96 results about "Envelope (radar)" patented technology

The invention relates to a robot path planning method based on multi-sensor fusion and free space topology composition, and belongs to the technical field of robot autonomous navigation. The method comprises the following steps: firstly, fusing laser radar and millimeter wave radar data, constructing multi-modal point cloud data, extracting a three-dimensional obstacle boundary by combining depth and normal vector mutation features, and generating a three-dimensional obstacle map and a free region tree; according to the constructed space model, factors such as energy consumption, dynamic obstacles, path smoothness and the like are integrated, target selection weights are dynamically regulated and controlled, and self-adaptive screening of intermediate navigation targets is achieved. And based on the intermediate navigation target, generating a safe trajectory satisfying dynamic constraints by adopting geometric-dynamic dual-mode fusion modeling, and enhancing the feasibility and robustness of the trajectory through trajectory envelope optimization and pre-execution fault-tolerant control. The method can be widely applied to autonomous navigation systems such as mobile robots and unmanned vehicles, and has good environment adaptability and path execution stability.

The invention belongs to the technical field of radar signal processing, and discloses a sea surface small target detection method based on optimized characteristic mode decomposition, which comprises the following steps: S1, acquiring to-be-detected signal data; s2, decomposing an original signal into a plurality of modal components by using FMD, and selecting an envelope spectrum entropy as a fitness function; s3, performing global optimization on the fitness function in the FMD by using an SOS algorithm; s4, introducing a PSO algorithm to carry out local optimization on key parameters of the FMD; s5, components with low envelope spectrum entropy values and correlation coefficients larger than a threshold value are reserved; s6, extracting an envelope spectrum entropy and frequency band energy ratio feature from the screened modal components, introducing a Gini coefficient as a weighting factor, and constructing a GSEBE joint feature; and S7, inputting the entropy value of the envelope spectrum into a DELM classifier with a controllable false alarm, and realizing target detection based on comparison between a predicted value and a judgment threshold. According to the invention, the capability of distinguishing sea clutters and target echoes is enhanced, and more accurate classification detection is realized.

The invention discloses a lunar radar horizon tracking method based on a dynamic search center, and solves the problems that an existing method is high in dependence on artificial experience and low in processing efficiency, and the false horizon misjudgment rate is high due to lunar soil non-uniformity interference. Comprising the following steps: performing Hilbert transform on a radar signal to extract an envelope; based on historical horizon data, predicting a dynamic search center of a current channel through Gaussian weighted average and determining a search window; screening local maximum value points in the window as candidate points, and calculating signal intensity, smoothness and edge direction scores of the candidate points; selecting an optimal candidate point as a horizon position through multi-feature linear fusion; and according to the lunar soil interface form and the signal-to-noise ratio dynamic adjustment parameters, tracking and outputting a final horizon path one by one. According to the method, historical path constraints and local signal features are fused, the identification precision and robustness of the lunar soil layered interface in the complex electromagnetic environment are remarkably improved, and the method is suitable for radar data processing of lunar exploration tasks such as Chang'e 4 and the like.

The invention discloses an unmanned aerial vehicle channel inspection path optimization method based on dynamic environment perception, and relates to the technical field of unmanned aerial vehicle intelligent path planning. Comprising the following steps: establishing a three-dimensional environment model based on channel geographic information data and surveying and mapping point cloud data, and generating an initial routing inspection path set with a coverage range meeting requirements; predicting and generating an obstacle envelope sequence changing along with time by using a dynamic obstacle trajectory collected by an airborne radar and a camera, performing space-time superposition calculation on the obstacle envelope sequence and the initial inspection path, and removing path fragments conflicting with a future obstacle movement range to obtain an inspection path set after obstacle avoidance correction; and according to elevation information in the three-dimensional environment model, predicting a local area and a spatial range in which communication shielding may occur in the inspection path of the unmanned aerial vehicle, carrying out secondary correction on a path segment which is about to enter a communication shielding area, and outputting a corresponding flight height and speed sequence.

