5681 results about "Wideband" patented technology

The invention provides a directional energy multi-target interference system based on an ultra-wideband phased array technology, and the system integrates signal perception, target recognition, interference signal generation and phased array control, so as to achieve the precise interference of an unmanned aerial vehicle cluster. The signal sensing module scans an airspace target through the ultra-wideband phased-array antenna array and obtains spectrum characteristics of a target signal. The target identification module analyzes signal features, identifies an individual target and predicts a motion track and a communication protocol of the individual target. And the phased array control module calculates and adjusts antenna beam forming parameters, and dynamically controls the radiation direction, phase and transmitting power of the antenna. The interference signal generation module generates a matched interference waveform based on the target communication protocol and the trajectory information. The ultra-wideband phased-array antenna array adopts a digital beam forming technology. According to the invention, efficient and accurate directional energy interference can be realized under multiple frequency bands, the confrontation capability of the unmanned aerial vehicle cluster is improved, and the method is suitable for defense tasks in electronic warfare and complex electromagnetic environments.

The invention discloses a wide-narrow integrated ad hoc network method, and belongs to the technical field of network communication. The method comprises the following steps: a network node generates dynamic topology information based on a narrow-band communication module periodic broadcast state beacon; according to the link quality and the node load in the topological information, coordinating the resource allocation of broadband and narrowband channels by adopting a load-aware time slot allocation algorithm; data are classified according to service types, broadband data are modulated and transmitted by adopting orthogonal frequency division multiplexing, and narrowband control instructions are modulated and transmitted by adopting differential phase shift keying; when the link quality is deteriorated, the link is switched, and the transmitting power and the frequency band parameters are dynamically adjusted; and adaptive switching and data distribution of wide and narrow band communication modes are realized. According to the method, the problems of difficulty in topology maintenance and low bandwidth and narrowband resource allocation efficiency in a high-dynamic network scene are solved, the network adaptability, the anti-interference capability and the resource utilization rate are remarkably improved through a dynamic cooperative bandwidth and narrowband communication mode, and meanwhile, the protocol switching overhead and energy consumption are reduced.

The invention discloses an ultra-wideband laser radar inertial navigation cooperative SLAM (Simultaneous Localization and Mapping) method and system, which are suitable for robot positioning and mapping tasks in a GPS (Global Positioning System)-free environment. According to the method, high-frequency motion priori of an IMU, relative pose constraint of LiDAR and absolute ranging information of UWB are fused, a unified factor graph optimization model is constructed, and multi-sensor cooperative positioning is realized; in the system initialization stage, IMU bias calibration, UWB base station coordinate configuration and LiDAR initial attitude estimation are completed; in the operation process, IMU pre-integration is utilized to predict the pose, LiDAR point cloud registration is utilized to obtain the relative motion between key frames, UWB ranging is combined to construct a residual item, a self-adaptive weight mechanism is introduced to suppress ranging abnormity, and the fusion robustness is improved; the system supports geometric feature loopback detection, cross-frame constraints are constructed in combination with UWB to carry out closed-loop optimization, and an optimization result is used for real-time incremental updating of a global map; the method has the advantages of high positioning precision, strong anti-interference capability, wide application scene and the like.

The invention relates to the technical field of 5G networks, in particular to a 5G network intelligent optimization method and system, and the method comprises the steps: obtaining 5G network signal data, recognizing an abnormal power spectral density region, carrying out the filtering extraction of the abnormal power spectral density region, and separating interference signals, interference types including narrowband interference, broadband interference and directional interference; extracting features from the obtained interference signals, and performing interference type identification according to a random forest algorithm; starting a corresponding anti-interference means according to the interference type, and generating operation state data in real time; a bee colony algorithm is adopted to simulate bee behaviors for iterative search, and a local optimal resource scheduling strategy is determined; and executing the resource scheduling strategy, feeding back an execution effect, and restarting the bee colony algorithm to determine a new resource scheduling strategy if the execution effect does not reach a set expectation. Therefore, the problems of lack of dynamic adaptive adjustment, single anti-interference means, lack of cross-base station collaboration and the like in the anti-interference aspect in the prior art are solved.

