5007 results about "Azimuth" patented technology

The invention relates to the technical field of communication, in particular to an airborne Tiantong phased-array antenna and an application method thereof. According to the method, phased-array antenna beams are driven to perform electronic scanning according to a geometric azimuth angle, beacon signal blind acquisition is performed in a preset airspace in a wide beam mode, and when an initial signal is detected, the mode is immediately switched to a narrow beam scanning mode; dynamically adjusting a phase weighting coefficient to realize pointing adjustment, so that a signal quality parameter is continuously converged in an optimal threshold interval; carrying aircraft maneuvering acceleration feedback is introduced, beam pointing offset is dynamically compensated based on a pre-constructed interference feature library, and signal fluctuation caused by a multipath effect is suppressed; and continuously checking a data validity flag bit of the main inertial navigation system, seamlessly switching to an antenna built-in inertial navigation data stream when a failure threshold is triggered, and activating a rapid recapture program to maintain zero interruption of a communication link. Through dual-source inertial navigation data fusion and intelligent beam control, rapid and accurate tracking of Tiantong satellites in an airborne environment is realized.

The invention relates to the technical field of trajectory tracking, in particular to an unmanned aerial vehicle trajectory tracking target classification method and system based on a multi-frequency-band radar, and the method comprises the following steps: synchronously collecting original radar echo data of a millimeter wave frequency band, a Ku frequency band and an L frequency band, and generating a multi-frequency-band data set comprising a timestamp, an azimuth angle and a pulse sequence; extracting multi-dimensional features of the target from the synchronized multi-band data set, and generating a multi-band feature vector; constructing a dynamic trajectory association matrix, and determining the space-time continuity of a target trajectory through a trajectory association algorithm based on an attention mechanism; constructing a lightweight classification model; performing online classification on the real-time multi-band feature vectors by using a lightweight classification model, and outputting a target type and confidence; according to the method, capture of the motion state of the target is enhanced, rapid response can be made to tiny motion and change of the target in a complex scene, and therefore more comprehensive and accurate time sequence context information is provided for subsequent classification tasks.

The embodiment of the invention provides a three-dimensional ray drawing method and device, and a curve control point is dynamically generated through precise conversion of a geographic coordinate system and a projection coordinate system in combination with an azimuth angle and an earth surface distance. A curvature correction mechanism based on a curved surface projection model is innovatively designed, the influence of the earth curvature on a ray trajectory is considered, and smooth space trajectory generation is realized through a Bezier curve parameter model. According to the system, the coordinate transformation compensation and spherical projection technology is adopted, accurate mapping of a geodetic coordinate system and a display coordinate system is established, accurate rendering of a three-dimensional space curve under different scales and view angles is ensured, and a high-precision technical scheme is provided for geographic information visualization. According to the method, the limitation of traditional straight line drawing is broken through, and the real trajectory expression considering the earth curvature is realized.

The invention provides an intelligent drilling guide method and system for a petroleum drilling tool face, and relates to the technical field of intelligent control, and the method comprises the steps: determining a first target point, a second target point and a third target point in the process of tracking a target azimuth angle according to a dynamic adjustment instruction; constructing a dynamic triangle through the first target point, the second target point and the third target point, and taking the barycentric coordinate of the dynamic triangle as an azimuth angle correction value; correcting forward and reverse rotation angles and periodic parameters of the drill string according to the azimuth angle correction value so as to obtain a corrected dynamic adjustment instruction; and controlling a drill string to act based on the corrected dynamic adjustment instruction, so that the underground tool surface continuously approaches the target azimuth angle through closed-loop iteration adjustment. The control efficiency and stability of the tool face under the complex working condition can be improved.

The invention relates to the technical field of directional drilling track control, and discloses a coal mining underground directional drilling track control method and system, and the method comprises the steps: carrying out the fusion track analysis of a drilling machine based on sensor data, drilling parameters and pre-obtained geological hardness parameters, and obtaining a reference track of the drilling machine, a sensor, an azimuth angle sensor and a bit pressure sensor are used for synchronously collecting drill bit attitude data of a drilling machine to generate a real-time track of the drilling machine, then track offset calculation is carried out to obtain inclination angle deviation and azimuth angle deviation, and dynamic gain adjustment analysis is carried out on the drilling machine to obtain adjustment parameters of the drilling machine. And finally, the drill bit posture of the drilling machine is adjusted based on the adjusting parameters. According to the method, the directional control accuracy of the underground drilling track can be improved.

