1055 results about "Signal parameter" patented technology

The invention provides a control method for optimizing operation of high-power short-pulse microwave equipment, and aims to improve the accuracy of microwave interference signals, the energy utilization efficiency and the system adaptability. The method comprises the following steps: firstly, acquiring position information, motion trail data, electromagnetic scattering characteristics and environmental electromagnetic parameters of a target object; and then, according to the target position prediction data, the electromagnetic scattering characteristics and the environmental electromagnetic parameters, generating a microwave pulse waveform control instruction. And controlling the phased-array antenna array to generate a directional microwave beam based on the control instruction and the target position prediction data. And collecting real-time response data of the target, dynamically updating the target motion trend prediction model according to the real-time response data, and recalculating microwave pulse signal parameters. And finally, according to the updated signal parameters and the target position prediction data, adjusting the transmitting power, the working time sequence and the beam direction of the phased-array antenna array so as to maintain the optimal interference effect, reduce unnecessary energy consumption and improve the stability and adaptability of the system.

The invention relates to the technical field of signal parameter measurement, and provides a parameter measurement method for a frequency modulation monitoring antenna, which realizes self-adaptive monitoring and accurate measurement of a complex electromagnetic environment through multi-dimensional data acquisition, intelligent analysis and dynamic optimization, and deeply integrates environment perception, signal processing and parameter optimization. A complete technical chain is formed, so that the parameter measurement method can have self-learning and self-adjusting capabilities, can cope with environmental changes and interference challenges in real time, remarkably improves the monitoring efficiency and the measurement precision, and provides a systematic solution for the application of a frequency modulation monitoring antenna in a complex scene.

The invention provides a signal optimization transmission system and method based on HPLC and HRF dual-mode communication, a signal acquisition and processing module of the signal optimization transmission system based on HPLC and HRF dual-mode communication is used for acquiring signals of two communication modes of HPLC and HRF in real time, preprocessing the signals and extracting key signal parameters; the dual-mode switching module is used for dynamically switching an HPLC mode and an HRF mode based on channel quality; the access module is used for constructing a longitudinal backbone network and a transverse Mesh network, forming a hybrid topology, optimizing a routing path and coordinating resource allocation and conflict avoidance of HPLC and HRF; the intelligent decision module is used for predicting future interference intensity according to the historical interference data and adjusting channel parameters; the central coordinator module is used for network initialization and resource allocation; according to the system and the method, the HPLC mode and the HRF mode are automatically switched according to the channel quality, the longitudinal HPLC backbone network is combined with the transverse HRF Mesh network to form a four-dimensional communication network, and the robustness in a complex scene is remarkably improved.

Disclosed in the present invention is a non-autoregressive Transformer-based modeling method for a 4-level pulse amplitude modulation high-speed transmitter. The method involves establishing a deep learning model having an encoder-decoder architecture to predict the behavior of a 4-level pulse amplitude modulation transmitter. An encoder processes unordered non-sequential inputs, including an input signal parameter and link parameters, to generate a context vector and then transmit same to a decoder. The decoder uses both the context vector generated by the encoder and a transmitter output signal sequence to generate a categorical probability distribution for each point in the sequence one by one. The model is trained using a random masking strategy, and inference is performed by means of non-autoregressive decoding and filtering, so that the model can perform parallel prediction on an output sequence, and perform a filtering process to predict an output signal. Compared to traditional simulation methods, the present invention achieves a significant acceleration effect, particularly when processing multi-link systems.

The invention provides a multi-target automatic tracking method and system based on an unmanned intelligent turntable. According to the method, electromagnetic echoes and environment depth data are synchronously collected through a detector, and an observation data set is constructed; separating thermal radiation, surface texture and motion features, establishing a four-dimensional feature space containing space-time coordinates, and identifying a shielding area; dynamically adjusting signal parameters to enhance the characteristics of the shielding area and feeding back an optimization record; calculating an optimal scanning path based on the parameter optimization value, and driving the sensor array to perform multi-angle scanning to generate a weighted data set; in combination with historical trajectory data, a trajectory prediction model is optimized in parallel through distributed calculation, turntable parameter synchronization and decision making are coordinated, and finally efficient reconstruction of a multi-target continuous trajectory in a shielded environment is realized. According to the technical scheme provided by the invention, through multi-dimensional feature fusion and dynamic parameter optimization, reconstruction of a multi-target trajectory in a shielding environment is realized, and the environmental adaptability and tracking efficiency of an unmanned system are improved.