The invention provides a multi-platform cooperative unmanned inspection task planning method and system for a wind power scene, and relates to the technical field of wind power plant inspection, and the method comprises the steps: based on a wind power plant three-dimensional scene model, adaptively dividing an inspection region, constructing a reachability path network, calculating an inspection difficulty coefficient according to target detection point information, and calculating a target inspection point; and generating an unmanned aerial vehicle and unmanned vehicle inspection area. A sensor is deployed to collect environment and equipment state data, feature vectors are extracted to establish an inspection constraint model, and main and branch inspection paths are planned on the reachability path network. And performing multi-platform relative positioning by using ultra-wideband radio waves, and dynamically optimizing an inspection path according to the equipment health score and the inspection constraint model. Through multi-platform cooperation, adaptive path planning and intelligent state identification, the wind power plant inspection efficiency and accuracy are improved, and the inspection cost is reduced.

Techniques pertaining to techniques for physical downlink shared channel (PDSCH) allocation in subband full duplex (SBFD) networks are described. Such techniques pertain to both PDSCH frequency domain resource allocation (FDRA) Type-0 and / or FDRA Type-1 and include the use of fractional resource block groups (RBGs), virtual resource block (VRB)-interleaving, canceling one or more repetitions or SPS transmission in a slot that is an SBFD slot or a non-SBFD slot. The techniques further include VRB-to-physical resource block (PRB) mapping that excludes one or more PRBs in the sequence of PRBs that belong to one or more UL-subband or one or more guard bands and applying one or more rules to provide for the selection of a wideband setting for a precoder resource block (RB) group (PRG) size with respect to use of a physical downlink shared channel (PDSCH) demodulation reference signal (DMRS).

The invention discloses a thiapyran molecule modified solar cell and a preparation method thereof. The cell sequentially comprises an ITO (Indium Tin Oxide) conductive glass layer, a 4-aminotetrahydro-2H-thiapyran-1, 1-dioxide hydrochloride modified [4-(3, 6-dimethoxy-9H-carbazole-9-yl) butyl] phosphonic acid hole transport layer, a Cs0.05 (FA < 0.77 > MA < 0.23 >) < 0.95 > Pb < (I < 0.77 > Br < 0.23 >) 3 wide-band gap perovskite thin film, a phenethyl ammonium iodide passivation layer, an electron transport layer of [6, 6]-phenyl-C61-butyric acid isomethyl ester, a 2, 9-dimethyl-4, 6, 7-tetrahydro-2H-thiapyran-1, 1-dioxide hydrochloride modified [4-(3, 6-dimethoxy-9H-carbazole-9-yl) butyl] the hole barrier layer is made of 1, 7-biphenyl-1, 10-phenanthroline; the electrode layer is made of metal Ag; according to the scheme, the hole transport layer is modified through thiapyran molecules, agglomeration of the hole transport layer is relieved, and a more compact and more uniform self-assembled single layer is generated by inducing favorable crystal orientation. A good bottom interface is obtained based on thiapyran molecule modification, and ordered growth of high-quality perovskite crystal grains is promoted. In addition, the energy level of the hole transport layer is effectively adjusted through thiapyran molecule treatment, and the extraction and transmission of carriers by the hole transport layer are enhanced.

The invention discloses a graph optimization-based UWB / IMU / GNSS multi-unmanned vehicle cooperative positioning method, which comprises a global satellite navigation system GNSS, an ultra wide band (UWB) system, an inertial measurement unit IMU and a robot motion control system, and is characterized in that the UWB system comprises a UWB label and three UWB base stations, the UWB label is deployed on a target unmanned vehicle to be positioned, and the UWB label is deployed on the target unmanned vehicle to be positioned; and the three UWB base stations are respectively arranged on the other three unmanned vehicles as mobile base station unmanned vehicles. The GNSS module and the IMU module are deployed on the unmanned vehicle to serve as a movable UWB base station, and GNSS absolute position information and IMU relative motion information are fused by adopting an extended Kalman filtering algorithm; and according to the determined position of the unmanned vehicle in the movable base station, a distance observation value between the label and the base station is obtained based on a single-side bidirectional distance measurement method, a factor graph model fusing UWB distance measurement constraint and IMU motion constraint is constructed, and a factor graph optimization algorithm is adopted to optimize the position of the target unmanned vehicle. According to the method, the cost of a traditional fixed base station is reduced through the deployment of a mobile base station unmanned vehicle, and the precision and robustness of UWB system positioning in a complex environment are improved in combination with a multi-source sensor data fusion strategy.