The invention provides a calibration method for an inertial measurement unit of an airborne photoelectric platform, and belongs to the technical field of precision optical machine installation and adjustment, and the method comprises the following steps: S1, detecting and adjusting the intersection degree of the position of an azimuth pitch axis system of the airborne platform; s2, calibration and precision detection are carried out on a rotating shaft of an azimuth pitch axis system of the airborne platform; s3, detecting and adjusting the perpendicularity of the azimuth pitch axis system of the airborne platform; s4, carrying out orthogonality detection and adjustment on the optical axis and the shaft system of the photoelectric platform; and S5, calibrating the coordinate system deviation of the inertial measurement unit. According to the method provided by the invention, through a series of optical machine adjustment steps, the shafting precision adjustment of the airborne platform and the deviation calibration of the inertial measurement unit are completed at the same time, the orthogonal coordinate system adjustment and positioning of the shafting and the optical axis of the airborne photoelectric platform are realized, and the deviation value of the inertial measurement unit and the orthogonal coordinate system is tested. And the information is fed back to a data processing subsystem to realize geometric space correlation calculation.

The embodiment of the invention provides an X-band weather radar non-rainfall data quality control method and system. The method is applied to the technical field of weather radars and comprises the following steps: acquiring X-band weather radar data; identifying and eliminating the electromagnetic interference echo according to the continuity characteristic of the electromagnetic interference echo and the distribution condition of the correlation coefficient CC and the differential reflectivity factor ZDR; judging whether the difference value of the reflectivity factors of each echo point before and after hardware filtering is greater than a preset threshold value or not, and if so, marking the echo point as a rainfall echo; if not, fuzzy logic recognition elimination based on characteristic parameters is carried out; wherein the non-precipitation echo probability PNPR and the precipitation echo probability PPR of each echo point are calculated according to the characteristic parameters, whether the PNPR is larger than the PPR or not is judged, and if yes, the echo point is marked as a non-precipitation echo; if not, non-rainfall weak echo discrimination is carried out; whether the echo is a non-rainfall echo is determined by comparing the reflectivity factor mean value # imgabs0 #, the correlation coefficient mean value # imgabs1 # of the elevation angle of the whole layer of the echo and the ratio ValCC of the effective distance library number of the correlation coefficients with a judgment threshold value, and if the echo is the non-rainfall echo, the echo point is marked as the non-rainfall echo; and if not, continuously filtering scatter and plaque noise around the echo point by using the reflectivity factors in the radial direction and the azimuth to obtain the rainfall echo. In this way, the quality of weather radar data can be improved.

An object detection device includes an azimuth sensor that measures an azimuth region of an object that is present around a vehicle, a plurality of distance sensors each of which measures a distance to the object, and an object determination section that calculates arcs of circles whose radii are the distances measured by the respective distance sensors and calculates intersection points of a tangent to adjacent ones of the arcs and the azimuth region measured by the azimuth sensor.

The invention provides a method and device for determining the horizontal stress difference ratio of a deep coalbed methane reservoir, and relates to the technical field of deep coalbed methane exploration, and the method comprises the steps: obtaining the logging data and azimuth seismic observation data of the deep coalbed methane reservoir, building a reservoir parameter initial model of the deep coalbed methane reservoir based on the logging data, and obtaining the horizontal stress difference ratio of the deep coalbed methane reservoir; constructing a target functional for inverting deep coal bed gas reservoir parameters on the basis of azimuth seismic observation data and an azimuth seismic reflection coefficient equation, and solving the target functional on the basis of a generalized linear inversion theory and an iterative reweighted least square joint algorithm under the constraint of the initial model to obtain a reservoir parameter target model; and calculating the horizontal stress difference ratio of each sampling point in the deep coal bed gas reservoir according to the target model. According to the method, under the constraint of the accurate initial model, accurate estimation of the horizontal stress difference ratio of the deep coal bed gas reservoir is achieved, and the technical problem that an existing horizontal stress difference estimation method is low in accuracy is solved.