The invention discloses a method for improving transformer area crosstalk of HPLC (High Performance Liquid Chromatography) and micropower wireless dual-mode communication, which comprises the following steps of: S1, electrifying an acquisition terminal equipment node, and aligning signal acquisition time windows of two communication modes; s2, combining the obtained dual-mode signal parameters with a preset transformer area topology database to generate feature vectors of multi-dimensional features; s3, training to generate a random forest model, inputting feature vectors of multi-dimensional features, dynamically calculating the affiliation weight value of the transformer area, and carrying out nonlinear weighted calculation on the feature vectors; and S4, on the basis of weight comparison and transformer area boundary node processing, correcting measurement errors by combining the transformer area attribution weight value with a preset impedance shielding compensation algorithm, generating a unique transformer area identifier, locking a networking relationship, and executing transformer area attribution judgment. According to the method, the wide coverage advantage of HPLC is reserved, meanwhile, the space attenuation characteristic of wireless communication is used for achieving accurate recognition of the transformer area boundary, and the installation and acquisition stability of the use and acquisition terminal equipment can be improved.

The invention relates to the technical field of display screen driving, in particular to a low-power-consumption display screen driving method and system based on the OLED technology, and the method comprises the steps: S1, carrying out the image feature detection, collecting the inter-frame brightness change rate, the sub-pixel gray level distribution and the regional temperature gradient, and generating a dynamic driving signal parameter; s2, voltage compensation adjustment: dividing a power consumption area according to a brightness change rate, calculating a brightness compensation coefficient and correcting the voltage by combining gray level distribution and a temperature gradient, and realizing sub-pixel voltage dynamic adjustment; and S3, refresh frequency control: adjusting a local refresh rate according to the compensation coefficient and the correction voltage, executing a frequency reduction strategy on a high-power-consumption area, triggering ghosting suppression on a low-power-consumption area, and applying a temperature threshold to constrain a refresh upper limit. According to the invention, energy-saving driving, ghost suppression and brightness balance of the OLED display screen are realized, and the display performance and the system intelligence are effectively improved.

Apparatuses, systems, and techniques that utilize a neural network to infer signal parameters to direct and transmit wireless signals. In at least one embodiment, one or more neural networks are trained, using reinforcement learning techniques, to infer a beam direction to be used by a first device to transmit a signal based, at least in part, on characteristics of another signal being transmitted by a second device.

The invention relates to the technical field of pipeline detection, and discloses a pipeline weld defect analysis method and device based on magnetic flux leakage detection.The method comprises the steps that a composite excitation signal is generated and optimized through a multi-frequency excitation source, a magnetic flux leakage attenuation coefficient and scattering characteristics are calculated in combination with pipeline parameters, and if the attenuation coefficient exceeds a preset attenuation threshold value, the pipeline weld defect is detected; if yes, adjusting the excitation signal for optimization, extracting high-frequency transient and low-frequency stable features of the optimized magnetic flux leakage signal, and generating a preliminary feature vector of the weld defect; mapping the preliminary feature vector to a three-dimensional defect space position, generating a space distribution diagram containing the defect position, optimizing the preliminary feature vector to make a fuzzy region clear, and obtaining the depth and direction of the defect; and according to the depth and direction of the defect, analyzing the spatial distribution characteristics of the preliminary feature vectors, determining the type of the defect, dynamically adjusting excitation signal parameters for optimization, recalculating the attenuation coefficient of the signal, extracting the optimized scattering features, and obtaining a high-precision weld defect positioning result.