Technologies directed to using at least three antennas and Ultra-Wideband (UWB) protocols are described. One method includes sending a first signal to a second wireless device with data that cause it to send a second signal at a plurality of times. The method receives copies of the second signal at a first time via a first pair of antennas and copies of the second signal at a second time via a second pair of antennas. The method determines first and second angle-of-arrival (AoA) values from the copies of the second signals at the first and second times, respectively. The method determines location information of the second wireless device, the location information including an identifier corresponding to a first field of view (FOV) corresponding to the first pair or a second FOV corresponding to the second pair and at least one of the first AoA value or the second AoA value.

The invention discloses a wiring harness dynamic load and electromagnetic interference coupling test method, and relates to the technical field of wiring harness testing, and the method comprises the steps: S1, defining a plurality of environment parameter groups, and constructing a test platform; s2, dynamic current pulse and multi-axis vibration excitation are synchronously loaded; s3, applying broadband electromagnetic interference signals and monitoring signal crosstalk amplitude and bit error rate changes; s4, the sensor nodes are dynamically configured according to the topological structure of the wire harness; s5, generating a feature vector; s6, outputting a wire harness performance index; s7, outputting a wire harness fault probability prediction value; s8, obtaining prediction data; s9, triggering a high-speed data recording mode, and storing original sensor data 60 seconds before the fault; and dynamically adjusting the gradient step length and the loading sequence in the environment parameter group. Performance evaluation, fault prediction and service life management can be carried out on the wire harness under complex working conditions, and the reliability and safety of an automobile electrical system are improved.

The invention relates to the technical field of road surface detection, in particular to a road surface skid resistance detection system based on multi-feature fusion, which comprises the following steps: applying broadband sweep frequency excitation by using a frequency modulation vibration sensor, matching with the inherent frequency of road surface texture to generate local resonance, and collecting the temperature, humidity and rainfall of a road surface in real time; performing fast Fourier transform on the collected vibration signals to obtain a resonance response spectrum, extracting key parameters through Gaussian fitting, and fusing frequency domain, material and environment data to form a comprehensive feature set; the frequency domain features are converted into three-dimensional energy distribution of pavement microtextures, the actual contact area ratio is calculated according to the three-dimensional energy distribution, an environment temperature and humidity compensation factor is introduced, and a dynamic friction attenuation coefficient is calculated; and comparing the calculated dynamic friction attenuation coefficient with a third-level safety threshold, and outputting a corresponding anti-skid performance level. Multi-source data fusion enables a detection result to be more fit with an actual driving scene, and misjudgment caused by single data is avoided.

The invention relates to the technical field of electrical performance testing, in particular to a water supply equipment electrical performance detection system based on artificial intelligence, which comprises an electrical parameter acquisition module, an energy efficiency analysis module, an insulation performance evaluation module and a comprehensive diagnosis module. According to the invention, a three-phase voltage and current root-mean-square value is dynamically calculated through a broadband current transformer and a sliding window integration method, a 50Hz fundamental component amplitude is extracted to separate power frequency and high frequency harmonic waves, a continuous period energy efficiency ratio standard deviation triggers an insulation detection threshold value, and a parameter fluctuation and insulation degradation response mechanism is established. Harmonic interference correction synchronous processing energy efficiency ratio and leakage current integration, the detection error being lower than 5%, temperature rise rate linear regression and bearing current threshold value cooperative determination, winding aging cross validation, fault misjudgment rate reduction to 26%, closed-loop detection fusion transient capture, dynamic threshold value triggering and multi-parameter diagnosis, early warning success rate reaching 92%, and positioning response being reduced to 3 seconds.

