The ground roll and body wave usually show significant differences in arrival time, frequency content, and polarization characteristics, and conventional polarization filters that operate in either the time or frequen...The ground roll and body wave usually show significant differences in arrival time, frequency content, and polarization characteristics, and conventional polarization filters that operate in either the time or frequency domain cannot consider all these elements. Therefore, we have developed a time-frequency dependent polarization filter based on the S transform to attenuate the ground roll in seismic records. Our approach adopts the complex coefficients of the S transform of the multi-component seismic data to estimate the local polarization attributes and utilizes the estimated attributes to construct the filter function. In this study, we select the S transform to design this polarization filter because its scalable window length can ensure the same number of cycles of a Fourier sinusoid, thereby rendering more precise estimation of local polarization attributes. The results of applying our approach in synthetic and real data examples demonstrate that the proposed polarization filter can effectively attenuate the ground roll and successfully preserve the body wave.展开更多
In this study, an unscented particle filtering method based on an interacting multiple model (IMM) frame for a Markovian switching system is presented. The method integrates the multiple model (MM) filter with an unsc...In this study, an unscented particle filtering method based on an interacting multiple model (IMM) frame for a Markovian switching system is presented. The method integrates the multiple model (MM) filter with an unscented particle filter (UPF) by an interaction step at the beginning. The framework (interaction/mixing, filtering, and combination) is similar to that in a standard IMM filter, but an UPF is adopted in each model. Therefore, the filtering performance and degeneracy phenomenon of particles are improved. The filtering method addresses nonlinear and/or non-Gaussian tracking problems. Simulation results show that the method has better tracking performance compared with the standard IMM-type filter and IMM particle filter.展开更多
Positioning and mapping technology is a difficult and hot topic in autonomous driving environment sensing systems.In a complex traffic environment,the signal of the Global Navigation Satellite System(GNSS)will be bloc...Positioning and mapping technology is a difficult and hot topic in autonomous driving environment sensing systems.In a complex traffic environment,the signal of the Global Navigation Satellite System(GNSS)will be blocked,leading to inaccurate vehicle positioning.To ensure the security of automatic electric campus vehicles,this study is based on the Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain(LEGO-LOAM)algorithm with a monocular vision system added.An algorithm framework based on Lidar-IMU-Camera(Lidar means light detection and ranging)fusion was proposed.A lightweight monocular vision odometer model was used,and the LEGO-LOAM system was employed to initialize monocular vision.The visual odometer information was taken as the initial value of the laser odometer.At the back-end opti9mization phase error state,the Kalman filtering fusion algorithm was employed to fuse the visual odometer and LEGO-LOAM system for positioning.The visual word bag model was applied to perform loopback detection.Taking the test results into account,the laser radar loopback detection was further optimized,reducing the accumulated positioning error.The real car experiment results showed that our algorithm could improve the mapping quality and positioning accuracy in the campus environment.The Lidar-IMU-Camera algorithm framework was verified on the Hong Kong city dataset UrbanNav.Compared with the LEGO-LOAM algorithm,the results show that the proposed algorithm can effectively reduce map drift,improve map resolution,and output more accurate driving trajectory information.展开更多
Ground magnetic, ground penetrating radar (GPR), and dipole-dipole resistivity were carried out to environmentally investigate a landfill. In this context, these geophysical techniques were conducted to identify the s...Ground magnetic, ground penetrating radar (GPR), and dipole-dipole resistivity were carried out to environmentally investigate a landfill. In this context, these geophysical techniques were conducted to identify the subsurface contents of the landfill, furthermore, specify any possible leakage and/or contamination in the study area. The ground-magnetic survey carried out in the study area comprised 31 profiles each 120 m in length. Different wavelength filters were applied to the measured data. Vertical derivative, downward continuation, apparent susceptibility, band-pass, and analytical signal filters separated successfully the shallow sources. Whereas, upward continuation and low-pass Gaussian filters isolated significantly the deep magnetic sources. 3D Euler deconvolution (SI = 3) remarkably estimated the depths of the shallow sources (0 - 10 m) of the landfill contents. The conducted GPR and dipole-dipole resistivity allocated tangibly the locations and depths of the near surface anomalies. Both techniques didn’t reveal any possible leakage and/or contamination. Noteworthy, integration among magnetic, GPR, and dipole-dipole resistivity confirmed positively the results of each method. Nevertheless, some anomalies were recognized successfully by one technique and not by the others.展开更多
Ground water is a major source of drinking water. In the Niger Delta, the ground water is unfit for human consumption due to high concentration of iron, coliforms and acidity. In an attempt to make the water potable, ...Ground water is a major source of drinking water. In the Niger Delta, the ground water is unfit for human consumption due to high concentration of iron, coliforms and acidity. In an attempt to make the water potable, groundwater samples were collected from domestic boreholes and analyzed for physicochemical and microbial parameters using standard analytical methods. The groundwater samples were collected after single and double trickling filter treatment. The treated water from the single and double trickling filter was similarly analyzed. Results show that after treatment, iron decreased from 5.23-9.96 mg/L in the raw water to 1.67-2.02 mg/L in the single treatment and 0.05-0.31 mg/L in the double treated water （P 〈 0.05）. Similarly, pH increased from 4.39-5.17 in the raw water to 5.31-5.87 in the single treatment and 6.09-6.90 in the double treatment （P 〈 0.05）. Coliforms decreased from 60-85 MPN/100 mL in the raw water to 3-10 MPN/100 mL in the single treatment and 0-2 MPN/100 mL in the double treatment （P 〈 0.05）. Based on the findings of this study, it is recommended that it is unsafe to drink untreated groundwater as currently practiced in the Niger Delta, but should be subjected to double trickling filter treatment and chlorination before consumption.展开更多
基金supported by the National Science and Technology Major Project of China(Grant No.2011ZX05014 and 2011ZX05008-005)
文摘The ground roll and body wave usually show significant differences in arrival time, frequency content, and polarization characteristics, and conventional polarization filters that operate in either the time or frequency domain cannot consider all these elements. Therefore, we have developed a time-frequency dependent polarization filter based on the S transform to attenuate the ground roll in seismic records. Our approach adopts the complex coefficients of the S transform of the multi-component seismic data to estimate the local polarization attributes and utilizes the estimated attributes to construct the filter function. In this study, we select the S transform to design this polarization filter because its scalable window length can ensure the same number of cycles of a Fourier sinusoid, thereby rendering more precise estimation of local polarization attributes. The results of applying our approach in synthetic and real data examples demonstrate that the proposed polarization filter can effectively attenuate the ground roll and successfully preserve the body wave.