The invention discloses an active layer depth identification method based on an envelope fusion algorithm, and belongs to the technical field of seasonal frozen depth survey. The method comprises the following steps: optimizing survey line arrangement and radar frequency through field survey and ground temperature data, and collecting data by using a ground penetrating radar; performing background removal, gain compensation, band-pass filtering and time-depth conversion preprocessing on the data; then, a gravity center method and an edge detection method are adopted to extract a bottom interface track, and noise and abnormal values are effectively suppressed according to self-adaptive weighted fusion of signal definition and continuity; and finally, carrying out cross validation and error correction by taking the earth temperature 0 DEG C isotherm depth as a reference, outputting a continuous and smooth interface fusion curve with centimeter-level precision, and calculating the depth of an active layer. According to the method, the high-efficiency and lossless advantages of the GPR are kept, meanwhile, the limitation of traditional interpretation precision is broken through, and a practical technical scheme which can be directly used for designing parameter values is provided for engineering investigation of the permafrost region.

The invention relates to the technical field of radars, in particular to a weather radar distance resolution calibration method and system. The method comprises the following steps: collecting oversampling original baseband I / Q data of a point target in a plurality of continuous pulse periods; determining a pulse signal-to-noise ratio, and screening out effective pulses according to a threshold value; carrying out sub-sampling stage time alignment on the effective pulses based on cross-correlation analysis, and carrying out incoherent averaging on power module values of all the aligned pulses to generate an average pulse power envelope; converting the average pulse power envelope to a logarithm domain, and selecting discrete data points in a main lobe region; according to the discrete data points, a nonlinear least square method is adopted to carry out iterative fitting on the generalized Gaussian mathematical model, and a continuous analytic function describing the pulse envelope is obtained; according to the continuous analytic function, determining a pulse time width when the power is reduced to a peak value of-6dB; and determining the real distance resolution according to the pulse time width. The measurement robustness is improved, and sub-meter calibration precision is achieved.

The invention relates to the technical field of electromagnetic wave detection and imaging, and discloses a radar target echo generation method based on a physical information neural radiation field, which effectively improves the physical consistency of generated echo signals, accurately simulates the energy attenuation characteristics at different observation angles, and improves the radar target echo generation efficiency. The problem of signal completion under the sparse view angle condition is solved. The signal generated by the method is highly matched with measured data in the aspects of amplitude distribution, phase continuity and energy envelope form, a reliable data basis is provided for radar target identification and feature analysis, and the perception capability of a network on target geometric details is enhanced through high-dimensional position coding. Therefore, the generated echo signal can accurately reflect the spatial distribution characteristics of the scattering center. Meanwhile, due to the introduction of the multi-frequency coding sequence, the network can adaptively capture electromagnetic scattering characteristics under different scales, and a reliable technical means is provided for echo generation of a complex target.

The invention discloses a ground penetrating radar adaptive gain method comprising the following steps: S1, selecting a to-be-gained radar data profile, and obtaining the overall attenuation trend; s2, acquiring an analysis signal; s3, calculating the envelope of each column of signals and the average value of each row of the envelope matrix; s4, fitting an average value of each row of the envelope matrix according to a least square method and a model function to obtain an attenuation coefficient; and S5, obtaining a gain coefficient through the attenuation coefficient, and gaining each column in the radar data profile in the step S1 based on the gain coefficient. The method has the beneficial effects that the gain process and the calculation method have a good gain effect on original data acquired by ground penetrating radars with different frequencies under different working conditions, and parameter setting is not needed, so that the signal-to-noise ratio and the image definition of radar signals in the whole effective depth range are improved.

