Aeromagnetic interference could not be compensated effectively if the precision of parameters which are solved by the aircraft magnetic field model is low. In order to improve the compensation effect under this condit...Aeromagnetic interference could not be compensated effectively if the precision of parameters which are solved by the aircraft magnetic field model is low. In order to improve the compensation effect under this condition, a method based on small signal model and least mean square（LMS） algorithm is proposed. According to the method, the initial values of adaptive filter＇s weight vector are calculated with the solved model parameters through small signal model at first,then the small amount of direction cosine and its derivative are set as the input of the filter, and the small amount of the interference is set as the filter＇s expected vector. After that, the aircraft magnetic interference is compensated by LMS algorithm. Finally, the method is verified by simulation and experiment. The result shows that the compensation effect can be improved obviously by the LMS algorithm when original solved parameters have low precision. The method can further improve the compensation effect even if the solved parameters have high precision.展开更多
Aeromagnetic compensation is one of the key issues in high-precision geomagnetic fl ight carrier navigation, directly determining the accuracy and reliability of real-time magnetic measurement data. The accurate model...Aeromagnetic compensation is one of the key issues in high-precision geomagnetic fl ight carrier navigation, directly determining the accuracy and reliability of real-time magnetic measurement data. The accurate modeling and compensation of interference magnetic measurements on carriers are of great signifi cance for the construction of reference and real-time maps for geomagnetic navigation. Current research on aeromagnetic compensation algorithms mainly focuses on accurately modeling interference magnetic fields from model- and data-driven perspectives based on measured aeromagnetic data. Challenges in obtaining aeromagnetic data and low information complexity adversely aff ect the generalization performance of a constructed model. To address these issues, a recursive least square algorithm based on elastic weight consolidation is proposed, which eff ectively suppresses the occurrence of catastrophic forgetting by controlling the direction of parameter updates. Experimental verifi cation with publicly available aeromagnetic datasets shows that the proposed algorithm can eff ectively circumvent historical information loss caused by interference magnetic field models during parameter updates and improve the stability, robustness, and accuracy of interference magnetic fi eld models.展开更多
Unmanned Aerial Vehicle(UAV)aeromagnetic survey technology has been increasingly applied in geophysical exploration within complex terrains owing to its flexibility and cost-eectiveness.However,the inherent magnetic i...Unmanned Aerial Vehicle(UAV)aeromagnetic survey technology has been increasingly applied in geophysical exploration within complex terrains owing to its flexibility and cost-eectiveness.However,the inherent magnetic interference of UAV platforms and disturbances caused by dynamic flight attitudes signicantly constrain data accuracy.This study focuses on the CH-4 UAV aeromagnetic gradient measurement system,conducting an in-depth analysis of its error sources.Common interference factors are identified,including static ferromagnetic material interference,dynamic servo noise,and attitude coupling effects.Building on this analysis,an innovative full-axis gradient dynamic compensation technology is proposed.Utilizing a compensation algorithm independently developed by the China Aero Geophysical Survey and Remote Sensing Center for Natural Resources,this technique effectively mitigates the impact of magnetic interference on measurement accuracy through real-time monitoring and adjustment.Experimental results demonstrate a breakthrough reduction in the standard deviation of the total magnetic eld intensity from 0.126 nT to 0.022 nT,indicating a substantial improvement in measurement accuracy.Concurrently,the transverse gradient error was optimized from a range of 2.398 nT/m–0.132 nT/m to 0.103 nT/m–0.005 nT/m.Through the synergistic integration of sensor extension,non-magnetic material replacement,and algorithmic dynamic compensation,the measurement system is further optimized.Experiments conrm that extending the sensor by 4.6 meters beyond the wingtip eectively suppresses servo-induced interference to below 0.1 nT.Nevertheless,high-frequency disturbances necessitate further optimization via active shielding technology.At present,the application of active shielding in UAV aeromagnetic surveys faces limitations such as unstable shielding performance and adverse eects on UAV flight characteristics.Future research will prioritize the refinement of active shielding technology to improve its adaptability and stability in complex operational environments,thereby establishing a robust theoretical foundation and oering valuable practical insights for high-precision UAV aeromagnetic gradient surveys.展开更多
Different from the traditional contact surface topography measurement,reflective intensity-modulated fiber optic sensor(RIM-FOS)has the unique advantages of non-contact nondestructive detection.This paper briefly intr...Different from the traditional contact surface topography measurement,reflective intensity-modulated fiber optic sensor(RIM-FOS)has the unique advantages of non-contact nondestructive detection.This paper briefly introduces the principle and performance of RIM-FOS for surface topography measurement and compares with several other methods of topography measurement.Based on the review of its development process,this paper summarizes and analyses the hot issues of RIM-FOS in the surface topography measurement,then predicts the future trend for a guidance of the further study.展开更多
基金co-supported by the National Basic Research Program of China (No. 623125020103)
文摘Aeromagnetic interference could not be compensated effectively if the precision of parameters which are solved by the aircraft magnetic field model is low. In order to improve the compensation effect under this condition, a method based on small signal model and least mean square（LMS） algorithm is proposed. According to the method, the initial values of adaptive filter＇s weight vector are calculated with the solved model parameters through small signal model at first,then the small amount of direction cosine and its derivative are set as the input of the filter, and the small amount of the interference is set as the filter＇s expected vector. After that, the aircraft magnetic interference is compensated by LMS algorithm. Finally, the method is verified by simulation and experiment. The result shows that the compensation effect can be improved obviously by the LMS algorithm when original solved parameters have low precision. The method can further improve the compensation effect even if the solved parameters have high precision.