Apparatuses, systems, and techniques that utilize a neural network to jointly infer signal parameters to direct and transmit wireless signals. In at least one embodiment, one or more neural networks are trained, using reinforcement learning techniques, to infer hybrid beamforming parameters used by one or more devices to transmit wireless signals.

Novel tools and techniques are provided for implementing detection and estimation of direct and reflected navigation satellite (e.g., global navigation satellite system (“GNSS”), etc.) signal parameters in a multipath environment. In various embodiments, logic of semiconductor package that is disposed on a user device concurrently receives a plurality of signals from a satellite(s), each signal travelling along a different path between each satellite(s) and the user device within a multipath environment. The logic identifies two or more signal peaks that fall within a tracking aperture based on analysis of the received signals, and determines peak parameter estimates for each signal peak based on measurements of signal parameters from at least one signal peak. The logic provides the determined peak parameter estimates for each signal peak to a position engine (“PE”) of the user device to calculate a navigation solution (e.g., position, velocity, and / or time, etc.) for the user device.

The invention discloses an eSIM service cost intelligent optimization method based on different operator information sources, and particularly relates to the technical field of operator network management. The method comprises the following steps: collecting eSIM tariff rules of a plurality of operators and real-time charging data of eSIM terminals, extracting tariff terms and conditional expense trigger mechanisms hidden in charging behaviors of different operators by using an association rule mining algorithm, and constructing a multi-level cost structure model; on the basis of a network registration behavior log of the eSIM terminal, predicting the probability that each operator signal source has an abnormal registration event, and evaluating the risk that each operator signal source triggers a hidden cost trap in combination with a multi-level cost structure model; and according to the real-time network signal parameters of the eSIM terminal, a signal source recommendation strategy is generated in combination with the risk assessment result, and the eSIM terminal is driven to execute a signal source switching operation, so that real-time adjustment and cost optimization control of communication network selection are realized, and the service stability of the eSIM in a cross-network use scene is improved.

The invention provides an unmanned aerial vehicle navigation decoy method and system based on multimode satellite signal counterfeiting. The method comprises the following steps: firstly, acquiring original signal parameters, covering signal time delay, carrier phase and signal intensity distribution, of multimode satellite signals in an unmanned aerial vehicle navigation link in a target area in real time; secondly, extracting spatio-temporal characteristics through signal time delay and carrier phase, and generating time domain synchronous forged navigation parameters in combination with signal strength dynamic change; dynamically adjusting the signal time delay correction and the carrier phase offset in the forged navigation parameters; meanwhile, dynamic compensation is carried out on the navigation message based on the three-dimensional coordinate increment, and a multimode forged navigation signal covering the receiving end of the unmanned aerial vehicle is generated; and finally, superposing the forged navigation signal and the original signal parameter to form a deceptive navigation track for inducing the unmanned aerial vehicle to deviate from the original route. According to the technical scheme provided by the invention, the multi-mode compatibility and concealment of navigation decoy of the unmanned aerial vehicle can be improved.

Disclosed are a beam management method and apparatus, applied to a network device, comprising: receiving first feedback information reported by a user equipment, the first feedback information comprising measured values of signal parameters of a first beam set in N historical time windows, the signal parameters comprise physical layer reference signal receiving power L1-RSRP, reference signal receiving quality RSRQ and signal to interference plus noise ratio SINR, and N is an integer greater than or equal to 1; performing beam prediction based on the first feedback information to obtain a beam prediction result, the beam prediction result comprising a second beam set and / or second beam information, the second beam set being a subset of a third beam set, and the third beam set being a set of candidate beams used by the network device for transmitting data; the second beam information comprises a predicted value of a signal parameter of each beam in the second beam set. By implementing the embodiments of the present application, the accuracy of beam prediction can be improved, and the signaling overhead and time delay of beam prediction can be reduced.

