For high precision calibration of camera with large field-of-view,massive calibration points will be needed if traditional methods are selected,which makes the calibration complex and time-consuming.In order to solve ...For high precision calibration of camera with large field-of-view,massive calibration points will be needed if traditional methods are selected,which makes the calibration complex and time-consuming.In order to solve this problem,a calibration method based on flexible planar target is proposed.In this method,distortion factor is firstly acquired by the invariance of cross ratio,and existing feature points are adjusted with the distortion factor.Then,a large number of points that will be used for the calibration are constructed with the adjusted feature points.Simultaneously,Tsai method is modified so as to reduce the complexity of calibration,which makes the process linear.The simulation and real experiments show that the method proposed in this paper is simple,linear,accurate and robust,and the precision of this method is close to that of Tsai method using abundant points.The method can satisfy the requirement of high precision calibration for camera with large field-of-view.展开更多
基于BEV(bird’s eye view)多传感器融合的自动驾驶感知算法近年来取得重大进展,持续促进自动驾驶的发展。在多传感器融合感知算法研究中,多视角图像向BEV视角的转换和多模态特征融合一直是BEV感知算法的重点和难点。笔者提出MSEPE-CRN(...基于BEV(bird’s eye view)多传感器融合的自动驾驶感知算法近年来取得重大进展,持续促进自动驾驶的发展。在多传感器融合感知算法研究中,多视角图像向BEV视角的转换和多模态特征融合一直是BEV感知算法的重点和难点。笔者提出MSEPE-CRN(multi-scale feature fusion and edge and point enhancement-camera radar net),一种用于3D目标检测的相机与毫米波雷达融合感知算法,利用边缘特征和点云提高深度预测的精度,实现多视角图像向BEV特征的精确转换。同时,引入多尺度可变形大核注意力机制进行模态融合,解决因不同传感器特征差异过大导致的错位。在nuScenes开源数据集上的实验结果表明,与基准网络相比,mAP提升2.17%、NDS提升1.93%、mATE提升2.58%、mAOE提升8.08%、mAVE提升2.13%,该算法可有效提高车辆对路面上运动障碍物的感知能力,具有实用价值。展开更多
Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the see...Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the seekers the FOV is not fully exploited which means the target can be missed before becoming out of the FOV,this results of the nonlinearity of the reticle structure.In this paper,a novel method of the target position detection a crossed four slits or crossed array trackers(CAT) seeker will be designed,simulated and evaluated.The idea of this method depends on dividing the FOV into main regions up to a certain parameter,which is the pulses number;then,each main region will be divided into sub-regions up to a second parameter which will be the pulses distribution a spin period.The errors sources will be discussed and evaluated.Other new idea will be applied which is exploiting some area of the FOV where a part of the position data is missed in the information signal by pushing the target to the region where the information signal carries the total position data.展开更多
A gated viewing laser radar has an excellent performance in underwater low light level imaging, and it also provides a viable solution to inhibit backscattering. In this paper, a gated viewing imaging system according...A gated viewing laser radar has an excellent performance in underwater low light level imaging, and it also provides a viable solution to inhibit backscattering. In this paper, a gated viewing imaging system according to the demand for real-time imaging is presented, and then the simulation is used to analyze the performance of the real-time gated viewing system. The range accuracy performance is limited by the slice number, the width of gate, the delay time step, the initial delay time, as well as the system noise and atmospheric turbulence. The simulation results indicate that the highest range accuracy can be achieved when the system works with the optimal parameters. Finally, how to choose the optimal parameters has been researched.展开更多
Multi-view laser radar （ladar） data registration in obscure environments is an important research field of obscured target detection from air to ground. There are few overlap regions of the observational data in dif...Multi-view laser radar （ladar） data registration in obscure environments is an important research field of obscured target detection from air to ground. There are few overlap regions of the observational data in different views because of the occluder, so the multi-view data registration is rather difficult. Through indepth analyses of the typical methods and problems, it is obtained that the sequence registration is more appropriate, but needs to improve the registration accuracy. On this basis, a multi-view data registration algorithm based on aggregating the adjacent frames, which are already registered, is proposed. It increases the overlap region between the pending registration frames by aggregation and further improves the registration accuracy. The experiment results show that the proposed algorithm can effectively register the multi-view ladar data in the obscure environment, and it also has a greater robustness and a higher registration accuracy compared with the sequence registration under the condition of equivalent operating efficiency.展开更多
基金Sponsored by the Fundamental Research Funds for the Central Universities(Grant No.HIT.NSRIF.2014019)
文摘For high precision calibration of camera with large field-of-view,massive calibration points will be needed if traditional methods are selected,which makes the calibration complex and time-consuming.In order to solve this problem,a calibration method based on flexible planar target is proposed.In this method,distortion factor is firstly acquired by the invariance of cross ratio,and existing feature points are adjusted with the distortion factor.Then,a large number of points that will be used for the calibration are constructed with the adjusted feature points.Simultaneously,Tsai method is modified so as to reduce the complexity of calibration,which makes the process linear.The simulation and real experiments show that the method proposed in this paper is simple,linear,accurate and robust,and the precision of this method is close to that of Tsai method using abundant points.The method can satisfy the requirement of high precision calibration for camera with large field-of-view.