基金supported by the National Natural Science Foundation of China under Grant 61673017in part by the Science and Technology Department of Shaanxi Province under Grant 2024JC-YBQN-0657。
文摘Aeromagnetic compensation is one of the key issues in high-precision geomagnetic fl ight carrier navigation, directly determining the accuracy and reliability of real-time magnetic measurement data. The accurate modeling and compensation of interference magnetic measurements on carriers are of great signifi cance for the construction of reference and real-time maps for geomagnetic navigation. Current research on aeromagnetic compensation algorithms mainly focuses on accurately modeling interference magnetic fields from model- and data-driven perspectives based on measured aeromagnetic data. Challenges in obtaining aeromagnetic data and low information complexity adversely aff ect the generalization performance of a constructed model. To address these issues, a recursive least square algorithm based on elastic weight consolidation is proposed, which eff ectively suppresses the occurrence of catastrophic forgetting by controlling the direction of parameter updates. Experimental verifi cation with publicly available aeromagnetic datasets shows that the proposed algorithm can eff ectively circumvent historical information loss caused by interference magnetic field models during parameter updates and improve the stability, robustness, and accuracy of interference magnetic fi eld models.
基金supported by Xizang Autonomous Region Science and Technology Program Project:Development of a HighTemperature Superconducting Airborne Full Tensor Magnetic Gradient Measurement System and Research on Error Compensation Methods(Project No.:XZ2025ZY0136)。
文摘Unmanned Aerial Vehicle(UAV)aeromagnetic survey technology has been increasingly applied in geophysical exploration within complex terrains owing to its flexibility and cost-eectiveness.However,the inherent magnetic interference of UAV platforms and disturbances caused by dynamic flight attitudes signicantly constrain data accuracy.This study focuses on the CH-4 UAV aeromagnetic gradient measurement system,conducting an in-depth analysis of its error sources.Common interference factors are identified,including static ferromagnetic material interference,dynamic servo noise,and attitude coupling effects.Building on this analysis,an innovative full-axis gradient dynamic compensation technology is proposed.Utilizing a compensation algorithm independently developed by the China Aero Geophysical Survey and Remote Sensing Center for Natural Resources,this technique effectively mitigates the impact of magnetic interference on measurement accuracy through real-time monitoring and adjustment.Experimental results demonstrate a breakthrough reduction in the standard deviation of the total magnetic eld intensity from 0.126 nT to 0.022 nT,indicating a substantial improvement in measurement accuracy.Concurrently,the transverse gradient error was optimized from a range of 2.398 nT/m–0.132 nT/m to 0.103 nT/m–0.005 nT/m.Through the synergistic integration of sensor extension,non-magnetic material replacement,and algorithmic dynamic compensation,the measurement system is further optimized.Experiments conrm that extending the sensor by 4.6 meters beyond the wingtip eectively suppresses servo-induced interference to below 0.1 nT.Nevertheless,high-frequency disturbances necessitate further optimization via active shielding technology.At present,the application of active shielding in UAV aeromagnetic surveys faces limitations such as unstable shielding performance and adverse eects on UAV flight characteristics.Future research will prioritize the refinement of active shielding technology to improve its adaptability and stability in complex operational environments,thereby establishing a robust theoretical foundation and oering valuable practical insights for high-precision UAV aeromagnetic gradient surveys.
基金Youth Science and Technology Research Foundation of Shanxi Province(No.2015021104)Programs for Science and Technology Development of Shanxi Province(No.201703D121028-2)
文摘Different from the traditional contact surface topography measurement,reflective intensity-modulated fiber optic sensor(RIM-FOS)has the unique advantages of non-contact nondestructive detection.This paper briefly introduces the principle and performance of RIM-FOS for surface topography measurement and compares with several other methods of topography measurement.Based on the review of its development process,this paper summarizes and analyses the hot issues of RIM-FOS in the surface topography measurement,then predicts the future trend for a guidance of the further study.