A passivity-based dual-mode integrated control method for a grid-connected inverter (GCI) is provided. In view of the insufficient robustness of the conventional single-mode GCI in a high-impedance and low-inertia weak grid, and the problem of wideband oscillation of the grid voltage and grid current or even system instability in nonlinear application scenarios such as grid structure / parameter variation, and plug-and-play of the inverter, the dual-mode integrated control method performs modeling on the GCI based on a port-controlled Hamiltonian (PCH) model, thereby obtaining integrated control with a weighted passivity-based feedback control law for the GCI based on a grid-following (GFL) mode and a grid-forming (GFM) mode. Based on the dual-mode integrated control method, the stable operation of the GCI in severe grid conditions with large fluctuation of the impedance, and desirable robustness of the GCI in nonlinear working scenarios can be ensured.

The invention relates to the cross technical field of atmospheric science and communication technology, in particular to an atmospheric refraction and waveguide environmental parameter detection and prediction method and device, and the method comprises the following steps: carrying out the power distribution of a light beam of a broadband light source through employing a light splitting element based on the emission of the broadband light source, and forming a detection light beam and a reference light beam, and guiding the detection light beam to pass through a preset open atmosphere optical path, and guiding the reference light beam to pass through a known refractive index stabilizing medium or a vacuum pipeline. The detection light beam and the reference light beam are formed through light splitting of the broadband light source, the detection light beam penetrates through the open atmosphere path, the reference light beam passes through the stable medium, Fourier transform is carried out on interference signals of the two light beams to extract wavelength phase difference mapping data, and tiny optical path change caused by atmospheric refractive index disturbance can be captured. Compared with the traditional single-point or single-path measurement, the sensing sensitivity and the measurement dimension of the atmospheric refractive index spatial nonuniformity are improved by using the broadband spectral information.

The invention discloses a radio interference identification method based on electromagnetic spectrum monitoring, and the method comprises the following steps: S1, collecting spectrum data in an electromagnetic environment through broadband spectrum monitoring equipment, and carrying out the digital sampling processing; s2, adopting a diffusion probability model to automatically remove environmental noise and non-interference signals; s3, automatically generating an expansion data set of edge and small sample interference signals by adopting an attention-enhanced data synthesis expansion technology; s4, extracting multi-dimensional time-frequency domain dynamic correlation characteristics of the spectrum interference signal based on a Transform structure; s5, adopting an attention enhancement self-supervision algorithm to generate a self-supervision soft label of an unknown interference type; s6, dynamic back diffusion iteration is carried out through the diffusion probability model, and an interference classification result is obtained; and S7, constructing a closed-loop dynamic feedback mechanism by using an interference classification result. According to the invention, accurate identification of radio interference signals is realized, and the accuracy, dynamic adaptability and automation degree of interference signal classification are improved.

The invention discloses an integrated machine room operation and maintenance management system, which relates to the field of information technology management and comprises a plurality of modules such as a distributed data acquisition module, a heterogeneous equipment adaptation module and a standardized communication interface module. The system realizes module cooperation through a two-way synchronous lock mechanism and an intelligent load sensing mechanism; the distributed acquisition module realizes millisecond-level high-precision data synchronization by using an ultra wide band and millimeter wave combined sensing technology; the heterogeneous equipment module eliminates communication compatibility obstacles; the standardized communication module is fused with an optical fiber and a dynamic arbitration mechanism to realize microsecond-level low-delay communication; the resource virtualization module supports unified abstraction and low-delay scheduling of physical resources; the expansion module can complete new node integration within three seconds; the fault-tolerant module can early warn faults ten minutes in advance and realize quick recovery; the intelligent decision-making module optimizes an operation and maintenance strategy based on edge reinforcement learning; and the interaction module supports multi-terminal state reproduction and programming control. The method has the beneficial effects that automation, intelligence and reliability levels of machine room operation and maintenance are improved.

