne imaging speckle interferometer coupled with lithium niobate is developed for whole field dynamic deformation imaging. In this device, the carrier frequency is introduced by the dual-transverse linear electro-optic effect. It is electrically controlled within a large range, which is twice the angular velocity of the driving alternating electric fields. By setting the angular velocity, the carrier frequency can fit most of area-array detectors, making it feasible to achieve whole field real time imaging. By using temporal evolution of the light intensity in heterodyne interferometry, the temporal intensity analysis method is employed to extract the deformation at each pixel dynamically. The principle and system configuration are described. The preliminary experiment is conducted with a cantilever beam and the results are compared with theoretical simulations to validate the proposed approach.

Interferometry is an optical measuring method with the character of non-destructive, high sensitivity and high accuracy. However, its measurement range is limited by the phase ambiguity. Hence the method with two separate different wavelengths light source is introduced to enlarge the measurement range. As for the two-wavelength interferometry case, phase shifting is the traditional way to acquire the phase map, it needs to repeat the measurement twice, which means the measurement cannot be accomplished in real time. Hence to solve the problem, a temporal sequence interferometry has been used. This method can obtain the desired phase information in real time by using the Fourier transform methods of the interferogram recorded in a sequence while the object is being deformed. But, it is difficult to retrieve the phase information directly due to the multi extreme points in one period of the cosine function. In this paper, an algorithm based on the wavelet ridge analysis is adopted to retrieve the two wavelength phase fluctuation caused by the displacement simultaneously. The preliminary experiment is conducted and the results are compared with theoretical simulations to validate the proposed approach. The laser emits light with two wavelengths 532 nm and 473 nm, two separated interference patterns in time sequence are detected by the CCD camera in the same time. The overlapped interferograms of two colors are analyzed by this algorithm and the corresponding phase information are obtained. The maximum error value between the simulation and theory is 0.03 um and the relative error is 0.33%.

Direction finding is a hot research area in radar and sonar systems. In the case of q ≥ 2, the 2qth-order cumulant based direction of arrival (DOA) estimation algorithm for the 2q-level nested array can achieve high resolution performance. A virtual 2qth-order difference co-array, which contains O(N2q) virtual sensors in the form of a uniform linear array (ULA), is yielded and the Gaussian noise is eliminated. However, some virtual elements are separated by the holes among the 2qth-order difference co-array and cannot be fully used. Even though the application of the multi-frequency method for minimum frequency separation (MFMFS) can fill the holes with low computation complexity, it requires that the number of frequencies must increase with the number of holes. In addition, the signal spectra have to be proportional for all frequencies, which is hard to satisfy when the number of holes is large. Aiming at this, we further propose a multi-frequency method for a minimum number of frequencies (MFMNF) and discuss the best frequency choice under two specific situations. Simulation results verify that, compared with the MFMFS method, the proposed MFMNF method can use only one frequency to fill all the holes while achieving a longer virtual array and the DOA estimation performance is, therefore, improved.

Digital shearing speckle pattern interferometry (DSSPI) has been recognized as a practical tool in testing strain. The DSSPI system which is based on temporal analysis is attractive because of its ability to measure strain dynamically. In this paper, such a DSSPI system with Wollaston prism has been built. The principles and system arrangement are described and the preliminary experimental result of the displacement-derivative test of an aluminum plate is shown with the wavelet transformation method and the Fourier transformation method. The simulations have been conducted with the finite element method. The comparison of the results shows that quantitative measurement of displacement-derivative has been realized.

Digital shearing speckle pattern interferometry (DSSPI) is a powerful tool in the measurement of strain, residual stress and the non-destructive testing (NDT). It is widely used in the fields of wood testing, tire inspection and aerospace, etc. The DSSPI system based on the Wollaston prism is attractive because of its compact arrangement, high immunity to disturbance, and, most of all, the ability to measure strain directly. It could show the strain distribution of the measured object by producing fringe patterns. In conventional DSSPI systems, phase-shifting devices are commonly adopted to extract phase information from the fringe patterns, which means dynamical measurement cannot be realized. In this paper, the principle of a novel DSSPI system based on the temporal analysis is presented. Phase information is extracted with the Fourier Transform method instead of the phase-shifting devices in this system. In this way, dynamical measurement is realized. The measuring accuracy is mostly determined by the quality of the fringe patterns (the fringe width and the contrast ratio). There are several factors that influence the quality of the fringe patterns. Here we mainly discuss the influence of the shearing distance and the polarization state. The preliminary experiments with different shearing distances and polarization states are conducted. The ideal shearing distance and polarization state are suggested.