The invention provides a signal exception processing method and system, a server and a storage medium, and relates to the field of servers, the method is applied to the signal exception processing system, the signal exception processing system comprises a substrate management controller and a hardware extension module, and the hardware extension module is used for performing function extension on a central processing unit and a universal input and output interface. Wherein the substrate management controller does not immediately respond to the signal sent by the hardware extension module, but can firstly take the signal as a to-be-detected signal, and detect the signal according to a preset signal parameter to determine whether the signal form is abnormal or not. And if the to-be-detected signal is determined to be abnormal, in order to distinguish whether the to-be-detected signal is a normal signal, the substrate management controller can also actively acquire a register value corresponding to the signal from the hardware extension module, and determines whether to respond to the to-be-detected signal according to whether the logic meaning of the to-be-detected signal is consistent with the logic meaning of the register value. In this way, signal abnormity can be actively detected, and error response can be avoided.

The invention relates to the technical field of submarine cable fault positioning, in particular to a submarine cable fault positioning system based on underwater beacons. The method comprises the steps that an underwater acoustic beacon array unit monitors and collects submarine cable fault sound wave signals in real time based on underwater acoustic beacons; the fault signal processing analysis unit extracts submarine cable fault sound wave signal parameters based on a non-point source space sound source waveform analysis model, and generates multi-parameter fault sound source feature vectors; the sound source positioning analysis algorithm unit performs three-dimensional inversion positioning based on the multi-parameter fault sound source feature vector and the arrival time difference of the submarine cable fault sound wave signal to the underwater acoustic beacon, and obtains the spatial position information of the submarine cable fault point; and the data communication alarm management unit sends the spatial position information of the submarine cable fault point to a shore-based operation and maintenance system. The submarine cable fault positioning method is used for realizing a submarine cable fault positioning technology for quickly and accurately positioning and identifying spatial extension characteristics in a complex submarine environment.

The invention provides a coal rock fracture damage mode classification method and system. The coal rock fracture damage mode classification method comprises the steps that collected acoustic emission signals are preprocessed, and damage categories are marked for various signal parameter data; inputting various signal parameter data and annotation data and training an integral coal rock fracture damage mode classification model, wherein the model comprises an adaptive diversity wavelet kernel module, a CWT-based feature extraction layer, a BiLSTM feature fusion layer and a classification layer; the adaptive diversity wavelet kernel module is used for extracting time domain features, frequency domain features and CWT features of various signal parameter data, adaptively adjusting wavelet kernel parameters, generating a diversified wavelet kernel set, inputting the diversified wavelet kernel set into a CWT-based context feature extraction layer, including global branches and local branches of parallel calculation, and respectively extracting global features and local features; carrying out feature fusion on the global features and the local features through a BiLSTM feature fusion layer; and inputting the fusion features into a classification layer, and classifying the coal rock fracture damage modes. According to the method, the coal rock fracture damage modes can be classified.

The invention relates to the technical field of 5G communication, in particular to a 5G network signal low-altitude coverage test method and system, and the method comprises the steps: obtaining regional geographic information and base station layout information; based on geographic information and base station layout, constructing a three-dimensional digital map, dividing a dynamic test grid, and determining an initial flight path; according to a multi-source sensor of the unmanned aerial vehicle, in combination with the initial flight path, collecting 5G signal parameters and environmental data of the grid points through a preset frequency; a wavelet transform filtering algorithm is adopted for calibration, abnormal values are removed, and feature vectors are generated; according to the feature vectors, a coverage evaluation model is constructed in combination with a three-dimensional digital map, and a low-altitude coverage blind area and an interference type are identified; and if a low-altitude coverage blind area or abnormal interference is detected, dynamically adjusting the flight path of the unmanned aerial vehicle through an A-star algorithm, testing a target area, and generating a coverage optimization scheme based on a test result. Therefore, the problems of low test efficiency, lagging data processing and analysis and the like in the prior art are solved.