文摘基于BEV(bird’s eye view)多传感器融合的自动驾驶感知算法近年来取得重大进展,持续促进自动驾驶的发展。在多传感器融合感知算法研究中,多视角图像向BEV视角的转换和多模态特征融合一直是BEV感知算法的重点和难点。笔者提出MSEPE-CRN(multi-scale feature fusion and edge and point enhancement-camera radar net),一种用于3D目标检测的相机与毫米波雷达融合感知算法,利用边缘特征和点云提高深度预测的精度,实现多视角图像向BEV特征的精确转换。同时,引入多尺度可变形大核注意力机制进行模态融合,解决因不同传感器特征差异过大导致的错位。在nuScenes开源数据集上的实验结果表明,与基准网络相比,mAP提升2.17%、NDS提升1.93%、mATE提升2.58%、mAOE提升8.08%、mAVE提升2.13%,该算法可有效提高车辆对路面上运动障碍物的感知能力,具有实用价值。
文摘Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the seekers the FOV is not fully exploited which means the target can be missed before becoming out of the FOV,this results of the nonlinearity of the reticle structure.In this paper,a novel method of the target position detection a crossed four slits or crossed array trackers(CAT) seeker will be designed,simulated and evaluated.The idea of this method depends on dividing the FOV into main regions up to a certain parameter,which is the pulses number;then,each main region will be divided into sub-regions up to a second parameter which will be the pulses distribution a spin period.The errors sources will be discussed and evaluated.Other new idea will be applied which is exploiting some area of the FOV where a part of the position data is missed in the information signal by pushing the target to the region where the information signal carries the total position data.
基金supported by the Pre-research Foundation under Grant No. G020104PJ09DZ0246
文摘A gated viewing laser radar has an excellent performance in underwater low light level imaging, and it also provides a viable solution to inhibit backscattering. In this paper, a gated viewing imaging system according to the demand for real-time imaging is presented, and then the simulation is used to analyze the performance of the real-time gated viewing system. The range accuracy performance is limited by the slice number, the width of gate, the delay time step, the initial delay time, as well as the system noise and atmospheric turbulence. The simulation results indicate that the highest range accuracy can be achieved when the system works with the optimal parameters. Finally, how to choose the optimal parameters has been researched.
文摘Multi-view laser radar （ladar） data registration in obscure environments is an important research field of obscured target detection from air to ground. There are few overlap regions of the observational data in different views because of the occluder, so the multi-view data registration is rather difficult. Through indepth analyses of the typical methods and problems, it is obtained that the sequence registration is more appropriate, but needs to improve the registration accuracy. On this basis, a multi-view data registration algorithm based on aggregating the adjacent frames, which are already registered, is proposed. It increases the overlap region between the pending registration frames by aggregation and further improves the registration accuracy. The experiment results show that the proposed algorithm can effectively register the multi-view ladar data in the obscure environment, and it also has a greater robustness and a higher registration accuracy compared with the sequence registration under the condition of equivalent operating efficiency.
