With the rapid development of software-defined radio (SDR) technology, a digital, software-reconfigurable, and flexible solution is provided for microwave radiometers, particularly suitable for atmospheric water vapor and oxygen detection with wideband, multi-channel requirements, significantly improving system efficiency. Meanwhile, digitization helps improve channel consistency and address nonlinearity issues, while the digital zero-balancing mechanism implemented through adaptive integration is more suitable for digital platforms. This paper proposes a digital Dicke-type radiometer system based on an SDR platform, using Xilinx RFSoC XCZU47DR (AMD, San Jose, CA, USA) as the core hardware to achieve single-chip integration of RF signal sampling, digital local oscillator generation, and signal processing. The system implements a 46-channel channelized receiver (23 channels each for K-band and V-band) on an FPGA using a polyphase filter bank. The prototype filters achieve 70 dB stopband attenuation and 0.5 dB passband ripple, with each polyphase branch requiring only 25 coefficients, significantly reducing hardware resource consumption. An adaptive integration method is proposed, where an adaptive switch controller dynamically adjusts the hot source injection time ratio by calculating the power difference between adjacent integration periods, enabling the Dicke zero-balancing mechanism to operate entirely in the digital domain. Furthermore, a complete hardware transfer model is established for three signal branches (antenna, hot source, and matched load), and full-chain calibration of all 46 channels is performed using a liquid nitrogen cold source, with calibration reliability verified through blackbody measurements. Experimental results demonstrate brightness temperature consistency better than 0.7 K, with a sensitivity of less than 0.15 K for the K-band and less than 0.21 K for the V-band at 1 s integration time.

Ground-based scatterometers are widely used for quantitative microwave backscattering measurements in soil moisture retrieval, vegetation monitoring, and satellite scatterometer validation. However, low-cost software-defined radio (SDR) transceivers provide limited instantaneous bandwidth, making it difficult to transmit and process signals with bandwidths on the order of hundreds of MHz for fine range resolution, especially for systems requiring real-time onboard processing. To address this problem, this paper presents a vehicular, fully polarimetric, SDR-based scatterometer that achieves an equivalent wideband response by sequentially transmitting adjacent narrow subbands and coherently synthesizing them onboard. To enable real-time operation on a resource-limited field-programmable gate array/system-on-chip (FPGA/SoC) platform, we adopt a frequency-domain synthesis-pulse-compression pipeline that avoids interpolation and eliminates repeated matched filtering across subbands. A slot-based online phase calibration is performed within the settling window after each fast lock to estimate and compensate random local oscillator (LO) phase offsets, preserving coherent stitching. In addition, pulse repetition within each subband and coherent accumulation are integrated to improve the signal-to-noise ratio (SNR) under real-time throughput constraints. A Zynq-based implementation demonstrates deterministic onboard range-profile output, with a minimum processing latency of about 1.57 ms per frame. Loopback and outdoor experiments validate the equivalent 200 MHz bandwidth (five 40 MHz subbands), achieving approximately 0.75 m resolution and yielding sidelobe metrics consistent with the designed windowing, including a peak sidelobe ratio (PSLR) of −27.43 dB and an integrated sidelobe ratio (ISLR) of −12.38 dB. Field scans over farmland further show consistent σ0 trends across incidence angle and azimuth, indicating reliable onboard quantitative backscattering measurement. These results demonstrate that the proposed method provides a feasible solution for deterministic real-time equivalent wideband scatterometry on a low-cost SDR platform.

Radio occultation observation has garnered significant attention owing to its low-cost, all-weather, and global coverage feature. However, traditional occultation inversion methods lead to error accumulation due to assumptions that are not entirely suitable in the real ionospheric environment, resulting in poor performance in the low ionosphere (D, E layers). In this article, we propose a new method for inverting the electron density in low ionosphere using high-precision 50 Hz occultation data. This method can eliminate the fixed constant term of 50 Hz data and obtain a sharper weighting function through epoch differencing. The inversion results have a good consistency with the results of the ionosonde, with a correlation coefficient of 0.92 and a determination coefficient of 0.85. In addition, the new method can retrieve local details of electron density profiles and capture sporadic E layer (Es), providing support for the study of Es layer morphology and structure.

