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Electronics 2019, 8(1), 51; https://doi.org/10.3390/electronics8010051

A Novel Multicomponent PSO Algorithm Applied in FDE–AJTF Decomposition

1
School of Electronics and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
2
Institute of Remote Sensing Information, Beijing 100192, China
3
The 96901 Unit of PLA, Beijing 100094, China
4
Network Management Center, CAPF, Beijing 100089, China
*
Author to whom correspondence should be addressed.
Received: 29 October 2018 / Revised: 5 December 2018 / Accepted: 21 December 2018 / Published: 2 January 2019
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Abstract

The echo of maneuvering targets can be expressed as a multicomponent polynomial phase signal (mc-PPS), which should be processed by time frequency analysis methods, while, as a modified maximum likelihood (ML) method, the frequency domain extraction-based adaptive joint time frequency (FDE–AJTF) decomposition method is an effective tool. However, the key procedure in the FDE–AJTF method is searching for the optimal parameters in the solution space, which is essentially a multidimensional optimization problem with different extremal solutions. To solve the problem, a novel multicomponent particle swarm optimization (mc-PSO) algorithm is presented and applied in the FDE–AJTF decomposition with the new characteristic that can extract several components simultaneously based on the feature of the standard PSO, in which the population is divided into three groups and the neighborhood of the best particle in the optimal group is set as the forbidden area for the suboptimal group, and then two different independent components can be obtained and extracted in one extraction. To analyze its performance, three simulation tests are carried out and compared with a standard PSO, genetic algorithm, and differential evolution algorithm. According to the tests, it is verified that the mc-PSO has the best performance in that the convergence, accuracy, and stability are improved, while its searching times and computation are reduced. View Full-Text
Keywords: maneuvering target echo; mc-PPS; time frequency analysis; FDE–AJTF decomposition; optimal algorithm; mc-PSO maneuvering target echo; mc-PPS; time frequency analysis; FDE–AJTF decomposition; optimal algorithm; mc-PSO
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Yu, L.; Lao, G.; Li, C.; Sun, Y.; Li, Y. A Novel Multicomponent PSO Algorithm Applied in FDE–AJTF Decomposition. Electronics 2019, 8, 51.

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