The invention relates to the technical field of power management, in particular to a multi-source data fusion photovoltaic power scheduling control system, which comprises a sensing extraction module, a disturbance identification module, an offset trend analysis module, a path switching module and a frequency band suppression module. According to the method, a disturbance pre-judgment interval is identified by constructing a time derivative sequence and combining illumination and wind speed trend change in a continuous period, a disturbance time period is accurately discriminated, the disturbance interval is confirmed and disturbance characteristics are extracted through conjoint analysis of photovoltaic and energy storage current change trend and grid-connected point fluctuation amplitude, and the disturbance accuracy is improved. An offset trend curve is formed by calculating photovoltaic and energy storage current change differences, the energy supply offset degree is judged in real time to trigger scheduling conditions, dynamic suppression adjustment is performed on regulation and control signal parameters according to spectrum energy distribution, the accuracy and timeliness of disturbance recognition, energy supply offset judgment and frequency band regulation and control are improved from multiple levels, and the energy storage and energy supply efficiency is improved. And more stable and efficient optical storage combined scheduling control is realized.

The invention discloses a mechanical arm regulation and control multi-sensor array underground structure detection system and detection method based on reinforcement learning, a vibration source module provides a sweep frequency vibration signal, a multi-sensor array collects a reflected signal, a data processing module receives and processes the reflected signal, and the data processing module receives and processes the reflected signal; the imaging module generates a three-dimensional underground structure image through a wave velocity inversion and reverse time migration imaging technology, the intelligent optimization and adaptive adjustment module adaptively adjusts vibration source signal parameters and sensor array layout through a reinforcement learning algorithm, and the display terminal displays detection data and imaging results in real time and provides parameter optimization suggestions. According to the invention, real-time and automatic adjustment of vibration source signals and sensor layout is realized through an intelligent optimization and adaptive adjustment module constructed through a reinforcement learning algorithm, and a high-resolution underground structure three-dimensional image is generated accordingly. And an efficient and accurate underground structure identification and positioning scheme can be provided.

The invention relates to the technical field of unmanned aerial vehicle monitoring and trajectory processing, and discloses a low-altitude unmanned aerial vehicle dynamic trajectory tracking and predicting method based on multi-base-station cooperation. The method comprises the steps that signal parameters are obtained through multi-base-station collaborative observation, and a multi-modal position prediction set is generated; and performing classification and scoring according to the spatial distribution characteristics of the candidate points and the historical track points, and screening out an optimal prediction position point. And inputting the optimal prediction point and the historical trajectory into a generative model, and dynamically adjusting the number of trajectory points by analyzing the point distribution probability to form a preliminary smooth trajectory. And performing physical feasibility verification and fine adjustment on the trajectory according to kinematics constraints to obtain a final smooth continuous trajectory. And matching degree calculation is carried out by fusing alternative trajectories generated by a multi-kinematic model, and the most probable target trajectory is identified. According to the method, the robustness of trajectory prediction and the structural rationality of the generated trajectory in a complex observation environment are improved.

The invention provides a feature extraction method for an electroacoustic background interference signal of operation power transformation equipment, which belongs to the technical field of power transformation equipment, and comprises the following steps: acquiring an electroacoustic signal, preprocessing the electroacoustic signal, and generating a controlled interference signal at the same time; and performing time-frequency analysis on the preprocessed electroacoustic signal and the controlled interference signal, and optimizing the interference signal parameter to enable the interference signal parameter to be highly similar to the electroacoustic signal. And constructing a wavelet basis function library based on the optimized controlled interference signal, and performing wavelet packet decomposition on the electroacoustic signal to obtain a plurality of frequency band sub-signals. A self-adaptive threshold model is established by using a controlled interference signal, and soft threshold denoising processing is performed on sub-signals. Time-frequency features of the denoised sub-signals and the controlled interference signals are extracted, a feature mapping relation is established, and an initial feature set is obtained; and performing nonlinear dimensionality reduction on the initial feature set by adopting principal component analysis to obtain a dimensionality-reduced feature set. And an improved support vector machine model is adopted to evaluate the importance of dimension reduction features, and an optimal feature set is selected as an electroacoustic background interference signal feature.