The sea surface height (SSH) measured by the satellite radar altimeter is determined by the distance from the satellite to the sea surface and the altitude of the satellite above the reference ellipsoid. The former is measured by altimeter and the latter is determined by precision orbit determination. If the two systems use different clocks, there may be a time tag bias between their time series. This time tag bias reduces the accuracy of SSH measurements by satellite radar altimeter. To solve the problem of time tag bias of the HY-2 altimeter, we conducted nearly 20 in-orbit calibration experiments from November 2021 to September 2022 using a reconstructive transponder, and statistically analysed the effect of time tag bias on the altimeter height measurement. The results of time tag bias of HY-2B is 0.03 ms, that of HY-2C is 0.07 ms, and that of HY-2D is 0.1 ms. As an independent calibration method, the reconstructive transponder can be deployed on land, which makes it unaffected by error sources introduced by sea surface dynamics, resulting in calibration with more accuracy. The altimeter system delay after correcting the time tag bias is also given, which provides a guarantee for the quality of the subsequent data products.

The present work investigates the corrosion behaviour of an AA2024 alloy thin wall structure produced by wire arc additive manufacturing (WAAM) with interpass rolling, focussing on the influence of interpass rolling. It is found that although interpass rolling does not change the typical configuration of thin wall structure, i.e. melt pool zone (MPZ), melt pool border (MPB) and heat-affected zone (HAZ), the plastic deformation introduced by interpass rolling leads to the variation of grain-stored energy across the structure, which consequently results in the highest corrosion susceptibility of MPB due to its relatively high stored energy.

The highly flexible wearable device for human-machine interaction is a burgeoning technology that has garnered considerable attention amongst researchers. However, current wearable devices such as data gloves, wrist bands and exoskeleton devices require additional fixation aids, which interfere with the users’ movements and cause discomfort. Here, a flexible on-skin triboelectric sensor is developed for high-precision human-machine interaction, which is in the form of a thin film containing a soft substrate and two triboelectric layers with mismatched elastic modulus. The on-skin triboelectric sensors can be mounted on the forearm epidermis by its own adhesion, which is rarely perceptible and does not impede hand and wrist mobility. On the basis, the sensors can accurately measure the tiny deformations caused by muscle movement. Meanwhile, a heterogeneous parallel channel fusion (HPCF) model is proposed for advanced signal processing and recognition of sensor data, where varying signal features are extracted by different-sized convolutional kernels. The human-machine interaction system by combining the on-skin triboelectric sensors and algorithm achieves up to 99.12% accuracy when identifying 26 distinct gestures, which holds vast potential in several areas, such as gesture recognition, virtual reality, and teleoperation.

This study is based on the echo data from the Yinchuan vertical ionosonde.The ionosonde supports scanning in the frequency range from 1 to 30 MHz,with a distance resolution of 1.5 km and a reception window ranging from 67.5 km to 560.1 km.It utilizes pulse compression technology and en-codes the transmission signal using Bernoulli mapping sequences,successfully resolving the issue of echo signal mixture with strong clutter interference in practical detection,thus obtaining Ionograms of high quality.In order to extract key information of ionosphere from the ionograms,the signal processing prob-lem is transformed into a semantic segmentation task in computer vision,constructing an original iono-grams dataset,and undergoing preprocessing such as discretization and manual annotation.By training a cGAN neural network to analyze the characteristic parameters of each layer's traces in the ionograms,the goal of segmenting different traces is achieved.The network is suitable for processing various types of ionograms under calm conditions,with an accuracy rate of over 95％,effectively saving time in manual parameter measurement and improving processing efficiency.An improved bottom inversion model of the International Reference Ionosphere and the NeQuick top model is used to invert the electron density pro-file above the ionosonde,while the top calculation results are corrected according to the actual measure-ment data from"CSES-1".By comparing the total electron content calculated with the data results pub-licly available from CDDIS,the accuracy of the ionosonde data is verified.On this basis,combined with the geomagnetic data acquired by the Gaoshaowo magnetometer,the ionosonde successfully observed the entire process of ionospheric anomalies during the geomagnetic storm on 23-24 April,2023,and provid-ed the results of the total electron content changes,offering accurate and reliable observational data for exploring the electromagnetic environment changes in western China.