Vibration is one of the confused problems in many fields. To give a comprehensive analysis of vibration, an electro-optical heterodyne interferometry with temporal intensity analysis method that can track the trajectory of the vibration dynamically has been built in this paper. The carrier frequency is introduced by the electrically controlled electro-optical frequency shifter. The trajectory is obtained by using temporal evolution of the light intensity in heterodyne interferometry. The instantaneous displacement of the vibration is extracted with spectral analysis technique. No target mirror and moving parts are required in our self-developed system. The principle and system configuration are described. The simulations and the preliminary experiments have been performed and the results show that this trajectory tracking system is high-efficiency, low-cost, jamproof, robust, precise and simple.

Pulse oximeter is widely used in the monitoring of blood oxygen in clinic for its convenience and efficiency. However, synchronizing light source flashing with data collecting is required, otherwise the separation of the data from different LEDs will fail. More importantly, synchronous acquisition makes the pulse oximetry system vulnerable. Meanwhile, the pulse waveform extraction is a crucial procedure in the measurement. Hence, in this paper, an asynchronous acquisition pulse oximetry system based on wavelet transform has been built. PhotoPlethysmoGraph (PPG) and photoelectric detection technology are applied in our homemade system. The adaptive soft-threshold de-noising is realized by Stein's Unbiased Risk Estimate (SURE). The principle and system configuration are described. The preliminary experiment results from wavelet transforms and Fourier transforms are compared. The results show that our homemade system is adaptive, accurate, robust and simple.

The triboelectric nanogenerator (TENG) has attracted global attention in the fields of power sources and self-powered sensors. By coupling the omnipresent triboelectrification effect and the electrical induction effect, the TENGs can transduce ambient mechanical energy into electrical energy. Such energy could be consumed instantaneously or stored for later use. In this way, they could be deployed distributedly to be compatible power sources in the era of the internet of things (IoTs), completing the powering structure that is currently relying on power plants. Also, the electrical signals can reflect the environment changes around the TENGs. Thus, the TENGs can serve as self-powered sensors in the IoTs. In this work, we adopted two approaches for TENG fabrication: the thermal drawing method (TDP) and 3D printing. With TDP, we have fabricated scalable fiber-based triboelectric nanogenerators (FTENG), which have been woven into textiles by an industrial loom for wearable use. This fabrication process can supply FTENG on a large scale and fast speed, bridging the gap between the TENG and weaving industry. With 3D printing, we have fabricated TENGs that are compatible with the shape of arbitrary substrates. They have been used as biocompatible sensors: human-skin-compatible TENG has been used to recognize silent speech in real-time by sensing the chin movement; the porcine-kidney-shaped fiber mesh has been used to monitor the perfusion rate of the organ. These works have extended the territory of TENGs and can be critical components in the IoTs. Ph.D. Portable electronic devices have become important components in our daily lives, and we are entering the era of the Internet of Things (IoTs), where everyday objects can be interconnected by the internet. While electricity is essential to all of these devices, the traditional power sources are commonly heavy and bulky and need to be recharged or directly connected to the immobile power plants. Researchers have been working to address this mismatch between the device and power systems. The triboelectric nanogenerators (TENG) are good candidates because they can harvest energy in the ambient environment. The users can use them to generate electricity by merely making the rubbing motion. In this work, we report two fabrication methods of the fiber-based triboelectric nanogenerators (FTENG). With the thermal drawing process, we have fabricated sub-kilometer-long FTENG and wove it with the regular cotton yarn into textiles. The wearable power source is human friendly as it does not induce any extra weight load for the user. Besides, we have demonstrated that such long fibers can work as self-powered distributed sensors, such as a Morse code generator. With 3D printing, we have fabricated FTENG-based devices that conform to the working substrates, which can be any shape. We have employed them as biofriendly sensors to translate the chin movement during speaking to language and to monitor the perfusion rate of a pig kidney. The FTENGs have offered excellent comfortability to the users and can play a vital role in reframing the power structure to be compatible with IoTs.