The invention discloses a computer mainboard abnormity identification method and system, and relates to the technical field of computer hardware diagnosis and maintenance, and the method comprises the following steps: collecting voltage, temperature and current signal parameters on a mainboard in real time; preprocessing the signal parameters to extract features; and inputting the preprocessed feature data into a pre-trained machine learning model, wherein the model is generated based on historical fault case training. According to the computer mainboard abnormity identification method and system, the voltage, temperature and current signal parameters of the mainboard are collected in real time, the pre-trained machine learning model is used for abnormal mode identification, the accuracy and the real-time performance of mainboard abnormity detection are remarkably improved, dominant faults can be identified, and the fault detection efficiency is improved. In addition, potential anomalies with high concealment, intermittency and relevance can be captured, the missing report rate and the false report rate are effectively reduced, time sequence analysis and spectrum analysis are combined, the capturing capacity of instantaneous anomalies is enhanced, and anomaly positioning is more accurate.

The invention provides a master-slave distributed synchronous satellite navigation decoy system and a control method, and belongs to the field of satellite navigation. The system is composed of a master control station and a plurality of synchronous deception signal generators arranged in different directions. And the master control station plans a deception trajectory by using a closed-loop control principle according to modes and parameters set by a user, satellite signal parameters output by the common-view GNSS receiver and target position and speed information transmitted by the detection system, generates a satellite number distribution and power control strategy, and generates a control instruction. And the master control station controls the deception signal generator to generate and emit a navigation deception signal causing false GNSS positioning according to the flow of the GNSS navigation signal simulator. When the signal reaches a target GNSS receiver antenna, the signal is synchronized with a GNSS satellite signal received by a target so as to control and decoy an integrated navigation system carried on the target, so that the target deviates from a preset course and track, and the purpose of hiding and efficiently preventing the target from invading a no-fly zone is achieved.

The invention discloses a substation primary and secondary equipment communication prefabricated optical cable online monitoring method and system, and belongs to the technical field of communication prefabricated optical cable monitoring. The system comprises an optical cable parameter acquisition module, a communication quality evaluation module, a physical parameter analysis module, a first-aid repair path planning module and a fault database. The method comprises the following steps: optical cable parameter acquisition: acquiring data in real time, and converting high-dimensional data into low-dimensional data through a principal component analysis algorithm; communication quality evaluation: identifying communication characteristics in the low-dimensional signal parameter matrix based on a fuzzy comprehensive evaluation algorithm, and outputting a communication quality score; the physical parameter analysis module extracts physical deep features of the optical cable by using a deep belief network DBN, and inputs an improved Bayesian classifier to output a state classification result; according to the first-aid repair path planning, OTDR detection parameters are dynamically adjusted, and an optimal first-aid repair path is planned in combination with the position of the inspection robot; according to the invention, optical cable communication quality evaluation, accurate physical state classification and efficient fault repair planning are realized.

The invention relates to the technical field of automatic production monitoring, and particularly discloses a composite monitoring system for an automatic production line of petroleum pipes, which realizes the stable processing and information identification process of the automatic production line of the petroleum pipes through the composite monitoring system. The system module comprises a sensor wiring module which is used for being connected with a sensor on an automatic production line to obtain the position layout of the sensor, determining wiring information and transmitting process signal parameters on the wiring information to a main control center; a key area selection module is arranged and used for determining key area information according to the process signal parameters obtained by the main control center; a composite monitoring module is arranged and used for importing the key area information into a composite numerical control platform to be matched with a corresponding process for monitoring, and an abnormal quality coefficient is obtained; and a monitoring identification module is arranged and is used for carrying out fault identification according to the abnormal quality coefficient and outputting fault early warning information.