The invention discloses an alignment method for a vehicle-mounted radar and related equipment, and relates to the technical field of navigation calibration, and the method comprises the following steps: obtaining inertial measurement unit data and horizontal tilt angle sensor data of the vehicle-mounted radar; generating an initial attitude matrix based on the inertial measurement unit data; determining a horizontal attitude data difference based on the horizontal tilt angle sensor data and the initial attitude matrix; and obtaining an alignment result of the vehicle-mounted radar based on the horizontal attitude data difference and a Kalman filtering algorithm. The initial attitude matrix is generated by fusing the inertial measurement unit data and the horizontal tilt angle sensor data, fine alignment is performed by combining the horizontal attitude data difference and the Kalman filtering algorithm, the azimuth angle alignment precision of the vehicle-mounted radar in a dynamic environment is improved, dependence on external satellite signals is not needed, and the accuracy of the azimuth angle alignment is improved. High-precision autonomous alignment can be realized under complex working conditions such as shaking and vibration, meanwhile, the hardware cost and the system complexity are reduced, and the method has wide applicability.

The invention belongs to the technical field of geophysical monitoring, and relates to an electromagnetic interference detection method for earthquake monitoring, which comprises the following steps: deploying a multi-dimensional electromagnetic field sensing unit and an earthquake signal acquisition unit and realizing high-precision synchronization; synchronously acquiring multi-dimensional electromagnetic field and seismic physical signal data; performing multi-feature and noise feature extraction on the two; inputting the features into a pre-trained machine learning / deep learning model for identification, and outputting information such as interference type, intensity and azimuth angle; and carrying out influence evaluation and quality marking on the seismic data according to the output, and selectively inhibiting or compensating. Through the above scheme, multi-dimensional perception and characterization, high-precision synchronization and correlation analysis, intelligent identification and spatial positioning are realized, and the reliability and accuracy of earthquake monitoring data are significantly improved.

The invention discloses a data processing method and system for micro-motion detection array station distribution, and relates to the technical field of micro-motion detection, and the method comprises the steps: according to the actually measured starting point coordinates and the azimuth angle of a measuring line, setting the measuring point distance, and the radius and number of nested triangle circumcircles, generating field station coordinates in batches; collecting and preprocessing station waveform data; calculating a spatial autocorrelation coefficient of any center station and a non-center station; dBSCAN clustering is carried out based on the station distance; performing spatial averaging on the spatial autocorrelation coefficient according to a clustering result; fitting the averaged spatial autocorrelation coefficient and a zero-order Bessel function to obtain a frequency dispersion spectrum, picking up a surface wave phase velocity in the frequency dispersion spectrum, and calculating an apparent shear wave velocity; inverting the shear wave velocity of the waveform data by adopting a self-adaptive gradient inversion strategy; and generating a velocity comprehensive profile of a depth domain and a frequency domain according to the surface wave phase velocity, the apparent shear wave velocity and the inverted shear wave velocity. The invention provides a new method for station distribution to data processing for micro-motion detection.

The invention discloses an atmospheric boundary layer turbulence statistic inversion method and system based on a 6-beam ground-based light quantum wind measurement laser radar DBS scanning mode, a medium and a program product, and relates to the technical field of atmospheric remote sensing and boundary layer detection. A multi-direction radial wind speed time sequence is collected, and the radial speed variance of each beam is calculated on the basis of data quality control; and further establishing a relationship between the velocity variance and the covariance of the velocity in the three directions, constructing an observation equation set and inverting the turbulence statistics, and combining coordinate rotation to obtain the turbulence statistics in the downwind direction, the transverse wind direction and the vertical direction. And finally, calculating turbulent flow kinetic energy, and outputting a turbulent flow statistic vertical profile of each height layer. According to the method, continuous monitoring and high-precision description of the atmospheric boundary layer turbulence statistics can be realized, and the requirements of a service system on stability, precision and deployability of a boundary layer turbulence inversion product are met.

