10 results about "Radar resolution" patented technology

The present disclosure provides a method, a device, an electronic apparatus, and a storage medium for object classification and relates to the technical field of radar sensors. The method comprises: identifying a plurality of objects using a hybrid radar sensor; determining the nearest object to a target object, as well as determining a first polar coordinate corresponding to the target object and a second polar coordinate corresponding to the nearest object; calculating a distance difference and an angular difference between the target object and the nearest object based on the first and second polar coordinates; determining a Gaussian distribution function of the target object in the polar coordinate system using a preset variance of a Gaussian distribution; and calculating a probability result based on the distance difference, the angular difference,Using radar resolution and the Gaussian distribution function, the target object and the nearest object are identified as the same object, and a classification result of the target object is determined based on the probability result. Through the Gaussian variance, the present disclosure achieves the output of an object classification probability in a hybrid radar sensor, which ensures computational efficiency and simultaneously expands the application scenarios of the radar.

The present invention relates to a method for calculating the effective detection distance of a lidar along the entire tunnel route, a device, and a medium. The method comprises: performing tunnel modeling on the basis of as-built drawings for post-construction survey of a track; and calculating the effective detection distance of a radar at each point on the track on the basis of an established tunnel model, wherein the calculation comprises: setting a certain point as a starting point, and the center of an object in a tunnel cross-section at a first set distance from the point as an end point; calculating, within the distance from the starting point to the end point, included angles between the lines connecting all tunnel points to the starting point and the line connecting the starting point to the end point; if there is an included angle smaller than the radar resolution, setting a point obtained by moving the end point back toward the starting point by a set distance as a new end point; and then repeating the calculation process until within the distance from the starting point to the end point, the included angles between the lines connecting all the tunnel points to the starting point and the line connecting the starting point to the end point are all greater than the radar resolution, and in this case, the distance from the end point to the starting point is the effective detection distance at the starting point. Compared with the prior art, the present invention has the advantages of high calculation precision.

This invention relates to the field of radar testing technology, and provides a passive calibrator and calibration method for radar penetration detection within a medium. The passive calibrator includes: a calibration element, a connecting rod, and lifting rings. The calibration element is configured to be disposed inside the penetrating medium, and includes a mounting base and reflectors. Multiple reflectors are arranged circumferentially along the central axis of the mounting base, with one end of each reflector connected at the central axis, forming a reflecting surface between adjacent reflectors. Two calibration elements are provided, with both ends of the connecting rod connected to the two calibration elements respectively. Two lifting rings are provided, located at the ends of the two calibration elements furthest from the connecting rod. The passive calibrator for radar penetration detection within a medium provided by this invention avoids the influence of surface scattering on the calibration results, enabling omnidirectional acquisition of the radar signal reflected by the calibrator. It also verifies the internal penetration detection resolution of the radar detection system, achieving a combined function of calibration and radar resolution verification.

This invention discloses a 3D scanning lidar, a lidar scanning method, and an unmanned forklift. The method establishes a mathematical model of the relationship between rotational speed and the spatial angular distribution of a point cloud. It fixes the spindle rotational speed r1 and adjusts the high-speed rotational speed r2 to form a non-integer proportional motion, achieving non-repetitive scanning to generate a uniform point cloud. Based on the model, it calculates the point cloud uniformity index δS, generates a feature map, and selects the optimal rotational speed to support switching between uniform, progressive, or repetitive scanning modes. Furthermore, through pre-calculated gyro effect compensation and bidirectional laser arrangement, it forms a cross-shaped oblique grid, improving boundary recognition accuracy; adjusting the ratio of r1 to r2 controls the grid angle, achieving acute, right, or obtuse angle grids. This invention overcomes the problems of traditional radar resolution being limited by the number of modules, slow coverage speed, and complex control. Through open-loop control and dynamic adjustment, it reduces cost and power consumption, improves point cloud density and task adaptability, and is applicable to fields such as autonomous driving and robotics.