China’s marine dynamic satellite constellation was formed in 2021 with the launch of HY-2D, with existing HY-2C and HY-2B. The SSH (Sea Surace Height) calibration by tide-gauges, buoys as well as range calibration utilizing transponders have been performed extensively. In order to correlate the SSH and range calibration in one experiment, search the association between the two biases, furtherly, to compile the range bias obtained by transponders into the altimeters data products, a novel calibration method was developed utilizing a coastal transponder. In the new method, the altimeter works at normal SSH tracking mode, and the transponder captures the pulses instantaneously, transmits them back entering the altimeters receiving windows. From the altimeter spectra, the correlation between the SSH and the transponder echoes are achieved, and the two biases could be validated. In this paper, all the China’s coastal tracks of HY-2B/C/D were examined, and four sites were selected. In March and August in 2023, two calibration missions were carried out. Besides the range bias, the SSH validation was analyzed for the first time. The new method shows potentials in combing the transponder and the sea surface methods. At present, some new calibration techniques based on the signal-rebuilt transponder are in research, involving the fully-focused SAR processing and the absolute measurements of ranges and the instrument resolutions. These new methods are expected to serve for the next advanced altimeters which would be launched in a few years.

Demodulation and decoding are pivotal for the eLoran system’s timing and information transmission capabilities. This paper proposes a novel demodulation algorithm leveraging a multiclass support vector machine (MSVM) for pulse position modulation (PPM) of eLoran signals. Firstly, the existing demodulation method based on envelope phase detection (EPD) technology is reviewed, highlighting its limitations. Secondly, a detailed exposition of the MSVM algorithm is presented, demonstrating its theoretical foundations and comparative advantages over the traditional method and several other methods proposed in this study. Subsequently, through comprehensive experiments, the algorithm parameters are optimized, and the parallel comparison of different demodulation methods is carried out in various complex environments. The test results show that the MSVM algorithm is significantly superior to traditional methods and other kinds of machine learning algorithms in demodulation accuracy and stability, particularly in high-noise and -interference scenarios. This innovative algorithm not only broadens the design approach for eLoran receivers but also fully meets the high-precision timing service requirements of the eLoran system.

HY-2C (Haiyang) and HY-2D were launched on 21 September 2020 and 19 May 2021 separately, which form China’s marine dynamic satellite constellation program with HY-2B, launched on October 25, 2018. The calibration mission for HY-2B altimeter was carried out in 2019, and a precision of less than 1 cm was achieved. For further validation, a comparison between HY-2B and Jasons was performed in SSH (Sea Surface Height). To obtain consistent and comparable calibration results, a mobile transponder was utilized in different sites for HY-2B/C/D altimeters. Two experiment missions were carried out in 2021 and 2022 separately, each for a month. The result shows the range calibration precision for HY-2B/C/D is less than 4 cm, and USO (Ultra Stable Oscillator) drift on board is very small and negligible compared with HY-2A. Further, the range bias correction of the altimeter instrument is defined and will be compiled into the L1 data to improve the quality of L2 data product. In March this year, a novel calibration method is developed on offshore, with the altimeter switched to ocean calibration mode. This paper gives a detailed description of the multi-calibration of HY-2B/C/D altimeter using a mobile transponder. The results are validated with the ocean mode calibration, which shows a high consistency. In the following mission, the mobile transponder will be installed offshore on the altimeter ground track permanently, performing regular range and sigma zero calibration.

Achieving high sensitivity of stretchable electronics with a wide working range is essential and challenging. While fundamental strategies using topographic design or introducing microstructures (e.g., wrinkles or cracks) can effectively improve the sensitivity, the strain-response range is still rather limited. Here, we propose a tunable and ultrasensitive piezoresistive strain sensor by leveraging a controllable kirigami design and a prestrained strategy. On the one hand, the kirigami structure enhances the sensitivity and structural stability. On the other hand, the prestrained strategy widens the surface crack to generate highly sensitive and continuous linear responses. This strategy allows general stretchable materials to versatilely realize strain sensors with ultrahigh sensitivity (GF > 1000) and good linearity in the low strain range. As a result, the increased sensitivity and conformability to soft surfaces enable the prestrained strain sensor to identify different body motions and hand grips of varying loads. The high amplitude and recognizable signal waveforms provide essential information in muscle strength assessment. With its general applicability to diverse soft materials, this prestrained strategy overcomes the material and manufactural-level limitations for imparting high sensitivity to various strain sensors, presenting a great potential in the fields of medical monitoring and rehabilitation.