The invention provides an unmanned aerial vehicle fusion positioning method based on four-anchor-point UWB pose dynamic quality evaluation, and the method comprises the following steps: defining an unmanned aerial vehicle coordinate system and a world coordinate system, and selecting a first frame point cloud coordinate system of a laser radar as the world coordinate system; defining a state transition model required by front-end state estimation; obtaining a front-end laser radar-inertial odometer factor by using an iterative Kalman filter; based on the four-anchor-point ultra wide band, the accurate unmanned aerial vehicle position and attitude are obtained to serve as ultra wide band factors; based on the obtained ultra-wideband factor, judging the position and attitude quality of the ultra-wideband factor, and determining whether the ultra-wideband factor participates in factor graph optimization or not by adopting an event triggering mechanism; and factor graph optimization is used to obtain the accurate position and attitude of the unmanned aerial vehicle after optimization. And the calculation burden of an airborne computer of the unmanned aerial vehicle is reduced, and the accurate unmanned aerial vehicle position and attitude obtained by combining the four-anchor-point ultra wide band are combined, so that the unmanned aerial vehicle real-time positioning with higher precision and lower calculation burden is realized.

The invention discloses an intelligent identification and grading early warning method based on mine production abnormity, and a system and equipment thereof. The method comprises the following steps: obtaining space-time evolution data, earth surface deformation data and environment monitoring data of rock mass stress in a target area; performing abnormal mode detection on the data by using a space-time convolutional network to obtain accident risk probability distribution data; using an ultra wide band positioning system to track the movement track of the person entering the target area in real time to obtain the movement track data of the person; and constructing a three-dimensional early warning index system in combination with the accident risk probability distribution data in the target area and a dynamic early warning mechanism, performing dynamic early warning grading on different positions in the target area by using the three-dimensional early warning index system, and generating a grading response strategy matched with the personnel activity trajectory data. According to the invention, the problems of incapability of tracking a personnel movement track in real time and low timeliness of mine production abnormity early warning are solved.

The present invention discloses a neural network accelerated simulation method for the radar scattering field of a wide-band target group, belonging to the technical field of electromagnetic simulation. The method of the present invention constructs a KAN neural network model at the central frequency of the wide band, and constructs KAN neural network models at other target frequencies through transfer learning or direct training; uses the trained KAN neural network model to generate a multi-frequency point numerical Green's function data set, and then constructs a wide-band training sample to train the multi-task learning model to realize the global prediction of the numerical Green's function of the entire target wide band; uses the numerical Green's function output by the multi-task learning model to realize the fast simulation of the scattering field of the wide-band target group. The method of the present invention can realize the fast and accurate simulation of the radar scattering field of the wide-band target group.

The invention discloses a mining equipment positioning system and method based on radar, ultra wide band and inertial navigation, and the system is characterized in that a multi-source sensor unit, a data synchronization and collection module and a preprocessing module are connected in sequence, and a state fusion module is connected with the preprocessing module, a UWB ranging error compensation module, a radar motion estimation module and a pose output module; the upper computer is connected with the pose output module; the method comprises the steps of collecting multi-source data; timestamp alignment and format conversion processing are carried out, and feature and speed constraint information extraction is carried out on the point cloud data; fitting correction is carried out on the ranging data by adopting a weighted least square method, and position information is obtained through an error weighted average algorithm; feature matching is carried out, and in combination with a KISS-ICP point cloud registration method, a speed estimation result is obtained; carrying out data fusion, and obtaining a pose estimation result by adopting an extended Kalman filtering algorithm; and outputting equipment position and attitude information. According to the invention, high-precision real-time estimation of the attitude and position information of the mining equipment can be realized.

A horizontally polarized omnidirectional multi-band antenna structure includes a substrate and two structurally-symmetric radiators, each being provided on a layout area on one of the two opposite sides of the substrate, and including a X-shaped primary microstrip line, four secondary microstrip lines, four primary stubs, four secondary stubs and four resonators. The primary microstrip line has four end points arranged with the secondary microstrip lines along different extending directions. The primary stubs extend along different directions from four sections of the primary microstrip line. Each secondary microstrip line is provided with one of the secondary stubs. Resonators are provided between four end points of the primary microstrip line and the primary stubs. The antenna structure supports WiFi 6E / WiFi 7 frequency bands including the 2 GHz, 5 GHz and 6 GHz bands, has characteristics of horizontal polarization and omnidirectionality, and effectively satisfies the needs for miniaturized multi-band and wide band antennas.

