article · 2010
Improved dynamic programming algorithm for tracking small target of low-manoeuvring
Cited by 0Abstract and details only
Abstract
An update dynamic programming algorithm is presented in allusion to the features of the moving infrared small dim target. The main idea of this algorithm is that the predicting states between frames and a low threshold are applied to reduce the computation. The background noise is suppressed by the image pre-processing. The probability of detecting and false alarm are used to determine the threshold of image. Then its performance is evaluated, and some application problems are discussed. The point-trajectory sharing is used to process the candidate trajectories, which can abstract the small target accurately. Finally, the algorithm is verified feasible and performs well in the detection, recognition and track under low signal to noise ratio through simulation experiment.
Cite this paper
Zhao, X., & Liu, X. (2010). Improved dynamic programming algorithm for tracking small target of low-manoeuvring. https://doi.org/10.1109/wcica.2010.5554666
Zhao, Xiaodong, and Xiangyang Liu. “Improved dynamic programming algorithm for tracking small target of low-manoeuvring.” 2010, pp. 2445–48, https://doi.org/10.1109/wcica.2010.5554666.
Zhao, Xiaodong, and Xiangyang Liu. 2010. “Improved dynamic programming algorithm for tracking small target of low-manoeuvring.” https://doi.org/10.1109/wcica.2010.5554666.
Zhao, X. and Liu, X. (2010) ‘Improved dynamic programming algorithm for tracking small target of low-manoeuvring’. Available at: https://doi.org/10.1109/wcica.2010.5554666.
@article{zhao2010improved,
title = {{Improved dynamic programming algorithm for tracking small target of low-manoeuvring}},
author = {Zhao, Xiaodong and Liu, Xiangyang},
pages = {2445--2448},
year = {2010},
doi = {10.1109/wcica.2010.5554666}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.