The invention provides a translation compensation method for an inverse synthetic aperture radar image of a non-cooperative target, and relates to the technical field of radar signal processing and radar imaging, and the method comprises the steps: carrying out the calculation of a target motion and a radar echo signal based on the inverse synthetic aperture radar image of the non-cooperative target, and obtaining a receiving signal; filtering the received signal to obtain a high-resolution range profile sequence; obtaining a motion offset prediction model by using a spatial feature extraction module and a time sequence decoding module; processing the high-resolution range profile sequence by using the trained motion offset prediction model to obtain a translation offset estimation sequence; and constructing a translation compensation item by using the translation offset estimation sequence, performing translation compensation on the compressed echo to obtain a translation compensation result, and completing envelope and phase joint compensation and inverse synthetic aperture radar imaging. According to the method, the problem of translational motion compensation caused by uncertainty and complexity of a non-cooperative target motion mode is solved.

The invention discloses a ground-based radar space object long-time energy accumulation method based on an orbital element model, and the method comprises the following implementation steps: 1, building an orbital element parameter space, and mapping the grid points of the parameter space into the distance between a target and a radar; and step 2, calculating an envelope position and a phase which need to be compensated according to the mapped distance history at each parameter space grid point. And step 3, compensating a corresponding phase for the echo signal after pulse compression along the calculated envelope position, and then performing coherent superposition, thereby realizing long-time coherent accumulation of echo energy. According to the method, the orbital elements are adopted to construct the parameter space, energy accumulation is carried out in the parameter domain, due to the fact that the orbital elements can better represent the actual motion of a space object, the energy accumulation effect can be improved, meanwhile, the orbital elements are small in parameter space dimension, and the algorithm calculation amount can be greatly reduced.

The application provides a PMEPR optimization method of a large-bandwidth OFDM radar communication integrated waveform, and the method is based on a reserved subcarrier method, an l p norm is introduced to remodel PMEPR under a high reservation rate as a target function that can be used for gradient analysis, the PRP conjugate gradient descent method is used to efficiently and quickly solve the target function, and the radar communication integrated waveform with good PMEPR reduction performance is obtained. The application has an important role in the actual application of the radar communication integrated waveform.

The invention discloses a rotor unmanned aerial vehicle micro-motion parameter estimation method, which comprises the steps of performing pulse compression on radar echoes of a rotor unmanned aerial vehicle, and taking slow time data of a distance envelope peak value position as an observation signal of sparse reconstruction; constructing a dictionary matrix based on observation signals, and converting a micro-Doppler parameter estimation problem into a sparse reconstruction problem; and on the basis of the dictionary matrix, utilizing a Bayesian sparse reconstruction algorithm to estimate the rotation frequencies of a plurality of rotors of the rotor unmanned aerial vehicle. The method is applied to the field of radar signal processing, can perform parameter estimation on a plurality of micro-Doppler signals in an aliasing state in a noise environment, has the advantages of high estimation precision and good robustness, can be widely applied to searching and monitoring of air rotor type unmanned aerial vehicle targets, and has wide application prospects. The method can be effectively suitable for micro-motion parameter estimation of the hovering unmanned aerial vehicle under the low signal-to-noise ratio.

The invention discloses a distributed radar target detection method and device based on space-time unified compensation, and the method comprises the steps: determining a slope distance process expression between each radar in a distributed radar and a target object for each echo signal group; based on the slant range process expression, respectively constructing an envelope range walking correction function and a frequency domain phase compensation function between radars; according to the to-be-solved parameters of the target object and the parameters of the target radar corresponding to the echo signal group, respectively constructing a range walk correction function and a time domain phase compensation function in each radar; constructing a space-time two-dimensional compensation function according to the envelope range walk correction function, the frequency domain phase compensation function, the range walk correction function and the time domain phase compensation function; the phase-coherent accumulation echo signal expression constructed according to the space-time two-dimensional compensation function and the to-be-solved parameters of the target object is solved, the parameter target value of the target object can be obtained, and the target detection accuracy of the distributed radar is improved.

