7 results about "Systematic error" patented technology

The invention relates to the technical field of radar remote sensing, discloses a high-order loose body historical activity detection method based on multi-source DEM data, and aims to solve the problem that the historical activity of a high-order loose body in a glacier coverage area is difficult to accurately and quantitatively evaluate in the prior art. The scheme mainly comprises the steps that drainage basin units are automatically divided based on DEM data, and glacier influence areas are screened; multi-source DEM data are fused, and system errors are eliminated through geographic positioning deviation correction, elevation distortion deviation correction and track mode deviation correction; establishing a penetration depth physical model, and correcting the radar penetration depth in the glacier area by using the C / X wave band elevation difference optimization parameter; calculating an elevation change rate by adopting robust regression; and calculating an activity comprehensive index by integrating multiple factors, and identifying a hot spot region and a time period through probability estimation and spatio-temporal clustering. According to the method, automatic and high-precision quantitative evaluation on the historical activity of the high-position loose body is realized, and the method is particularly suitable for geological disaster early warning and risk evaluation in high mountain areas.

The invention discloses a resource evaluation method and system based on multi-landform feature correction, which remarkably improves the accuracy of wind speed and solar radiation data by combining physical constraint correction and machine learning methods, and particularly improves the accuracy of the wind speed and solar radiation data under the conditions of complex terrains and multiple earth surface types. The problem of systematic errors existing in ERA5 reanalysis data in the prior art is solved. Specifically, through elimination of invalid values of radiation data at night and correction of wind speed data based on surface roughness, deviation caused by factors such as terrain shielding, vegetation canopy reflectivity and urban building group wind resistance effect is effectively eliminated. The ERA5 data is trained and optimized by using a machine learning model such as a random forest, so that the wind speed and radiation data at different geographic positions, seasons and time periods can be more accurately corrected, and the corrected data is more in line with an actual observation result.

The invention provides a precise positioning device integrating dual-mode distance measurement and horizontal calibration, and relates to the technical field of precise measurement. The precise positioning device integrating dual-mode distance measurement and horizontal calibration comprises a power supply structure and a shell. According to the invention, integration of the ranging function and scene self-adaption are realized, and the success rate and reliability of measurement are effectively improved. Through a built-in horizontal calibration module and a core algorithm, the key problem that real space coordinates can be obtained only by depending on manual conversion when existing equipment is used for measuring on a non-horizontal reference plane is solved. The device can automatically sense the inclination attitude of the device, carry out real-time geometric correction on original distance measurement data, and directly output a positioning result based on a horizontal reference, so that systematic errors caused by improper operation attitude are eliminated, the measurement process is simpler and more convenient, and the precision and reliability of final data are substantially improved.

The invention provides an aspheric system error calibration method and device, and relates to the technical field of aspheric system error calibration, and the method comprises the steps: obtaining an alignment error; acquiring a rotational symmetry part of the measured aspheric surface at the first wavefront of the original measurement position and a rotational symmetry part of the measured aspheric surface at the second wavefront after the measured aspheric surface is translated by the preset distance along the optical axis; calculating an error surface according to the rotational symmetry part of the first wavefront, the rotational symmetry part of the second wavefront and the alignment error; fitting the error surface with a pre-constructed rotational symmetry error base, and solving a coefficient of each rotational symmetry error term; according to the coefficient and the rotational symmetry error substrate, reconstructing a rotational symmetry surface shape component of the measured aspheric surface; obtaining a rotational symmetry part of a system error according to the difference between the rotational symmetry part of the first wavefront and the reconstructed rotational symmetry surface shape component; according to the invention, the calibration process is obviously simplified, the measurement time is shortened, and the calibration efficiency is improved.

The present application relates to the technical field of radar remote sensing, and discloses a high-position loose body historical activity detection method based on multi-source DEM data, aiming to solve the problem that the prior art cannot accurately and quantitatively evaluate the historical activity of high-position loose bodies in a glacier-covered area, and the scheme mainly comprises the following steps: automatically dividing a watershed unit and screening a glacier-affected area based on DEM data; eliminating systematic errors by fusing multi-source DEM data, correcting geographical positioning deviation, correcting height distortion deviation, and correcting orbit mode deviation; establishing a penetration depth physical model, using C / X band height difference optimization parameters to correct the radar penetration depth in the glacier area; calculating the height change rate by using robust regression; calculating the activity comprehensive index by comprehensively considering multiple factors, and identifying hot regions and time periods by probability estimation and spatiotemporal clustering. The present application realizes automatic and high-precision quantitative evaluation of the historical activity of high-position loose bodies, and is particularly suitable for geological disaster warning and risk assessment in high mountain areas.

The invention relates to a radar system error detection method based on cooperative targets, and the method comprises the steps: carrying out the calculation in a detection period through employing the obtained position information of a plurality of cooperative targets under a north-east-sky coordinate system, and obtaining a measurement truth value set; acquiring a plurality of actual measurement values of the radar system on the plurality of cooperative targets; calculating difference values between the plurality of actual measurement values and the measurement truth value set to obtain a difference value sequence set; performing data dimension expansion on the difference value sequence set, and performing generalized likelihood ratio test on the difference value sequence after dimension expansion to obtain a first statistical magnitude under the condition that the system error is positive and a second statistical magnitude under the condition that the system error is negative; determining whether a system error exists or not according to a comparison result of the first statistic or the second statistic and a detection threshold; and under the condition that the existence of the system error is determined, the radar system is corrected based on the error estimation value, and the corrected radar system is obtained. The device can maintain the overall positioning precision of the radar system under various error levels.

This invention discloses a near-field RCS measurement calibration method based on scattering center topological mismatch compensation. Addressing the systematic error problem introduced by the mismatch between the distributed scattering characteristics of the complex target and the ideal point source calibration body when using traditional metal sphere calibration, a physical model of calibration error incorporating near-field spherical wave effects is established. The method preprocesses data by extracting scattering centers and removing outliers, generates a global initial search point set using feature analysis of the error function sensitivity tensor, and performs local precise optimization using an improved parallel LM algorithm. Finally, it obtains the optimal spatial position parameters of the target that minimize measurement error. This method effectively compensates for RCS amplitude oscillations and phase distortion caused by phase center mismatch, reducing the root mean square error (RMSE) of RCS measurements for complex targets such as ship hulls from approximately 15% to below 5% in the Ka-band, significantly improving the accuracy and reliability of electromagnetic scattering characteristic measurements in the field and anechoic chamber.