scholarly journals Algorithm for constructing a route to pass a narrow fairway

2021 ◽  
Vol 2061 (1) ◽  
pp. 012116
Author(s):  
A A Antonov ◽  
D E Studenikin ◽  
S O Malakhov ◽  
R G Filatova ◽  
S I Kondratyev ◽  
...  

Abstract Modern navigation systems often employ the algorithms for plotting lines for the preliminary route construction. The current conditions of technological development imply the simplicity of constructing routes. However, the most important part was and remains the speed of the system that generates the route. The authors of the paper proposed a universal algorithm for constructing a navigation route in narrow channels of the sea. The presented algorithm identifies the middle of the fairway as the safest point at each narrow segment and connects them with track lines. The problem that can arise is smoothing, as the middle of the fairway can shift significantly. To solve this problem, new relative and absolute parameters that characterize plotting of turning points were introduced. In addition, a unified universal formula was proposed for finding the coordinates of these points on a line perpendicular to the current route of the vessel. It was experimentally proved that correctly selected empirical parameters enable the algorithm to quickly construct a route in any navigation area with a relatively low computational complexity. This approach is appropriate for clearly delineated zones of the fairway, and it is compatible with zone methods.

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Ran Li ◽  
Hongbing Liu ◽  
Yu Zeng ◽  
Yanling Li

In the framework of block Compressed Sensing (CS), the reconstruction algorithm based on the Smoothed Projected Landweber (SPL) iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA) to perform the adaptive hard-thresholding shrinkage. However, during learning the PCA matrix, it affects the reconstruction performance of Landweber iteration to neglect the stationary local structural characteristic of image. To solve the above problem, this paper firstly uses the Granular Computing (GrC) to decompose an image into several granules depending on the structural features of patches. Then, we perform the PCA to learn the sparse representation basis corresponding to each granule. Finally, the hard-thresholding shrinkage is employed to remove the noises in patches. The patches in granule have the stationary local structural characteristic, so that our method can effectively improve the performance of hard-thresholding shrinkage. Experimental results indicate that the reconstructed image by the proposed algorithm has better objective quality when compared with several traditional ones. The edge and texture details in the reconstructed image are better preserved, which guarantees the better visual quality. Besides, our method has still a low computational complexity of reconstruction.


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