The invention discloses an unmanned ship displacement attitude high-precision fusion method based on adaptive Kalman filtering, and belongs to the technical field of ship sensing positioning, and the method comprises the steps: building a discrete time state space model of a navigation data state through employing a discrete integration mode based on the navigation data state; obtaining a system state equation by means of a rotation matrix and a median theorem; obtaining an observation transfer matrix through coordinate system information, a geodesic line length between two points and an azimuth angle, and obtaining a state observation equation by combining noise data; based on the system state equation and the state observation equation, using an adaptive Kalman filtering algorithm to obtain displacement attitude information of the unmanned ship; detecting the prediction data of the unmanned ship by using a sliding window method; and when the predicted data is detected to be abnormal, substituting the predicted data into Kalman filtering for correction. According to the invention, through state modeling, fusion algorithm, anomaly detection and anomaly correction, the precision, reliability and robustness of obtaining the displacement attitude information of the unmanned ship are improved.

The present invention relates to the technical field of prevention and control of geological disasters in mountainous coal mining areas. Disclosed are an InSAR-based measurement method for the angle of critical deformation of a coal mining area, and a system. The method comprises: acquiring a mining-induced surface deformation field image by means of small baseline subset-interferometric synthetic aperture radar; in the mining-induced surface deformation field image, separately drawing profile lines along a coal seam strike and a coal seam dip, and selecting target deformation points on the profile lines as points to be monitored; according to the incident angle, the flight direction and the azimuth angle of a satellite, obtaining vertical and horizontal deformation values; using a probability integral method to calculate parameters such as inclination, curvature and horizontal deformation; and drawing a curve graph on the basis of the vertical deformation of a target region and the above parameters, so as to obtain a corresponding angle of critical deformation. The InSAR-based measurement method for angle of critical deformation of a coal mining area provided by the present invention has the advantages of improved temporal resolution and reduced phase noises and the like, can achieve high precision and high efficiency, and can generate clear and visible Excel tables for surface deformation data of mining areas and corresponding profile data.

The invention provides an AR positioning and direction correction method and device, equipment and a storage medium, and relates to the technical field of augmented reality, and the method comprises the steps: obtaining a first high-precision positioning point and a second high-precision positioning point, and respectively calculating azimuth angles in a geographic coordinate system and an AR coordinate system; the initial orientation when the device is started is then determined by using the angle difference between the azimuth angles. According to the initial orientation, coordinate orientation rotation can be carried out on three-dimensional scene elements in the AR scene, so that direction correction is completed. By using the high-precision positioning point information, the initial orientation of the equipment can be determined more accurately, so that the accuracy of AR positioning is improved. Moreover, no external auxiliary equipment or infrastructure is needed, and accurate AR positioning and direction correction can be realized only by means of the equipment and known high-precision positioning point information, so that the hardware cost is reduced.

The present invention relates to a method and apparatus for calculating and evaluating the loss of light collection efficiency of a heliostat. 【Solution means】The present invention simulates the pulsating wind load distribution of a heliostat at different elevation-azimuth angles by CFD calculation, extracts the aerodynamic admittance function and shape parameters, constructs a pulsating wind load spectrum prediction model, calculates the pulsating wind load spectrum by combining the attitude parameters of the heliostat, applies the pulsating wind load spectrum to the structural model of the heliostat mirror by finite element analysis, obtains the instantaneous dynamic response, displacement and strain distribution characteristics of the heliostat, simulates the influence of mirror deformation on the light reflection path, quantifies the instantaneous influence on the light collection efficiency of the deformed mirror, and generates a dynamic curve of the change of light collection efficiency over time.