The invention provides a same-measuring-point rockfill material grading upper envelope line prediction method and device, electronic equipment and a storage medium, and relates to the technical field of engineering geophysical exploration, and the method can realize the nondestructive detection of the initial quality of each particle group in a same-measuring-point rockfill material by using a surface image and a ground penetrating radar profile map in combination with a standard radar map. And the grading upper envelope line is calculated by adopting the maximum dry density, so that the obtained grading upper envelope line is closer to the real crushing and grading evolution state of the rockfill material. Moreover, the method adopts a nondestructive testing mode to predict the grading upper envelope line of the rockfill material at the same measuring point, the amount of data required to be detected is small, the calculation model is clear, the prediction efficiency can be improved, the prediction cost can be reduced, the influence on the construction progress of the dam can be avoided, the interference on the grading upper envelope line caused by introduction of human factors can be avoided, and the prediction accuracy is improved. And the accuracy of the grading upper envelope line is improved.

A method that exhibits the following: Providing a digital radar signal (y[n]) by means of a radar receiver, wherein the digital radar signal (y[n]) comprises a plurality of segments; Calculating an envelope signal (x env [n]), which represents the envelope of a segment of the digital radar signal (y[n]); Determining a time (n1) of the start of an interference signal contained in the segment of the digital radar signal (y[n]), wherein the determination comprises the following: Determining a statistical parameter (µ[n], σ[n]) of the envelope signal (x env [n]) for a plurality of successive time indices of the envelope signal (x env [n]); Calculate at least one threshold value (µ[n] + λ · σ[n], ​​λ · σ) based on at least one statistical parameter (µ[n], σ[n]), Detecting a time index (n1) representing the time of onset of an interference signal, based on a comparison of the envelope signal (x env [n]) with at least one threshold value (µ[n] + λ · σ[n], ​​λ · σ).

The present application relates to a method and apparatus for imaging maritime targets, belonging to the field of image processing, and addresses the problem of the dynamic characteristics of multiple targets in maritime interference scenarios reducing the focusing effect. The method comprises: performing range-direction pulse compression on the echo signal of the SAR radar; performing envelope alignment on the echo data after pulse compression; transforming the envelope-aligned data into the frequency domain for image pre-autofocusing processing; performing target classification and local autofocusing on the echo data after image pre-autofocusing processing; and imaging based on the echo data after local autofocusing. The technical solution provided by the present application can improve the focusing effect of SAR images, thereby improving the accuracy of SAR imaging.

The application relates to the technical field of radar imaging, in particular to an effective vehicle-mounted SAR-BP motion compensation method, which comprises the following steps: obtaining echo signals, performing pulse compression on the echo signals based on transmission signals to obtain distance domain signals of SAR; selecting a reference strong point in the distance domain signals, performing upsampling processing on the reference strong point through interpolation to obtain a distance migration curve of the reference strong point; calculating a reference envelope offset correction factor, then estimating envelope offset correction factors of each distance gate, performing envelope offset correction on the distance domain signals to obtain signals compensated for slant range error; calculating a residual phase compensation factor, performing residual phase error correction on the signals compensated for slant range error to obtain signals compensated for residual phase; and performing imaging on the signals compensated for residual phase by using a BP algorithm to obtain a SAR image. The method reduces memory occupation, shortens calculation time consumption, has stronger universality and higher precision, and improves imaging quality.

Embodiments of the present specification provide a cooperative target ISAR envelope alignment method and system, the method comprising obtaining a baseband echo of a target to be measured by a radar, compressing the echo to obtain a one-dimensional range image; using prior information of the cooperative target to perform coarse envelope alignment on the obtained one-dimensional range image to obtain a one-dimensional range image sequence after coarse envelope alignment; selecting an arbitrary one-dimensional range image after coarse alignment, determining the envelope shift amount of the previous one-dimensional range image, and determining the reference shift amount; performing a shift in the vicinity of the reference shift amount by a search method, performing cross-correlation calculation with the previous one-dimensional range image, and calculating a correlation coefficient; based on the setting of the shift range, performing traversal of the one-dimensional range image shift until the end of the traversal, determining the shift amount corresponding to the maximum correlation coefficient as the shift amount of the one-dimensional range image, and realizing envelope alignment of the one-dimensional range image. The problem of large amount of calculation and easy jumping of the alignment result in the prior art is solved.

