Polarized protons have never been accelerated to more than about 25 GeV. To achieve polarized proton beams in the Relativistic Heavy Ion Collider (RHIC, 250 GeV), the Hadron Electron Ring Accelerator (HERA, 820 GeV), ...
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A novel orientation tracking algorithm is introduced. The algorithm can provide 3DOF orientation information of an object in a hemisphere space. It is based on two-dimensional information about the gravity field and t...
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ISBN:
(纸本)0780386299
A novel orientation tracking algorithm is introduced. The algorithm can provide 3DOF orientation information of an object in a hemisphere space. It is based on two-dimensional information about the gravity field and the earth magnetic field. Comparing with the traditional algorithm, it reduced the needed information from three dimensions to two dimensions in operation. It is faster and simpler. The algorithm is validated with a system. The results indicate the algorithm can track the orientation of the object well.
Mobile satellite terminals especially with high-gain antenna require fast and accurate beam tracking algorithms for communication. The main topic of this paper is the extension of a tracking algorithm to mobile satell...
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ISBN:
(纸本)1424403081
Mobile satellite terminals especially with high-gain antenna require fast and accurate beam tracking algorithms for communication. The main topic of this paper is the extension of a tracking algorithm to mobile satellite communications, its implementation and performance. The presented considerations and simulation results concern low SNR condition and narrow antenna beam configuration as existing in satellite communications. The assumed satellite is geostationary. The work is presented in context of SANTANA-2 project, (Smart Antenna Terminal), founded and supported by the German DLR on behalf of BMBF. The realized terminal uses an antenna array in Ka-band and fully implements Digital BeamForming (DBF) to control the beam pointing direction and the antenna beam shape.
The paper presents a new efficient method for performance evaluation of imaging seeker tracking algorithm. The method utilizes multi features which associate with tracking point of each video frame, gets local score(L...
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ISBN:
(纸本)9780819488343
The paper presents a new efficient method for performance evaluation of imaging seeker tracking algorithm. The method utilizes multi features which associate with tracking point of each video frame, gets local score(LS) for every feature, and achieves global score(GS) for given tracking algorithm according to the combined strategy. The method can be divided into three steps. In a first step, it extracts evaluation feature from neighbor zone of each tracking point. The feature may include tracking error, shape of target, area of target, tracking path, and so on. Then, as to each feature, a local score can be got rely on the number of target which tracked successfully. It uses similarity measurement and experiential threshold between neighbor zone of tracking point and target template to define tracking successful or not. Of course, the number should be 0 or 1 for single target tracking. Finally, it assigns weight for each feature according to the validity grade for the performance. The weights multiply by local scores and normalized between 0 and 1, this gets global score of certain tracking algorithm. By compare the global score of each tracking algorithm as to certain type of scene, it can evaluate the performance of tracking algorithm quantificational. The proposed method nearly covers all tracking error factors which can be introduced into the process of target tracking, so the evaluation result has a higher reliability. Experimental results, obtained with flying video of infrared imaging seeker, and also included several target tracking algorithms, illustrate the performance of target tracking, demonstrate the effectiveness and robustness of the proposed method.
For several applications involving Unmanned Aerial Vehicles (UAVs), a moving target must the tracked and followed autonomously. Several algorithms have been already proposed, mainly based on three different strategies...
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For several applications involving Unmanned Aerial Vehicles (UAVs), a moving target must the tracked and followed autonomously. Several algorithms have been already proposed, mainly based on three different strategies, assuming in most of the cases the target trajectory known in advanced. We here propose a new algorithm and compared it with a well known and widely used control tracking algorithm in a ship-tracking scenario. Our proposal is derived from the qualitative analysis of the system response when a UAV low level controller is implemented. Besides, these algorithms depend on various parameters, which normally are tuned based on the experience. We also present a methodological way of tuning the parameters of these types of control algorithms based on the kinematic analysis of the movement, the control effort and the error while tracking the target. This method has been proved efficient and general, and it may be used for similar problems and control algorithms. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Because of the unique flight trajectory and high penetration effectiveness, near-space hypersonic vehicles (NSHV) become a great challenge for active air defense systems. This paper study the tracking algorithm for NS...
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ISBN:
(纸本)9781509044238
Because of the unique flight trajectory and high penetration effectiveness, near-space hypersonic vehicles (NSHV) become a great challenge for active air defense systems. This paper study the tracking algorithm for NSHV based on Aerodynamic Model. Firstly, the paper simulated flight trajectory of NSHV based on the equation of motion. Secondly, the paper designed a tracking method for NSHV by using aerodynamic acceleration model. the effectiveness and limitation of the model are both verified by simulation. Finally, this paper provided some suggestions for improvement of the tracking algorithm based on Aerodynamic Acceleration Model.
In this paper, the robot vision systems are studied. Through the analysis of the visual tracking process, this paper classifies and introduces several commonly track. The features affecting the quality of target track...
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ISBN:
(纸本)9783037853542
In this paper, the robot vision systems are studied. Through the analysis of the visual tracking process, this paper classifies and introduces several commonly track. The features affecting the quality of target tracking, such as block, rotation, translation deformation and others, are analyzed and discussed. At last, some further directions of target tracking algorithm are also shortly addressed.
We develop a fully Bayesian tracking algorithm with the purpose of providing classification prediction results that are unbiased when applied uniformly to individuals with differing sensitive variable values, e.g., of...
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We develop a fully Bayesian tracking algorithm with the purpose of providing classification prediction results that are unbiased when applied uniformly to individuals with differing sensitive variable values, e.g., of different races, sexes, etc. Here, we consider bias in the form of group-level differences in false prediction rates between the different sensitive variable groups. Given that the method is fully Bayesian, it is well suited for situations where group parameters or regression coefficients are dynamic quantities. We illustrate our method, in comparison to others, on simulated datasets and two real-world datasets.& COPY;2022 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Aiming at the problem that the particle filter target tracking based on single feature is vulnerable to environmental impacts and is difficult to deal with the size scaling and rotation changes, this paper proposes a ...
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ISBN:
(纸本)9781509060887
Aiming at the problem that the particle filter target tracking based on single feature is vulnerable to environmental impacts and is difficult to deal with the size scaling and rotation changes, this paper proposes a particle filter tracking algorithm based on covariance matrix. The algorithm uses the covariance matrix to fuse multiple features of the target in the framework of particle filter, which improves the adaptability of the algorithm. By introducing the covariance integral graph, the dimension of particle computation is effectively reduced, which reduces the computational cost of the algorithm and improves the real-time performance. The processing efficiency of the algorithm is effectively improved through the mean value calculation in covariance to remove the noise. Simulation experiment results show that the proposed algorithm is robust to the target tracking under the condition of illumination change, environmental disturbance and scale change.
The kernel bandwidth of the traditional Mean Shift tracking algorithm cannot be changed in real time. It can't achieve accurate tracking when the target size is changing. This paper proposes an algorithm to automa...
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ISBN:
(纸本)9781467376822
The kernel bandwidth of the traditional Mean Shift tracking algorithm cannot be changed in real time. It can't achieve accurate tracking when the target size is changing. This paper proposes an algorithm to automatically select the bandwidth of the kernel function, which can achieve accurate tracking when the size of the rigid target is changing. Firstly, it matches the target center of two consecutive frames by using the backward tracking. Then in order to effectively eliminate the false matching and ensure the accuracy of the regression, it extracts and disposes the feature points with regressive calculation on the base of matching. The results of tracking experiment show that the proposed algorithm can achieve accurate tracking in real time when the target size is changing.
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