Collecting electrophysiological (EP) signals (e.g., electrocardiogram (ECG), electromyogram (EMG)) during exercises is crucial for feedback of cardiac health and muscle injuries. However, since several interferences exist in the skin interface (e.g., deformation, perspiration, and motion artifacts), commercial rigid electrodes/systems have difficulty in recording high-fidelity EP signals. Here, a wireless Nepenthes -inspired hydrogel (NIH) hybrid system is developed for high-quality EP signal detection by establishing seamless-integrated and rapidly directional sweat-wicking device/skin interfaces during exercises. The adhesive strength of poly(vinyl alcohol)/poly(acrylic acid) (PVA/PAAC)-based double-network hydrogels is significantly increased by more than sixfolds. Nepenthes -inspired microstructures are further fabricated on hydrogels to enhance the directional transport speed of droplets by 4.5 times. Notably, the NIH electrodes can maintain an intimate coupling with the skin during continuous artificial sweat injection while showing the lowest impedance and highest signal-to-noise ratio (>19 dB) of EMG signals under complex conditions (i.e., vibration and perspiration). Finally, the NIH hybrid system is fabricated by decorating silicone joints and hollow structures to avoid stress concentration. This system can record high-quality ECG waveforms and heart rate curves with relative deviations of <2.6% during exercises and rest. This NIH hybrid system represents a promising platform for precise EP signal monitoring in exercising scenarios.

High power&short millimeter wavelength pulse gyrotron oscillators usually use high-order cavity modes as their operating modes. Quasi-optical mode converters play an important role in the high-efficiency output of high-power gyrotron oscillators. A quasi-optical mode converter designed for 140 GHz/TE28,8 mode gyrotron oscillator includes a Denisov-type launcher and three quasi-optical mirrors. By using the self-developed $\text{TE}_{28,8}$ mode generator, a cold test experiment on the conversion performance of the quasi-optical mode converter was carried out. The experimental results show consistency with the design, which can be used as a design and verification method for engineering application of quasi-optical mode converters.

The core of eLoran ground-based timing navigation systems is the accurate measurement of groundwave propagation delay. However, meteorological changes will disturb the conductive characteristic factors along the groundwave propagation path, especially for a complex terrestrial propagation environment, and may even lead to microsecond-level propagation delay fluctuation, seriously affecting the timing accuracy of the system. Aiming at this problem, this paper proposes a propagation delay prediction model based on a Back-Propagation neural network (BPNN) for a complex meteorological environment, which realizes the function of directly mapping propagation delay fluctuation through meteorological factors. First, the theoretical influence of meteorological factors on each component of propagation delay is analyzed based on calculation parameters. Then, through the correlation analysis of the measured data, the complex relationship between the seven main meteorological factors and the propagation delay, as well as their regional differences, are demonstrated. Finally, a BPNN prediction model considering regional changes of multiple meteorological factors is proposed, and the validity of the model is verified by long-term collected data. Experimental results show that the proposed model can effectively predict the propagation delay fluctuation in the next few days, and its overall performance is significantly improved compared with that of the existing linear model and simple neural network model.

Recent advances in flexible wearable devices have boosted the remarkable development of devices for human-machine interfaces, which are of great value to emerging cybernetics, robotics, and Metaverse systems. However, the effectiveness of existing approaches is limited by the quality of sensor data and classification models with high computational costs. Here, a novel gesture recognition system with triboelectric smart wristbands and an adaptive accelerated learning (AAL) model is proposed. The sensor array is well deployed according to the wrist anatomy and retrieves hand motions from a distance, exhibiting highly sensitive and high-quality sensing capabilities beyond existing methods. Importantly, the anatomical design leads to the close correspondence between the actions of dominant muscle/tendon groups and gestures, and the resulting distinctive features in sensor signals are very valuable for differentiating gestures with data from 7 sensors. The AAL model realizes a 97.56% identification accuracy in training 21 classes with only one-third operands of the original neural network. The applications of the system are further exploited in real-time somatosensory teleoperations with a low latency of <1 s, revealing a new possibility for endowing cyber-human interactions with disruptive innovation and immersive experience.