The application belongs to the technical field of radar signal processing, and specifically discloses a method for detecting airspeed targets based on long-time accumulation, which comprises the following steps: firstly, segmenting the echo signals after pulse compression according to the number of pulses, and compensating the distance migration and Doppler spread of the envelope of the echo signals in each segment; secondly, performing in-segment coherent accumulation on the compensated results in each segment; and finally, performing envelope migration and non-coherent accumulation between segments on all the echo signals, so that the energy of the echo signals can be effectively accumulated. The long-time accumulation method of time segmentation, in-segment coherent accumulation and inter-segment non-coherent accumulation can solve the problems of long-time coherent accumulation calculation and echo signal coherent deterioration, improve the detection performance, and is easy to implement in engineering.

The invention relates to an expandable rotating paraboloid double-reflector system SAR (Synthetic Aperture Radar) antenna, belongs to the technical field of spacecraft antennas, and solves the technical problems that the expandable rotating paraboloid double-reflector system SAR antenna is large in folding envelope and low in profile precision. The SAR antenna comprises a reflector and a phased array feed source device, the reflector comprises a main reflector body, an auxiliary reflector body and a conical force bearing barrel, the main reflector body is of a rotating paraboloid structure after being unfolded, the auxiliary reflector body is located on the inner side of the rotating paraboloid structure and connected with the main reflector body through the conical force bearing barrel, and the conical force bearing barrel is connected with the main reflector body. The phased array feed source device is arranged in the conical force bearing barrel, the phased array feed source device comprises a horn radiation unit, a T / R assembly and a heat conduction table, the cross section of the heat conduction table is of an axial symmetry structure shaped like a Chinese character'ji ', and the phased array feed source device is fixedly connected with an upper cabin plate of a load cabin of a satellite through the bottom face of a heat conduction table unit. The SAR antenna is high in precision, small in size, good in heat dissipation effect and high in stability.

The application discloses a kind of active layer depth identification method based on envelope fusion algorithm, belong to season frozen depth survey technical field, the present application is through field reconnaissance and ground temperature data optimization survey line arrangement and radar frequency, and with ground penetrating radar data acquisition;Data are removed, gain compensation, band-pass filtering and time-depth conversion preprocessing;Then using barycentric method and edge detection method extract bottom interface track, and according to signal definition and continuity adaptive weighted fusion, effectively suppress noise and abnormal value;Finally, with the depth of 0 ℃ isotheral line as benchmark, cross validation and error correction are carried out, and the interface fusion curve of continuous, smooth and centimeter-level precision is output, to calculate the depth of active layer.The method breaks through the traditional interpretation precision limit while maintaining the high-efficiency and non-destructive advantage of GPR, and provides a practical technical solution for the design parameter selection in permafrost engineering investigation.

This invention provides a multi-scale fusion-based method for target recognition and localization using lidar point clouds, belonging to the field of lidar data processing technology. This method employs a cascaded architecture of "macro-meta-micro." At the macro level, topological dimensionality reduction is performed, including constructing a dynamic secure envelope, rapidly stripping massive background point clouds using the surround number method, and clustering foreground targets by introducing radial compensation coefficients. At the meso level, probability peak finding is performed, including transforming the point cloud to a spherical coordinate system, constructing a probability density function of radial distance, and finding the peak to accurately pinpoint the target depth layer. At the micro level, complex plane optimization is performed, including constructing a multi-index joint optimization loss function mapped to the complex plane to achieve high-fidelity extraction and verification of target geometric features. This invention significantly reduces computational overhead and improves the accuracy and robustness of target recognition and localization in long-range and noisy environments.

