Cost-reference Particle Filter Bank Based Track-before-detecting Algorithm

Jin LU; Xin WANG

doi:10.11999/JEIT210234

Volume 43 Issue 10

Oct. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(10): 2815-2823

Jin LU, Xin WANG. Cost-reference Particle Filter Bank Based Track-before-detecting Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2815-2823. doi: 10.11999/JEIT210234

Citation:

Jin LU, Xin WANG. Cost-reference Particle Filter Bank Based Track-before-detecting Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2815-2823. doi: 10.11999/JEIT210234

Jin LU, Xin WANG. Cost-reference Particle Filter Bank Based Track-before-detecting Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2815-2823. doi: 10.11999/JEIT210234

Citation:

Jin LU, Xin WANG. Cost-reference Particle Filter Bank Based Track-before-detecting Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2815-2823. doi: 10.11999/JEIT210234

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Cost-reference Particle Filter Bank Based Track-before-detecting Algorithm

doi: 10.11999/JEIT210234

Jin LU^,,
Xin WANG

College of Electronic Information and Artificial Intelligence, Shaanxi University of Science & Technology, Xi’an 710021, China

Funds: The National Natural Science Foundation of China (61801281), The Scientific Research Project of Shaanxi Provincial Department of Education (17JK0084)

Received Date: 2021-03-22
Rev Recd Date: 2021-08-18

Available Online: 2021-09-16

Publish Date: 2021-10-18

Abstract

Abstract

Detection and tracking of low signal-to-noise ratio nonlinear frequency modulated signal can be effectively solved by Track-Before-Detecting (TBD) algorithms based on particle filters. However, the algorithms are high in computational complexity and hard to be implemented in parallel. Furthermore, because of the comparatively long convergence processing, the detection and state estimation capabilities of the particle filters based methods are limited. In this paper, a cost-reference particle filter bank is proposed, which does not depend on the distribution of the system and has an entirely parallel structure. Then a detection method based on the cost-reference particle filter bank is proposed. Simulation results of two nonlinear frequency modulated signals detection and estimation illustrate that the propose method has better performance in detection, estimation, and running speed than similar methods, such as particle filter based track-before-detecting algorithm, Rutten particle filter based TBD algorithm.
- Nonlinear frequency modulated signal,
- Track-Before-Detecting (TBD),
- Instantaneous frequency curve estimation,
- Cost-reference particle filter,
- Filter bank

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References(19)

References

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