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An Improved Ant Colony Optimization for Solving Task Scheduling Problem in Radar Signal Processing System

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Abstract

In order to solve the problem of low efficiency and high error rate in the manual establishment of the logical relationship mapping table, this paper proposes an implementation method for automatically establishing a mapping relation table based on Ant Colony System (ACS), and writes a corresponding GUI development environment based on Qt. Aiming at the shortcomings of ACS algorithm such as slow convergence and easy to fall into local optimal, the pheromone volatilization factor and expected heuristic factor of ACS are adaptively improved in this paper, and then the search strategy of 2-opt algorithm is integrated to make ACS jump out of the local optimal solution and improve the accuracy of mapping result. The experimental results show that the proposed algorithm can search for the optimal mapping scheme to satisfy the constraints. The quality and generation speed of the mapping scheme have been greatly improved compared to manual establishment methods, which can effectively improve the performance of the radar signal processing system.

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Data Availability

The datasets analysed during the current study are not publicly available due to radar signal processing test data involves confidentiality.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Number 61973234) and Tianjin Natural Science Foundation Project (Grant Number 18JCYBJC88400).

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Authors and Affiliations

  1. School of Control Science and Engineering, Tiangong University, Tianjin, 300387, China

    Guowei Xu, Hui Lin, Yi Cheng & Shuo Li

  2. School of Mechanical Engineering, Tiangong University, Tianjin, 300387, China

    Guowei Xu

  3. Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tiangong University, Tianjin, 300387, China

    Yi Cheng

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  1. Guowei Xu
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  2. Hui Lin
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Correspondence to Guowei Xu.

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Xu, G., Lin, H., Cheng, Y. et al. An Improved Ant Colony Optimization for Solving Task Scheduling Problem in Radar Signal Processing System. J Sign Process Syst 95, 333–350 (2023). https://doi.org/10.1007/s11265-023-01838-y

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