In optical fiber communication, due to the random variation of the environment, the state of polarization (SOP) fluctuates randomly with time leading to distortion and performance degradation. The memory-less SOP fluc...
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In optical fiber communication, due to the random variation of the environment, the state of polarization (SOP) fluctuates randomly with time leading to distortion and performance degradation. The memory-less SOP fluctuations can be regarded as a two-by-two random unitary matrix. In this paper, for what we believe to be the first time, the capacity of the polarization drift channel under an average power constraint with imperfect channel knowledge is characterized. An achievable information rate (AIR) is derived when imperfect channel knowledge is available and is shown to be highly dependent on the channel estimation technique. It is also shown that a tighter lower bound can be achieved when a unitary estimation of the channel is available. However, the conventional estimation algorithms do not guarantee a unitary channel estimation. Therefore, by considering the unitary constraint of the channel, a data-aided channel estimator based on the kabsch algorithm is proposed, and its performance is numerically evaluated in terms of AIR. Monte Carlo simulations show that kabsch outperforms the least-square error algorithm. In particular, with complex, Gaussian inputs and eight pilot symbols per block, kabsch improves the AIR by 0.20 to 0.30 bits/symbol throughout the range of studied signal-to-noise ratios.
We introduce an integrated method for processing depth maps measured by a laser profile sensor. It serves for the recognition and alignment of an object given by a single example. Firstly, we look for potential object...
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We introduce an integrated method for processing depth maps measured by a laser profile sensor. It serves for the recognition and alignment of an object given by a single example. Firstly, we look for potential object contours, mainly using the Retinex filter. Then, we select the actual object boundary via shape comparison based on Triangle Area Representation (TAR). We overcome the limitations of the TAR method by extension of its shape descriptor. That is helpful mainly for objects with symmetric shapes but other asymmetric aspects like squares with asymmetric holes. Finally, we use point-to-point pairing, provided by the extended TAR method, to calculate the 3D rigid affine transform that aligns the scanned object to the given example position. For the transform calculation, we design an algorithm that overcomes the kabsch point-to-point algorithm's accuracy and accommodates it for a precise contour-to-contour alignment. In this way, we have implemented a pipeline with features convenient for industrial use, namely production inspection.
Radars are part of the sensor suite installed on modern vehicles for environmental perception. The position and orientation of the radar must be known in order to transform the detections from the radar coordinate sys...
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Radars are part of the sensor suite installed on modern vehicles for environmental perception. The position and orientation of the radar must be known in order to transform the detections from the radar coordinate system to a vehicle coordinate system (VCS), which is a common requirement for multisensor fusion. In this work, 77-GHz automotive radar sensors are extrinsically calibrated by registering the radar detections of corner reflector targets with known locations of the targets in the VCS;the procedure estimates the position and orientation parameters needed to transform radar detections onto the VCS. Radar detections are noisy and very sparse;hence, an effort is put into achieving good calibration accuracy by taking advantage of multiple target configurations. Two multitarget methods are discussed;one models estimation error as white noise and averages multiple estimates, and another combines all observations to make the data points denser for a one-time global estimation. The methods are tested with both synthetic and experimental data. The synthetic data result shows that, with sparse data points per target configuration, the estimation errors obtained due to the global method tend to decay faster than those obtained due to the averaging method as the number of configurations increases. The experimental data obtained from just ten target configurations result in estimation errors of about 0.35 degrees and 1 cm for the orientation and position parameters, respectively.
This paper applies a method to obtain the extrinsic calibration parameters between a Camera and a 3D-LiDAR using 3D point-to- point correspondences. We use a calibration board with ArUco marker as a reference to obtai...
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ISBN:
(纸本)9781728194097
This paper applies a method to obtain the extrinsic calibration parameters between a Camera and a 3D-LiDAR using 3D point-to- point correspondences. We use a calibration board with ArUco marker as a reference to obtain features of interest in both sensor frames. Through a manual method which is easy to operate, the calibration board planar and edge will be extracted from the LiDAR point cloud by exploiting the geometry of the board. And then the vertices will be calculated by using nonlinear optimization. The corresponding vertices in the Camera image are detected by ArUco Marker API. Once we get the point-to-point correspondences, we use kabsch algorithm to get the final rotation and transition. The calibration accuracy is demonstrated by evaluating it in real application scenarios.
In truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various si...
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In truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various situations, each truck must maintain dynamic stability, and furthermore, the whole system must maintain string stability. Due to the short front-view range, however, the following vehicles' path planning capabilities become significantly impaired. In addition, in platooning with articulated cargo trucks, the off-tracking phenomenon occurring on a curved road makes it hard for the following vehicle to track the trajectory of the preceding truck. In addition, without knowledge of the global coordinate system, it is difficult to correlate the local coordinate systems that each truck relies on for sensing environment and dynamic signals. In this paper, in order to solve these problems, a path planning algorithm for platooning of articulated cargo trucks has been developed. Using the Kalman filter, V2V (Vehicle-to-Vehicle) communication, and a novel update-and-conversion method, each following vehicle can accurately compute the trajectory of the leading vehicle's front part for using it as a target path. The path planning algorithm of this paper was validated by simulations on severe driving scenarios and by tests on an actual road. The results demonstrated that the algorithm could provide lateral string stability and robustness for truck platooning.
Post-translational modifications (PTMs) provide a wide range of options to expand a proteins biological capabilities. Modifications such as addition of covalent functional groups influence proteins activity state, loc...
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ISBN:
(纸本)9781538654576
Post-translational modifications (PTMs) provide a wide range of options to expand a proteins biological capabilities. Modifications such as addition of covalent functional groups influence proteins activity state, localization, turnover, and interactions with the other proteins. PTMs potentially have an influence on therapeutic proteins and play critical element on biopharmaceutical drug development. Despite the importance of PTMs in cellular functions, most peptides with PTMs have no known three-dimensional structures. These protein structural prediction pose new set of challenges for peptides with existing PTMs. Protein-peptide docking simulations play an important role in drug discovery. Providing a peptide docking prediction is not feasible for peptides with only known secondary structure. In this paper, we extend the capabilities of a known peptide-protein docking algorithm to be able to handle peptides with existing PTMs. The proposed solution involves truncation of the PTMs in a peptide. We analyze the proposed algorithm by observing the effect of the length of truncation on the peptide sequence to the predicted structure of an existing docking tool CABSdock. The proposed framework introduces an alignment technique by kabsch and further refinement by molecular dynamics to the simulation.
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