The invention relates to the technical field of optical detection, in particular to an aspheric lens laser interference detection adjustment error separation system and method, and the method comprises the steps: placing an aspheric lens on a clamping platform, carrying out the multiple laser interference measurement through adjusting different pitch angles and azimuth angles, and collecting a multi-angle interference fringe image; for different installation and adjustment error types, key features of typical error fringe images are extracted and compared with current interference fringe images, and identification of the installation and adjustment error types and levels is achieved; a mathematical model of various installation and adjustment errors is constructed, polynomial parameterization representation is adopted, installation and adjustment compensation parameters are reversely solved according to an identification result, and installation and adjustment are completed; and repeating the measurement and analysis process, and constructing an error adjustment frequency optimization model until the precision requirement is met. The method provided by the invention can improve the adjustment efficiency and precision of the aspherical lens.

The invention relates to the technical field of optical system detection devices, in particular to a large-aperture standard reflector adjusting device, which specifically comprises a bottom plate, an orientation rotating device, a pitching rotating device and a reflector fixing device, and is characterized in that the orientation rotating device is arranged above the bottom plate; the pitching rotating device is arranged above the azimuth rotating device; the reflector fixing device is connected to the pitching rotating device, so that the azimuth rotating device can adjust the azimuth angle of the reflector fixing device, and the pitching rotating device can adjust the pitching angle of the reflector fixing device; wherein the azimuth rotating device and the pitching rotating device have a self-locking function. Therefore, under the condition that the surface type precision of the mirror surface of the standard reflecting mirror is ensured, the standard reflecting mirror can be precisely adjusted at a large angle in the azimuth angle and the pitching angle, and the detection requirement of an optical system is met.

The present disclosure discloses a method for suppressing the azimuth ambiguity of multi-channel SAR systems based on channel cancellation, which falls within the field of radar signal processing. The method includes: imaging echoed of the multi-channel SAR system based on a linear mapping reconstruction algorithm to obtain a reconstructed high-resolution wide-swath image; estimating positions of the azimuth ambiguity regions of the reconstructed high-resolution wide-swath image; extracting ambiguity images in the azimuth ambiguity regions based on channel cancellation and the refocusing algorithm; and suppressing a repetitive ambiguity image in imaging the echo of the multi-channel SAR system. The method weakens the influence of the original image on azimuth ambiguity extraction, improves the performance of ambiguity suppression, and solves the problem of additional repetitive ambiguity in multi-channel SAR systems by reconstructing the ambiguity signal, and improves the image quality of the multi-channel SAR system, which has great value for subsequent applications such as SAR image interpretation.

The invention discloses a high-feature-resolution underwater weak target parameter estimation method based on NOMP, and the method comprises the steps: obtaining a receiving array signal, carrying out the preprocessing of the receiving array signal, carrying out the azimuth angle estimation through employing a conventional beam forming algorithm, and extracting a beam output signal in a main target direction; rough search is carried out on discrete time delay and Doppler factor grids, initial parameters of a current most significant path are estimated, continuous optimization is carried out through a Newton iteration method, and optimized path parameters are obtained; constructing a continuous path echo signal according to the received signal, deducting the contribution of the current path to the received signal from the received signal, updating a residual signal, and continuously searching the next path by taking the residual signal as a new input signal until an iteration termination condition is met; and outputting parameter estimation results of all paths. According to the method, high-precision and high-resolution extraction of weak target parameters can be realized in an environment with a low signal-to-noise ratio and remarkable underwater multipath interference.

Techniques for detecting radar data inaccuracies using a multistage filtering technique are discussed herein. A vehicle may capture radar data including a set of radar points. The vehicle can input the radar data into a machine-learning model configured to detect objects and / or generate bounding boxes associated with such detected objects. In some instances, the vehicle may cluster the radar points such that a cluster includes the radar points located proximate to and / or within a bounding box. To identify double bounce object detections, the vehicle may determine whether a detected object is a false-positive double bounce object detection based on evaluating the azimuth, range, and relative velocity double bounce criteria. Based on the detected object satisfying the double bounce criteria for azimuth, range, and relative velocity, the vehicle may modify the radar data.