The invention discloses an unmanned aerial vehicle frequency hopping signal sorting and identification method based on spectrum characteristics, and the method comprises the following steps: carrying out the short-time Fourier transform of a signal received by a receiver, and obtaining a time-frequency matrix; eliminating fixed-frequency signal interference by adopting an energy cancellation method to obtain a time-frequency matrix; partial background noise is processed and eliminated through a threshold value method, and a binary matrix is obtained; removing interference by adopting a morphological filtering method to obtain a binary matrix; estimating parameters of the unmanned aerial vehicle by adopting a time-frequency analysis method to obtain a frequency hopping signal parameter set; matching the frequency hopping signal parameter set with features in an unmanned aerial vehicle signal feature library to obtain a pre-classification cluster; performing frequency hopping period estimation on the frequency hopping moment sequence in the pre-classification clusters by adopting a repetition period transformation method to obtain the frequency hopping period of each pre-classification cluster; adopting a sequence signal retrieval algorithm to screen out a frequency hopping sequence conforming to a frequency hopping period estimation value in the pre-classification cluster to obtain a main classification cluster; and matching the parameter set of the main classification cluster with the features in the unmanned aerial vehicle feature library and a frequency hopping signal number threshold, and if matching succeeds, identifying a specific unmanned aerial vehicle model. The method can solve the problems that interference cannot be effectively eliminated and multi-unmanned aerial vehicle frequency hopping signals cannot be sorted in a limited technology.

The invention relates to the technical field of signal crosstalk prevention, and provides an FFC wire harness signal crosstalk prevention method and device, electronic equipment and a storage medium. The method comprises the steps of performing frequency spectrum and time domain feature extraction processing on an original FFC signal to obtain a basic signal parameter set, constructing an FFC wire harness electromagnetic model according to FFC wire harness geometric data, and performing multi-conductor transmission line parameter extraction processing according to the basic signal parameter set and the FFC wire harness electromagnetic model to obtain a distribution parameter matrix. And performing Pareto multi-objective optimization processing on the signal arrangement sequence and daemon insertion of the distribution parameter matrix to obtain an optimal signal sequence and a daemon scheme, and performing microstructure configuration processing of the overall shielding layer and the grounding network according to the optimal signal sequence and the daemon scheme to obtain a shielding arrangement scheme. According to the invention, through fine modeling and multi-target collaborative optimization, the FFC wire harness realizes low crosstalk, high bandwidth and low electromagnetic radiation in a high-frequency and high-speed transmission environment.

The invention discloses an uplink subsystem complexity reduction method based on a PCMA technology, and relates to the technical field of high-capacity wireless transmission system design and complexity control, and the method comprises the following steps: collecting uplink signal parameters through spectrum analysis, bit error rate test and MIMO detection, obtaining channel characteristics through a pilot frequency and a Gray sequence, and obtaining the complexity of a high-capacity wireless transmission system; baseband data are generated, scene features are extracted, Wiener filtering and iterative soft decision feedback algorithms are adopted to optimize filtering and coding, channel and coding performance is evaluated, transmission strategies are dynamically adjusted through a gigabit network interface, clocks are unified, synchronization is optimized, and the complexity of a PCMA uplink system is reduced. The complexity of an uplink subsystem is effectively reduced through the PCMA technology, the efficiency and the stability of a high-capacity wireless transmission system are improved, efficient utilization of resources and improvement of synchronization precision are achieved by accurately collecting signal parameters, optimizing filtering and coding and dynamically adjusting a transmission strategy, and the method is suitable for large-scale popularization and application. And powerful support is provided for the development of a wireless communication system.

The invention relates to the technical field of radio transmission systems, in particular to a dual-module redundant satellite communication and internet-of-things terminal system, which comprises a data processing module, a management module, a frequency band allocation module, a self-adaptive switching decision module, a scheduling module and an optimization module. The data processing module collects satellite signal parameters and terminal state data, and generates dynamic decision context information including conflict frequency band feature vectors, terminal dynamic position tags and channel load indexes; the system iteratively optimizes a frequency band allocation strategy through a closed-loop data stream, constructs a conflict spatio-temporal topology network by adopting a graph database to realize competitive traceability, manages historical parameters in combination with a distributed data storage module, finally reduces channel competition conflict and data retransmission rate, optimizes terminal energy consumption and communication reliability, and improves the system performance. The method is suitable for Internet of Things terminal communication in complex environments such as satellite signal shielding and electromagnetic interference.