Micro Air Vehicle(MAV)swarms are often constrained by limited onboard processing capabilities and payload capacity,restricting the use of sophisticated localization systems.Lightweight ultra-wideband(UWB)ranging techn...Micro Air Vehicle(MAV)swarms are often constrained by limited onboard processing capabilities and payload capacity,restricting the use of sophisticated localization systems.Lightweight ultra-wideband(UWB)ranging techniques are commonly used to estimate inter-vehicle distances,but they do not provide local bearing information—essential for precise relative positioning.Inspired by bat echolocation in low-visibility environments,we propose an acoustic-enhanced method for local bearing estimation designed for low-cost MAVs.Our approach leverages ambient acoustic signals naturally emitted by a target MAV in flight,combined with UWB distance measurements.The acoustic data is processed using the Frequency-Sliding Generalized Cross-Correlation(FS-GCC)method,enhanced with our analytical formulation that compensates for inter-channel switching delays in asynchronous,high-frequency sampling.This enables accurate Time Difference of Arrival(TDOA)estimation,even with compact microphone arrays.These TDOA values,along with known microphone geometry and UWB data,are integrated into our geometric model to estimate the bearing of the target MAV.We validate our approach in a controlled indoor hall across two experimental scenarios:static-bearing estimation,where the target MAV hovers at predefined angular positions(0°,±30°,±45°,±60°),and dynamic-bearing estimation,where it flies across angles at varying velocities.The results show that our method yields reliable TDOA measurements compared to classical and machine learning baselines,and produces accurate bearing estimates in both static and dynamic settings.This demonstrates the feasibility of our low-cost acoustic-enhanced solution for local bearing estimation in MAV swarms,supporting improved relative navigation and decentralized perception in GPS-denied or visually degraded environments.展开更多
The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization...The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization weighted ESPRIT method using a single vector device is proposed. The frequency domain polari- zation parameters extracted from the signals are used to design the weighted function which is applied to the received signals. The bearing angle and the target frequency are estimated through ESPRIT using the weighted signals. The simulation and experiment results show that the presented method can obtain accurate estimation values under the low SNR with little prior information.展开更多
Three kinds of polymeric materials are taken as example for the verification of linear ex-trapolation method from unified master lines with reduced universal equations on creep and stress relaxation tests. The theoret...Three kinds of polymeric materials are taken as example for the verification of linear ex-trapolation method from unified master lines with reduced universal equations on creep and stress relaxation tests. The theoretical values of long-term mechanical behavior and lifetime for a cured epoxide, polypropylene, poly（methyl-methacrylate）, and SBR rubber are directly evaluated with the universal equations on reduced creep compliance and reduced stress relax-ation modulus and are compared with their predicted values by the linear extrapolation from the unified master lines of creep and stress relaxation. The results show that the theoretical values of dimensional stability, bearing ability and lifetime are in an excellent agreement with the predicted values, it shows that the linear extrapolation method is more simple and reliable. The dependences of long-term mechanical behaviors and lifetime on the different aging times are discussed.展开更多
基金Malaysian Ministry of Higher Education(MOHE)for providing the Fundamental Research Grant Scheme(FRGS)(FRGS/1/2024/TK04/USM/02/3)for conducting this research.
文摘Micro Air Vehicle(MAV)swarms are often constrained by limited onboard processing capabilities and payload capacity,restricting the use of sophisticated localization systems.Lightweight ultra-wideband(UWB)ranging techniques are commonly used to estimate inter-vehicle distances,but they do not provide local bearing information—essential for precise relative positioning.Inspired by bat echolocation in low-visibility environments,we propose an acoustic-enhanced method for local bearing estimation designed for low-cost MAVs.Our approach leverages ambient acoustic signals naturally emitted by a target MAV in flight,combined with UWB distance measurements.The acoustic data is processed using the Frequency-Sliding Generalized Cross-Correlation(FS-GCC)method,enhanced with our analytical formulation that compensates for inter-channel switching delays in asynchronous,high-frequency sampling.This enables accurate Time Difference of Arrival(TDOA)estimation,even with compact microphone arrays.These TDOA values,along with known microphone geometry and UWB data,are integrated into our geometric model to estimate the bearing of the target MAV.We validate our approach in a controlled indoor hall across two experimental scenarios:static-bearing estimation,where the target MAV hovers at predefined angular positions(0°,±30°,±45°,±60°),and dynamic-bearing estimation,where it flies across angles at varying velocities.The results show that our method yields reliable TDOA measurements compared to classical and machine learning baselines,and produces accurate bearing estimates in both static and dynamic settings.This demonstrates the feasibility of our low-cost acoustic-enhanced solution for local bearing estimation in MAV swarms,supporting improved relative navigation and decentralized perception in GPS-denied or visually degraded environments.
基金supported by the National Natural Science Foundation of China(11234002)
文摘The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization weighted ESPRIT method using a single vector device is proposed. The frequency domain polari- zation parameters extracted from the signals are used to design the weighted function which is applied to the received signals. The bearing angle and the target frequency are estimated through ESPRIT using the weighted signals. The simulation and experiment results show that the presented method can obtain accurate estimation values under the low SNR with little prior information.
基金This work was supported by the National Natural Science Foundation of China （No.50973007）.
文摘Three kinds of polymeric materials are taken as example for the verification of linear ex-trapolation method from unified master lines with reduced universal equations on creep and stress relaxation tests. The theoretical values of long-term mechanical behavior and lifetime for a cured epoxide, polypropylene, poly（methyl-methacrylate）, and SBR rubber are directly evaluated with the universal equations on reduced creep compliance and reduced stress relax-ation modulus and are compared with their predicted values by the linear extrapolation from the unified master lines of creep and stress relaxation. The results show that the theoretical values of dimensional stability, bearing ability and lifetime are in an excellent agreement with the predicted values, it shows that the linear extrapolation method is more simple and reliable. The dependences of long-term mechanical behaviors and lifetime on the different aging times are discussed.