The invention relates to the technical field of signal analysis, in particular to a GNSS (Global Navigation Satellite System) detection method and system based on machine learning, and the method comprises the steps: receiving a navigation radio-frequency signal containing reality and deception, and carrying out the down-conversion of an RF (Radio Frequency) front end to obtain intermediate-frequency data; gNSS signal capture is completed by searching correlation peaks in frequency and code phases based on intermediate frequency data; in the capturing stage, a motion state, a correlation peak number, a noise value, capturing parameters and peak + / -1 chip sampling features are extracted and input into a machine learning classification model to judge whether cheating exists or not; if so, separating the deception signal from the real signal, and respectively sending the deception signal and the real signal into independent tracking channels; measuring an array element carrier relative phase by an array antenna, establishing a phase center model, and correcting to obtain an effective phase center and a differential baseline; according to the method, a deception azimuth angle and a pitch angle are obtained, a beam weight is calculated, a deception direction is subjected to null setting, a real direction is subjected to main lobe protection, and a weight value is fed back in real time to improve a signal carrier-to-noise ratio and locking stability. According to the invention, the problem that the existing commercial GNSS signal is low in power and easy to be interfered by deception is solved.

The invention relates to the technical field of environmental shadow analysis, and discloses an environmental shadow analysis method for photovoltaic power station design, which comprises the following steps: collecting and preprocessing geographic space data of a photovoltaic power station; calculating a solar altitude angle and an azimuth angle based on the pre-processed parameters, and generating a three-dimensional solar direction vector; analyzing the geometric surface of the three-dimensional obstacle model, screening a visible surface patch according to a sun direction vector, and sampling effective projection points; dynamically updating the sun direction vector in a specified time period, and calculating shadow coordinates of projection points on the ground or an inclined plane in each time period; and generating shadow contours of all time periods and combining the shadow contours into a complete influence area. According to the invention, through the dynamic sun trajectory modeling and complex obstacle surface analysis technology and in combination with the multi-modal projection correction and Boolean operation merging strategy, high-precision analysis of shadow spatial-temporal distribution in a complex environment, multi-installation scene self-adaption and dynamic shielding influence quantitative evaluation are realized.

The invention discloses a wireless optical communication alignment system and a capture alignment method thereof, and relates to the technical field of optical communication, and the method comprises the steps: a three-dimensional holder carries out the coarse alignment of an optical path between a transmitting end and a receiving end according to the direction of beacon light; an alignment device located at the top of the three-dimensional holder carries out fine alignment on the light path; the alignment device comprises a two-dimensional alignment structure, a control circuit and a device shell. The control circuit captures a light intensity feedback value of the light intensity sensor of the two-dimensional alignment structure, and adjusts an azimuth angle and a pitch angle of the optical fiber collimator of the two-dimensional alignment structure according to the light intensity feedback value so as to adjust lens orientations of the transmitting end and the receiving end; the device shell provides a supporting platform for the two-dimensional alignment structure and the control circuit and is connected with the three-dimensional holder. Coarse alignment and fine alignment are combined, accurate angle adjustment is achieved through light intensity feedback, efficient alignment of light paths of the transmitting end and the receiving end is ensured, meanwhile, the device shell provides stable support and connection, and the stability and reliability of the alignment process are guaranteed.

The invention discloses an under-forest terrain extraction method, system and device based on an interference radar image and a medium. The method comprises the following steps: obtaining double-station InSAR data, and carrying out interference processing and correction; carrying out azimuth sub-aperture decomposition on the original InSAR image to obtain sub-view SAR images under different frequency spectrums; performing coherence amplitude correction on the complex coherence coefficients of different sub-view SAR images, reconstructing the complex coherence coefficients, and spreading the complex coherence coefficients to a complex plane; performing gross error elimination and least square coherent straight line fitting on the spread points in the complex number unit circle to obtain phase information of two intersection points of the coherent straight line and the unit circle; according to the effective vertical wave number and the phases of the two intersection points, one is judged as a ground surface phase point; and recombining the obtained earth surface phase and the corrected coherence amplitude into a new complex coherence coefficient, and further obtaining the elevation information of the terrain under the forest according to the new complex coherence coefficient. And under-forest terrain extraction of a forest area can be realized without depending on assistance of other external data products.