The present application belongs to the technical field of geological disaster monitoring, and particularly relates to a method for dynamically measuring the velocity of a surface flow field of a debris flow in a complex environment based on radar and vision fusion. The method comprises: establishing a joint calibration model of a millimeter wave radar and a camera to achieve spatio-temporal alignment of data from heterogeneous sensors; collecting a video image sequence to calculate a dense visual velocity field; at the same time, constructing a high-confidence sparse radar velocity field from a millimeter wave radar CFAR point cloud; constructing an environment perception adaptive weight model to dynamically calculate a fusion weight based on image texture richness and radar signal-to-noise ratio, and to perform pixel-level weighted fusion and correction on the visual dense flow field and the radar sparse flow field, and finally obtaining a high-robustness velocity vector distribution. The present application effectively solves the problems of large interference of a single visual sensor by light, rain and fog, and low resolution and lack of texture information of a single radar, and realizes all-weather high-precision fluid velocity measurement.

The application discloses a kind of methods and systems for generating airborne radar low observable waveform facing uncertain target scattering characteristics, the method includes: based on spatial information interaction theory, the expected interaction information amount between target scattering signal and radar receiving signal of maneuvering target in state transition angle interval is constructed, from the angle of intercept receiver signal processing link, with the log-likelihood ratio expected value of intercepted signal and the interaction information amount between intercept receiver input and output signal, fusion construction intercept-identification joint performance evaluation index;Under the given transmitting power constraint, the frequency domain waveform multi-objective optimization model with the maximum radar expected interaction information amount and the minimum intercept-identification joint performance index as target is constructed, and is converted into convex optimization problem for solving;Based on random sequence step frequency modulation signal, the time domain waveform implementation mode satisfying the frequency domain optimization result is designed, and the performance of the designed waveform is verified;The application satisfies radar resolution performance.

The invention provides a device and method for detecting the resolution of a drill-borne laser radar, and relates to the field of laser radar performance detection, and the method comprises the steps: reproducing an extreme environment condition of a drilling site; the bionic target simulates a real rock stratum; laser radar signals are collected at high precision under extreme interference; the acquired signals are processed based on prior knowledge, and a resolution index is inverted; and based on the convolutional neural network, analyzing the resolution index to obtain a high-confidence resolution index, and carrying out intelligent grading evaluation on the detection precision of the laser radar. The problems that a traditional device cannot adapt to the extreme drilling environment and the detection result distortion rate is high are effectively solved, and accurate, reliable and intelligent detection of the laser radar resolution in a laboratory is achieved.

This invention discloses an optimization method for multi-aircraft formation cooperative deception jamming based on genetic algorithms, belonging to the field of electronic countermeasures technology. This method addresses the problems of discrete false targets generated by existing multi-aircraft deception jamming techniques, which are easily identified and filtered by radar networks. First, a system model including aircraft formation, radar network, and flight area is established. Then, a cooperative jamming evaluation model is constructed. By calculating the spatial distance between false target pairs generated by different aircraft against different radars and comparing it with radar resolution thresholds, the jamming effectiveness of the formation is quantified. Finally, using this evaluation model as the objective function, a genetic algorithm is used to iteratively optimize the spatial positions of multiple aircraft, searching for an aircraft formation scheme that maximizes the spatial overlap of false targets. This invention can automatically generate optimized aircraft formation positions, significantly improving the cooperative deception jamming effectiveness of multi-aircraft formations against radar networks.

The invention discloses a multi-machine formation collaborative deception jamming optimization method based on a genetic algorithm, and belongs to the technical field of electronic countermeasures. Aiming at the problem that false targets generated by multi-aircraft deception jamming in the prior art are discrete and are easily recognized and filtered by a radar network, the method comprises the following steps: firstly, establishing a system model comprising an aircraft formation, a radar network and a flight area; then constructing a cooperative interference evaluation model, calculating the spatial distance between false target pairs generated by different airplanes to different radars, and comparing the spatial distance with a radar resolution threshold to quantify formation interference efficiency; and finally, taking the evaluation model as a target function, carrying out iterative optimization on the spatial positions of multiple aircrafts by utilizing a genetic algorithm, and searching to obtain an aircraft formation scheme capable of enabling false targets to coincide in space to the maximum extent. According to the method, the optimized aircraft formation position can be automatically generated, and the cooperative deception jamming efficiency of the multi-aircraft formation to the radar network is remarkably improved.