The invention discloses an energy storage battery thermal runaway damage diffusion early warning method based on a dynamic thermal model, and relates to the technical field of battery safety monitoring, and the early warning method comprises the specific steps: multi-source parameter collection: arranging a plurality of sensors to collect data, and preprocessing and storing the data; thermal stress modeling is conducted, units are divided through a finite element method to calculate thermal stress, and structural damage is judged in combination with a damage threshold value; multi-physics field cooperative calibration is carried out, and characteristic quantity is acquired and substituted into a formula to correct thermal stress; dynamic thermal model construction: introducing thermal stress influence to construct a model containing a damage diffusion term; thermal runaway early warning judgment is carried out, a multi-dimensional index system is constructed, a risk value is calculated, and early warning is triggered; through a multi-source parameter acquisition technology, in combination with temperature, current, voltage, ultrasonic wave and broadband impedance multi-dimensional sensor data, and assisted by external condition monitoring of environment temperature and humidity, heat dissipation system flow and rotation speed, comprehensive perception of the working state of the battery is realized, and richness and accuracy of data acquisition are improved.

The invention discloses a broadband oscillation identification method and system based on a multi-band Nyquist criterion, and the method comprises the steps: dividing the frequency of broadband oscillation into a low frequency band, a middle frequency band and a high frequency band with overlapped frequency bands, and obtaining the oscillation signals of a monitoring node in a power grid in different frequency bands; respectively calculating the equivalent impedance of the non-overlapped frequency band of each frequency band and the equivalent impedance of the overlapped frequency band in the two adjacent frequency bands so as to construct the equivalent impedance of the low frequency band, the middle frequency band and the high frequency band with the overlapped frequency bands; establishing a Nyquist criterion of each frequency band based on a transfer function of dynamic characteristics of each frequency band in an open-loop state of the system; a generalized Nyquist criterion of the overlapped frequency bands is constructed by using the multi-frequency-band coupling matrix; constructing a comprehensive decision function according to the recognition result of the generalized Nyquist criterion on the system stability, the broadband oscillation comprehensive characteristic quantity and the change rate of the high-frequency-band impedance module value along with the frequency; and according to the value of the comprehensive decision function and a threshold value, a broadband oscillation identification result is determined, and the broadband oscillation identification capability is improved.

The technology described herein is directed towards modular metasurfaces arranged with unit cells for narrowband, wideband and / or multiband sound absorption, in which the unit cells are based on Helmholtz resonators that are deployed in a server rack, proximate to a server, without substantially obstructing airflow from the server fan(s). Each sound absorbing unit-cells is designed and constructed based on a specific resonance frequency, and includes a neck portion and air chamber dimensioned to resonate at the desired resonance frequency and thereby inverse phase cancel corresponding narrowband frequencies of incoming sound waves. Differently-dimensioned unit cells can be built into a single metasurface module, thereby facilitating wideband and / or multiband sound absorption with that metasurface. The modular metasurfaces can be attached to the sidewalls of a server rack, or positioned in otherwise empty slots above and below a server, optionally coupled to blanking panels for covering the openings of those slots.

The invention discloses a noise monitoring analysis and fault early warning method and system for a large transformer, and relates to the technical field of noise monitoring, and the method comprises the following steps: collecting and preprocessing a coverage broadband noise signal through a sensor; a CNN-LSTM model is established for the collected noise signals through a deep learning module; and setting an early warning threshold value, performing judgment through the CNN-LSTM model, and triggering an early warning signal. According to the invention, key features can be automatically extracted from transformer noise, real-time analysis is carried out through the deep learning model, multiple fault types can be rapidly identified without manual intervention, early warning can be timely given out, power failure accidents caused by faults are reduced, the stability of power supply is improved, intelligent upgrading of a power equipment monitoring technology is promoted, and the power supply efficiency is improved. And a key technical support is provided for digital and intelligent transformation of the power industry.