The invention relates to the technical field of radar detection, and provides a multi-model filtering target positioning method, system, device, product and medium, and the method comprises the steps: determining a model matching parameter, carrying out the initialization assignment, obtaining an initialization parameter, and obtaining a sampling point set and a weight coefficient through the initialization parameter; performing state one-step prediction to obtain a state one-step prediction value, and performing secondary sampling and measurement one-step prediction to obtain an autocorrelation covariance and a mixed covariance; carrying out SVD operation to obtain a decomposition value set, detecting a target by a target radar to obtain a radar detection value, obtaining a Kalman gain matrix according to the mixed covariance, and calculating state estimation and an initial covariance; updating the model probability to obtain a Markov transition probability, and normalizing the Markov transition probability to obtain a normalized probability; and state estimation and target covariance are obtained through state fusion, so that the target orientation is determined. According to the invention, accurate tracking of the high maneuvering target is realized.

The invention relates to the technical field of unmanned aerial vehicle communication anti-interference, in particular to an unmanned aerial vehicle anti-interference system based on spectrum sensing. According to the invention, a spectrum sensing data acquisition module acquires multi-band frequency spectrum signal data and generates a spectrum interference characteristic spectrum; the interference source positioning module calculates an azimuth angle and a distance of an interference source and generates a spatial distribution data set; the three-dimensional interference field construction module constructs a three-dimensional interference field model containing an interference intensity gradient and a propagation direction in combination with the real-time height and geographic coordinates of the unmanned aerial vehicle; the anti-interference strategy generation module analyzes the vulnerability of a communication link, and dynamically adjusts the frequency band switching priority and the transmitting power allocation weight; the beam forming control module calculates antenna array phase offset and a beam pointing angle, and generates an adaptive beam forming parameter set. The system can improve the anti-interference capability and communication stability of the unmanned aerial vehicle in a complex electromagnetic environment.

The invention discloses a phased array receiving beam resource allocation method for satellite communication, which relates to the technical field of satellite communication, and comprises the following steps: acquiring satellite position, user position and satellite attitude data, calculating an azimuth angle and a pitch angle of a propagation path, querying a pre-stored dark matter density distribution database of a satellite-borne memory, and calculating a pre-stored dark matter density distribution database of the satellite-borne memory; extracting a dark substance density value; according to the user service priority and the real-time channel quality, a beam resource proportion is adjusted in a resource allocation table, and a beam scheduling instruction is generated; and executing the beam scheduling instruction, driving the state switching of the millimeter wave phased array phase shifter, monitoring the change rate of the signal-to-noise ratio of the user terminal, and re-calculating the azimuth angle and the pitch angle of the propagation path when the continuous change rate of the signal-to-noise ratio exceeds a preset change rate threshold. According to the method, a space-borne pre-stored dark matter density database is inquired, a phase disturbance value is calculated, and the cosmic scale dark matter physical field effect is brought into a beam control closed loop.

The invention discloses a self-stabilization control photoelectric tracking rotary table and method based on a rate gyroscope. The method comprises the following steps: respectively acquiring an azimuth compensation angular velocity and a pitching compensation angular velocity of the photoelectric tracking rotary table under a rotary table coordinate system and a roll angular velocity interference variable of the photoelectric tracking rotary table under a platform coordinate system through the rate gyroscope; constructing a rotation matrix, converting the roll angular velocity interference variable of the photoelectric tracking rotary table under the platform coordinate system into the roll angular velocity interference variable of the photoelectric tracking rotary table under the rotary table coordinate system, and performing Kalman filtering processing to obtain the optimal estimated angular velocity of the photoelectric tracking rotary table; and obtaining the control quantity of the photoelectric tracking turntable according to the optimal estimated angular velocity, and adjusting the control voltage of the photoelectric tracking turntable. According to the method, the process noise covariance matrix and the observation noise covariance matrix are updated by using the adaptive noise covariance matrix, so that the problem of filtering divergence or estimation lag caused by the fact that Kalman filtering adopting fixed noise covariance parameters is difficult to adapt to a dynamic environment is avoided.