Severe soft tissue defects and amputated digits are clinically common injuries. Primary treatments include surgical free flap transfer and digit replantation, but these can fail because of vascular compromise. Postoperative monitoring is therefore crucial for timely detection of vessel obstruction and survival of replanted digits and free flaps. However, current postoperative clinical monitoring methods are labor intensive and highly dependent on the experience of nurses and surgeons. Here, we developed on-skin biosensors for noninvasive and wireless postoperative monitoring based on pulse oximetry. The on-skin biosensor was made of polydimethylsiloxane with gradient cross-linking to create a self-adhesive and mechanically robust substrate that interfaces with skin. The substrate was shown to exhibit appropriate adhesion on one side for both high-fidelity measurements of the sensor and low risk of peeling injury to delicate tissues. The other side demonstrated mechanical integrity to facilitate flexible hybrid integration of the sensor. Validation studies using a model of vascular obstruction in rats demonstrated the effectiveness of the sensor in vivo. Clinical studies indicated that the on-skin biosensor was accurate and more responsive than current clinical monitoring methods in identifying microvascular conditions. Comparisons with existing monitoring techniques, including laser Doppler flowmetry and micro-lightguide spectrophotometry, further verified the sensor's accuracy and ability to identify both arterial and venous insufficiency. These findings suggest that this on-skin biosensor may improve postoperative outcomes in free flap and replanted digit surgeries by providing sensitive and unbiased data directly from the surgical site that can be remotely monitored.

In the above article [1], comparing (14) and (15) with (1), for all units of the NP ML-SWS to satisfy the BWS condition, the simplest way is to define the relationship between $L_{n}$ and $d_{n}$ as (16). Such that (16) should read as

A beam–wave resynchronization (BWRS) method is proposed by changing the structural parameters of the nonperiodic (NP) slow wave structure (SWS) to reduce the phase velocity of the wave for traveling-wave tubes (TWT) application. The mathematical model and analysis for the BWRS method are introduced to investigate what condition the NP meander line SWS (ML-SWS) and the NP folded-waveguide SWS (FW-SWS) should satisfy so that the corresponding TWT can have a good output performance. As the applications, the NP zigzag ML-SWS and the concentric arc FW-SWS are designed according to the method, which is also compared with that designed according to the phase velocity synchronization (PVS). The simulated results show that, by using the BWRS method, the max output power (efficiency) of the zigzag ML-SWS TWT can be improved from 56.7 (18.9%) to 76.26 W (25.4%), and the bandwidth can be expanded from 6 to 10 GHz in the Ka-band. Furthermore, the max output power (efficiency) of the concentric arc FW-SWS TWT can be improved from 199 (27.6%) to 237 W (32.9%), and the bandwidth can be expanded more than twice in the W-band as before. These results indicate that the BWRS method is beneficial for the improvement of the output power and electron efficiency and may be beneficial for wider bandwidth.

Currently, eLoran is the ideal backup and supplement for global navigation satellite systems. The time synchronization accuracy between stations in the eLoran system has improved, providing conditions for eLoran pseudorange positioning. The pseudorange positioning of eLoran is a nonlinear least-squares problem and the location of the eLoran transmitting stations may cause the above problem to be non-convex. This makes the conventional pseudorange positioning al-gorithm strongly depend on the initial value when solving the eLoran pseudorange positioning. We propose a shrink-branch-bound (SBB) algorithm to solve the eLoran pseudorange positioning initialization problem. The algorithm first uses a shrink method to reduce the search space of the position estimator. Then, optimization is performed using a branch and bound algorithm within the shrunk region, where a trust region reflective algorithm is used for the lower bound process. The algorithm can help the receiver to complete the initial positioning without any initial value information. Simulation experiments verify that the algorithm has a success rate of more than 99.5% in solving the initialization problem of eLoran pseudorange positioning, and can be used as an initialization algorithm for pseudorange positioning problems for eLoran or other long-range terrestrial-based radio navigation system.

On‐skin electronics have been widely used in fields, such as wearable healthcare and human–machine interfaces due to their excellent performances and wearable comfort. Among them, on‐skin sensors for collecting signals have been greatly developed, while the stimulators that provide tactile feedback are difficult to achieve in terms of flexibility and stretchability due to their rather complicated structures. Achieving on‐skin stimulators with superior performances and outstanding wearability requires major advances in materials, fabrication, and structure design. The on‐skin stimulator needs to be soft with a lightweight and thin structure so that it can be laminated onto the skin with conformal contact for accurate feedback. Three stimulation modes, namely electrotactile, thermal, mechanotactile, and vibrotactile stimulation, are investigated. Among them, electrotactile stimulation is the characteristics of high resolution and quick response. Thermal stimulation can provide a unique heat sensation without crosstalk with other stimuli. Mechanotactile and vibrotactile stimulation can bring comfortable feedback to skin, showing great potential in wearable applications. This paper summarizes the working principles, materials, structures, and applications of these on‐skin stimulators, and compares their advantages with conventional rigid devices. At the end of this paper, the challenging issues and future prospects in this field are discussed.