This invention relates to the field of elevator technology, and more particularly to an anomaly detection method for elevator polyurethane buffers based on millimeter-wave radar. The method includes: acquiring echo signals within a preset time window after the polyurethane buffer's compression and rebound by millimeter-wave radar; determining the target distance unit and generating a vibration displacement signal in the radar's line-of-sight direction; identifying intervals where the overall vibration envelope shows a decaying trend and extracting the damping response signal; implementing bistable stochastic resonance enhancement and variational mode decomposition to identify the target modal signal; calculating damping characteristic indices using the target envelope amplitude and stiffness characteristic indices using the target phase to construct a health feature vector; and determining whether the obtained health feature vector lies within the constructed health reference space. Using non-contact millimeter-wave radar to acquire echo signals during the polyurethane buffer's rebound process allows for precise capture of phase changes caused by minute movements or vibrations of the target, resulting in high detection efficiency and safety.

The application discloses a multi-source sensing-based anti-collision early warning system for power distribution network construction machinery, and relates to the technical field of image analysis, which comprises the following steps: obtaining laser radar point cloud data and camera image data, obtaining laser radar distance and visual distance respectively, and performing consistency determination; when there is inconsistency, determining the reference sensor and the sensor to be adjusted by analyzing the visual recognition influence value and the radar response influence value, performing dynamic parameter adjustment on the sensor to be adjusted, obtaining the target distance based on the re-measured distance value and the reference measured distance fusion, thereby constructing a dynamic envelope volume, calculating the net safety distance, and outputting an anti-collision early warning signal, which effectively solves the problem that multi-source sensing data deviates and is inconsistent under complex environmental interference in the prior art, resulting in a decrease in distance detection reliability and affecting anti-collision early warning precision.

The application discloses a multi-radar power envelope fusion method, comprising: single-radar envelope modeling, constructing envelope fusion foundation; determining non-coherent field fusion, constructing multi-radar envelope model; constructing gradient diffusion model, realizing envelope fusion smooth transition; displaying Euler method iteration convergence, realizing multi-radar envelope complete fusion; adopting adaptive octree structure to dynamically divide three-dimensional space. Advantageous effects: the multi-radar power envelope fusion method firstly calculates single-station detection probability of each radar unit at a grid point in a three-dimensional space voxel according to a radar equation, a propagation loss model and target scattering characteristics; then adopts a probability union or a more complex dependent relationship model to generate a full-space joint detection probability field; finally, an isosurface extraction (such as an improved Marching Cubes algorithm) and a probability gradient driven color / transparency mapping are adopted to generate a visual continuous, mathematically accurate fusion envelope surface.

The present application relates to the field of radar technology, especially to a weather radar range resolution calibration method and system. The method comprises the following steps: collecting oversampling original baseband I / Q data of a point target in multiple pulse periods; determining pulse signal-to-noise ratio, and screening effective pulses according to a threshold value; performing time alignment of the effective pulses in a sub-sampling stage based on cross-correlation analysis, performing non-coherent average of power modulus of all the aligned pulses, and generating an average pulse power envelope; converting the average pulse power envelope to a logarithmic domain, and selecting discrete data points located in a main lobe region; using a nonlinear least squares method to iteratively fit a generalized super-Gaussian mathematical model according to the discrete data points, and obtaining a continuous analytical function describing the pulse envelope; determining a pulse time width at which the power drops to a peak value-6dB according to the continuous analytical function; and determining a real range resolution according to the pulse time width. The measurement robustness is improved, and the calibration accuracy is sub-meter.

