113 results about "Envelope (radar)" patented technology

The invention discloses an unmanned aerial vehicle cluster cooperative control system and method, and relates to the technical field of unmanned aerial vehicle cluster control, and the system comprises a multi-source sensing unit, an integrated laser radar, an RGB-D camera and a millimeter wave radar array, and is used for generating a centimeter-level precision three-dimensional map and tracking a dynamic obstacle in real time; the collaborative decision-making unit comprises an artificial intelligence prediction module which is used for predicting a collision point based on the movement state of the obstacle; the safety space construction module is used for generating a dynamic safety sphere according to the formation envelope size and the obstacle volume; the artificial intelligence correction module is used for constructing a safety section and generating an optimization path; and the dynamic communication unit is used for carrying out cluster data interaction by adopting hybrid networking of 5G and LoRa adaptive switching. The unmanned aerial vehicle cluster can be used as a whole to avoid obstacles, the original forms of the unmanned aerial vehicles are synchronously kept, and it is guaranteed that multiple unmanned aerial vehicles in the cluster do not collide.

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 ISAR (Inverse Synthetic Aperture Radar) multi-pulse accumulation cross-correlation distance and phase correction system based on an FPGA (Field Programmable Gate Array). The ISAR multi-pulse accumulation cross-correlation distance and phase correction system comprises an upper computer and the FPGA, the upper computer is used for controlling the inverse synthetic aperture radar system to transmit a signal and receiving an echo signal; performing de-line frequency modulation on the echo signal to obtain an echo signal after pulse compression, and preprocessing the echo signal to obtain a to-be-processed echo signal; quantizing the echo signal to be processed, acquiring a quantized echo signal, transmitting the quantized echo signal to the FPGA, and receiving the distance returned by the FPGA and the echo signal after phase correction; and the FPGA is used for executing a multi-pulse cumulative cross-correlation envelope alignment algorithm to perform alignment processing on the quantized echo signal, obtaining a corrected echo signal and returning the corrected echo signal. The register transfer stage circuit based on the multi-pulse cumulative cross-correlation envelope alignment algorithm is designed based on the FPGA, high-parallelization acceleration based on the multi-pulse cumulative cross-correlation envelope alignment algorithm module is achieved, and the processing speed and efficiency of the algorithm are remarkably improved.

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 present application provides a pulse detection method for radar signals, which relates to the field of digital signal technology. The method includes: obtaining a digital time-domain signal corresponding to the radar signal, calculating the amplitude of the digital time-domain signal to obtain the signal amplitudes of each sampling point on the digital time-domain signal, performing a delay process on the signal amplitudes of each sampling point for a preset number of clock cycles, using the signal amplitudes of each sampling point after the delay to perform envelope detection on the digital time-domain signal to obtain the envelope signal of the digital time-domain signal, performing time-domain alignment on the digital time-domain signal and the envelope signal according to a preset number of clock cycles, finally calculating the pulse width of the digital time-domain signal based on the envelope signal after time-domain alignment to obtain the signal pulse width of the digital time-domain signal, calculating the signal amplitude of the digital time-domain signal according to the envelope signal after time-domain alignment and the signal amplitudes of each sampling point, and performing envelope detection on the digital time-domain signal, which can improve the detection accuracy of the signal pulse width and the signal amplitude.

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 radar signal gain method. The method comprises the following steps: S1, acquiring data bscan and preprocessing the data bscan; s2, absolute values of all the numerical values are obtained, and the maximum value is solved; s3, linearly connecting the maximum values to form an extreme value envelope A (i), performing inverse function on the extreme value envelope A (i) to obtain a gain function, and multiplying the original bscan by the gain function; s4, the maximum value hmax of the absolute value of each row is taken and connected to obtain a function H (t), Hilbert transform is carried out on H (t), and the signal is analyzed to take the absolute value to obtain an envelope signal; and S5, obtaining a coefficient M, taking the reciprocal of the A (t), multiplying the reciprocal by the coefficient M to obtain a gain function Wm ', and processing the two-dimensional data by using the gain function. According to the method, envelope gain is added when ground penetrating radar signals are processed, extreme value envelope is taken from each row of bscan, a gain function is obtained through Hilbert transformation, then the bscan is processed through the gain function, new bscan is obtained, undifferentiated amplification of all signals is prevented, strong gain is achieved for echo signals, and the adaptability and pertinence of an algorithm are improved.

Directional antenna for a motor vehicle radar system includes a housing comprising a reflecting envelope comprising an inner volume forming a reflecting cavity for electromagnetic waves, characterized in that the reflecting envelope is bounded by a set of walls including a first transmission wall comprising an electromagnetic wave transmission zone between the inside and the outside of the housing; a second guide wall, opposite the first wall, able to guide electromagnetic waves in a privileged direction; and a set of reflective lateral walls connecting the first and second walls, wherein each lateral wall is able to reflect the electromagnetic waves within the reflective cavity.

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.

The present invention discloses a radar point condensation method based on echo envelope detection, which comprises the following steps: receiving radar original detection point data; merging the detection points to form a plurality of point ambiguity regions; determining whether each point ambiguity region meets waveform resolution; performing azimuth resolution processing on the point ambiguity regions that meet waveform resolution to form one or more "small cluster" regions after resolution; performing range resolution processing on each "small cluster" region formed by azimuth resolution to form the final respective point regions; calculating the point positions condensed by each region according to the amplitude weighting method for the point regions, and outputting and saving the point information. The present invention solves the problems in the prior art that the point condensation algorithm cannot distinguish the echo overlapping situation, is prone to large deviations between the true position of the target and the condensed position, and only one point trace appears for multiple batches of adjacent targets, and improves the efficiency and accuracy of track tracking in complex environments.

The invention discloses a millimeter-wave radar falling detection method based on a lightweight neural network. The method comprises the following steps: S100, collecting an original signal of a millimeter-wave radar; s200, performing data preprocessing to obtain a speed-time atlas, and extracting a speed-time atlas envelope; s300, marking falling and getting-up actions, and establishing a falling detection data set; s400, building a neural network model; s500, training and testing the neural network model; and S600, carrying out logic discrimination on an output result of the neural network. In the scheme, the data set category and the data volume are enriched through original signal collection, the detection accuracy can be improved by performing envelope extraction on the speed-time spectrogram and reducing the dimensionality of the input data of the neural network and the specific data set, so that the neural network learns the data features, the high accuracy can be achieved under the small operand, and the detection accuracy is improved. The method is suitable for a millimeter wave radar environment with limited resources, and the accuracy and robustness of fall detection are further improved through logic discrimination.

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 invention discloses a method for estimating the occurrence time of typical separation events based on piecewise fitting, comprising the following steps: S1: Obtain a radar echo signal, and perform pulse compression on the radar echo signal to obtain a range profile signal; S2: Perform envelope alignment processing on the range profile sequence in the range profile signal; S3: Perform threshold detection on each range profile in the range profile signal, extract the peak information of the range profile, and obtain a range profile peak sequence signal; S4: Extract line segments by frames based on the range profile peak sequence signal; S5: Perform fusion processing on the line segments extracted in each frame, retain the line segments with a length greater than threshold one, and obtain a target sequence; S6: Estimate the separation time based on the fused line segment information and obtain the respective echo signals of the separated targets. The present invention can accurately reflect the occurrence time of the separation event and obtain the independent echo signals of each target after separation without the need for empirical estimation of the position and velocity of the separation point time.

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.