基金Project supported by the National Natural Science Foundation ofChina (No. 60673024)the National Basic Research Program(973) of China (No. 2004CB719400)
文摘In this study, an unscented particle filtering method based on an interacting multiple model (IMM) frame for a Markovian switching system is presented. The method integrates the multiple model (MM) filter with an unscented particle filter (UPF) by an interaction step at the beginning. The framework (interaction/mixing, filtering, and combination) is similar to that in a standard IMM filter, but an UPF is adopted in each model. Therefore, the filtering performance and degeneracy phenomenon of particles are improved. The filtering method addresses nonlinear and/or non-Gaussian tracking problems. Simulation results show that the method has better tracking performance compared with the standard IMM-type filter and IMM particle filter.
基金supported by the National Natural Science Foundation of China(Grant Nos.51975088 and 51975089).
文摘Positioning and mapping technology is a difficult and hot topic in autonomous driving environment sensing systems.In a complex traffic environment,the signal of the Global Navigation Satellite System(GNSS)will be blocked,leading to inaccurate vehicle positioning.To ensure the security of automatic electric campus vehicles,this study is based on the Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain(LEGO-LOAM)algorithm with a monocular vision system added.An algorithm framework based on Lidar-IMU-Camera(Lidar means light detection and ranging)fusion was proposed.A lightweight monocular vision odometer model was used,and the LEGO-LOAM system was employed to initialize monocular vision.The visual odometer information was taken as the initial value of the laser odometer.At the back-end opti9mization phase error state,the Kalman filtering fusion algorithm was employed to fuse the visual odometer and LEGO-LOAM system for positioning.The visual word bag model was applied to perform loopback detection.Taking the test results into account,the laser radar loopback detection was further optimized,reducing the accumulated positioning error.The real car experiment results showed that our algorithm could improve the mapping quality and positioning accuracy in the campus environment.The Lidar-IMU-Camera algorithm framework was verified on the Hong Kong city dataset UrbanNav.Compared with the LEGO-LOAM algorithm,the results show that the proposed algorithm can effectively reduce map drift,improve map resolution,and output more accurate driving trajectory information.
文摘Ground magnetic, ground penetrating radar (GPR), and dipole-dipole resistivity were carried out to environmentally investigate a landfill. In this context, these geophysical techniques were conducted to identify the subsurface contents of the landfill, furthermore, specify any possible leakage and/or contamination in the study area. The ground-magnetic survey carried out in the study area comprised 31 profiles each 120 m in length. Different wavelength filters were applied to the measured data. Vertical derivative, downward continuation, apparent susceptibility, band-pass, and analytical signal filters separated successfully the shallow sources. Whereas, upward continuation and low-pass Gaussian filters isolated significantly the deep magnetic sources. 3D Euler deconvolution (SI = 3) remarkably estimated the depths of the shallow sources (0 - 10 m) of the landfill contents. The conducted GPR and dipole-dipole resistivity allocated tangibly the locations and depths of the near surface anomalies. Both techniques didn’t reveal any possible leakage and/or contamination. Noteworthy, integration among magnetic, GPR, and dipole-dipole resistivity confirmed positively the results of each method. Nevertheless, some anomalies were recognized successfully by one technique and not by the others.
文摘Ground water is a major source of drinking water. In the Niger Delta, the ground water is unfit for human consumption due to high concentration of iron, coliforms and acidity. In an attempt to make the water potable, groundwater samples were collected from domestic boreholes and analyzed for physicochemical and microbial parameters using standard analytical methods. The groundwater samples were collected after single and double trickling filter treatment. The treated water from the single and double trickling filter was similarly analyzed. Results show that after treatment, iron decreased from 5.23-9.96 mg/L in the raw water to 1.67-2.02 mg/L in the single treatment and 0.05-0.31 mg/L in the double treated water （P 〈 0.05）. Similarly, pH increased from 4.39-5.17 in the raw water to 5.31-5.87 in the single treatment and 6.09-6.90 in the double treatment （P 〈 0.05）. Coliforms decreased from 60-85 MPN/100 mL in the raw water to 3-10 MPN/100 mL in the single treatment and 0-2 MPN/100 mL in the double treatment （P 〈 0.05）. Based on the findings of this study, it is recommended that it is unsafe to drink untreated groundwater as currently practiced in the Niger Delta, but should be subjected to double trickling filter treatment and chlorination before consumption.