The invention discloses a Parkinson's disease gait feature extraction method, gait recognition method and system based on a millimeter wave radar, and the method comprises the following steps: collecting a millimeter wave radar signal, carrying out the preprocessing of the signal, and obtaining a Doppler spectrum and a distance spectrum of the signal; extracting a trunk velocity curve from the Doppler spectrum of the signal by using an adjacent column constraint rule, extracting a trunk position change curve from the distance spectrum, and extracting basic gait information from the trunk velocity curve and the trunk position change curve; an envelope speed curve corresponding to sample movement is extracted from the Doppler spectrum, and key gait features are screened out in combination with basic gait information. The method does not depend on a multi-sensor wearing system, and typical motion difference characteristics of the Parkinson's disease patient are fully revealed through targeted modeling of gait detail characteristics.

The embodiment of the invention discloses a ground penetrating radar signal processing method for obtaining the thickness of a black soil layer, and the method comprises the steps: carrying out the detection in a detection region through a ground penetrating radar, and obtaining an original ground penetrating radar signal of each measurement point; the method comprises the following steps of: after preprocessing an original signal, decomposing the original signal into a plurality of intrinsic mode function components by adopting a variational mode decomposition method; and based on the time-frequency distribution characteristics of each component, eliminating noise components to obtain a de-noised signal, and determining the time domain position of the interface of the black soil layer by identifying a sudden change peak of an instantaneous frequency curve of the de-noised signal. And performing Hilbert transform on the preprocessed signal to obtain an envelope signal, determining the dielectric constant of the black soil layer according to an average envelope amplitude by combining a dielectric constant model, and calculating the propagation speed of the electromagnetic wave in the black soil layer. Determining the thickness of the black soil layer at each measuring point according to the time domain position of the interface of the black soil layer at each measuring point and the corresponding electromagnetic wave propagation speed; and based on the black soil layer thickness of each measuring point, black soil layer thickness distribution data of the detection area is generated through a spatial interpolation method.

This invention belongs to the field of obstacle avoidance technology for bucket wheel excavators, specifically a lidar system for obstacle avoidance in bucket wheel excavators. It includes a ground point cloud recognition module, a working material pile recognition module, a candidate target clustering module, an obstacle attribute determination module, and a safety control module. The system identifies the ground point cloud by performing height gradient analysis on the point cloud in the bucket wheel excavator's working area. Then, it predicts the material pile envelope based on the cantilever attitude and defines the point cloud on the material pile surface by combining surface continuity and the angle of repose, thereby structurally separating the ground, material pile, and residual point cloud. After eliminating the former two, the residual point cloud is three-dimensionally clustered to obtain candidate target clusters. By comparing the difference in reflection intensity and spatial relationship between the candidate clusters and the material pile surface, real obstacles are identified through multi-dimensional logic determination. Finally, kinematic collision detection is performed on the obstacles, and avoidance, deceleration, or stopping commands are generated according to the collision level, ensuring that alarms are only triggered for real, stable obstacles.

The application relates to a dynamic absolute distance measurement method based on sinusoidal frequency modulation interference and relates to the field of laser radar phase demodulation technology. The application is aimed at solving the problems of low precision and limited measurement range of the existing absolute distance measurement method. The dynamic absolute distance measurement method based on sinusoidal frequency modulation interference comprises the following steps: inputting light signals emitted by a sweep frequency light source into a first coupler, so that the light signals are divided into two light signals; inputting the two light signals into a measurement interferometer and an auxiliary interferometer respectively; compensating the asymmetry of output signals by using an ellipse fitting algorithm; extracting the phases of the measurement interferometer and the auxiliary interferometer signals with high precision by using an inverse tangent and unwrapping operation; filtering the phase of the measurement interferometer; directly calculating the relative displacement of a target by using the low-frequency part; calculating the envelope of the signal by using the high-frequency part; calculating the envelope of the phase of the auxiliary interferometer; and finally calculating the absolute distance of the target by taking the ratio of the two envelopes and eliminating the influence of modulation bandwidth fluctuation.