The invention relates to the technical field of combustion equipment state monitoring, in particular to a combustion state monitoring method and system based on vibration and noise fusion analysis, and the method comprises the steps: collecting a combustion signal in real time through a vibration sensor and a broadband noise sensor, extracting a characteristic frequency band through noise reduction and filtering, and obtaining a combustion state; fPGA hardware-level clock synchronization is adopted to realize time alignment of bimodal signals, a vibration-noise joint feature matrix is constructed and multidimensional coupling is carried out, a combustion state feature vector is generated through a mixed deep learning model, a combustion state is determined based on a bimodal confidence weighting decision, and a linkage control instruction is generated during interruption. The system comprises a signal acquisition synchronization unit, a feature fusion and modeling unit, a state decision and instruction generation unit and a safety linkage execution unit, executes a method and activates a standby safety system, solves the problems of asynchronous bimodal data and insufficient monitoring precision, and improves the combustion state monitoring accuracy and safety response efficiency.

The invention provides a broadband low-noise amplifier based on a three-coil coupling transformer. The broadband low-noise amplifier comprises an input matching network, a common-source differential output driving stage amplifier, an inter-stage matching network, a common-source differential output power stage amplifier and an output matching network which are connected in sequence, broadband matching is realized by using the input matching network and the inter-stage matching network, and the effective transconductance of the transistor is improved; through the cross-coupled capacitors, the LNA gain and stability on a broadband are improved, better isolation is realized, and input and output are decoupled; due to the design of the grounding capacitor, the linearity of the LNA is improved; through the combination of the three-coil coupling transformer and the differential topology, output signals are superposed in the same direction at the output end, and noise is cancelled in the reverse direction at the output end, so that the thermal noise is greatly inhibited, the isolation is improved through the output matching network, the insertion loss is reduced, and the output matching performance is optimized.

The invention belongs to the technical field of unmanned aerial vehicle full-aviation electromagnetic detection, and particularly relates to a full-aviation frequency domain electromagnetic emission system and a control method. A broadband frequency mixing and matching circuit is connected in series between an H-bridge power inverter and an emission coil of an unmanned aerial vehicle electromagnetic emission system; the broadband mixing and matching circuit comprises a first resonance unit formed by connecting a fixed capacitor and an adjustable inductor in parallel and a second resonance unit formed by connecting a fixed capacitor and an adjustable inductor in parallel, and the first resonance unit and the second resonance unit are connected in series. The adjustable inductor is matched with the dynamic impedance of the inductive load by adjusting the inductance value, and the broadband frequency mixing and matching circuit can adjust the impedance in real time, so that the matching of different resonant frequencies is realized, and the frequency range of a matching signal can be obviously widened.

Power switch device includes a wide-bandgap semiconductor switch, and a gate driver. The gate driver includes a driver circuit and a diagnostic circuit. The driver circuit is configured to provide a driver signal to control the wide-bandgap semiconductor switch. The diagnostic circuit is configured to sense an electrical characteristic of the wide-bandgap semiconductor switch, and perform a diagnostic test for the wide-bandgap semiconductor switch in response to the electrical characteristic of the wide-bandgap semiconductor switch.

The invention discloses a broadband wave-absorbing material based on an MAX-phase metasurface structure and an impedance matching optimization method of the broadband wave-absorbing material. The wave-absorbing material comprises an MAX-phase ceramic substrate and periodic metasurface structures which are arranged on the surface of the MAX-phase ceramic substrate in an array mode and composed of conductive resonance units. The resonance units are isolated through gaps, an equivalent R1L1C1 series resonance circuit is formed in an electromagnetic field, and a base body is equivalent to a parallel resistor R2. By establishing an equivalent circuit model and optimizing parameters R1, L1, C1 and R2, impedance matching of the wave-absorbing material in a target frequency band can be regulated and controlled, so that the wave-absorbing material at least has an absorption peak of which the reflection loss is less than-10 dB. According to the optimization method, electromagnetic simulation and circuit simulation are combined, optimized circuit parameters are reversely mapped into structure geometric parameters, material preparation is guided, and accurate design and broadband absorption of the wave absorbing performance are achieved.