A new neural network approach to the target tracking problem with smart structure

Date

2006-10-03

Author

Caylar, Selcuk
Leblebicioğlu, Mehmet Kemal
Dural, Guelbin

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[1] A modified neural network - based algorithm ( modified neural multiple-source tracking algorithm (MN-MUST)) is proposed for real-time multiple-source tracking problem. The proposed approach reduced the input size of the neural network without any degradation of the accuracy of the system for uncorrelated sources. In addition, a spatial filtering stage that considerably improves the performance of the system is proposed to be inserted. It is observed that the MN-MUST algorithm provides an accurate and efficient solution to the target-tracking problem in real time.

Subject Keywords

Electrical and Electronic Engineering, General Earth and Planetary Sciences, Condensed Matter Physics

URI

https://hdl.handle.net/11511/38108

Journal

RADIO SCIENCE

DOI

https://doi.org/10.1029/2005rs003301

Collections

Department of Electrical and Electronics Engineering, Article

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A new neural network approach to the target tracking problem with smart structure Caylar, Selcuk; Leblebicioğlu, Mehmet Kemal; Dural, Gülbin (2006-12-01) The algorithm presented in this paper, namely the modified neural multiple source tracking algorithm (MN-MUST) is the modified form of the recently published work, a NN algorithm, the neural multiple-source tracking (N-MUST) algorithm, was presented for locating and tracking angles of arrival from multiple sources. MN-MUST algorithm consists of three stages that are classified as the detection, filtering and DoA estimation stages. In the first stage a number of radial basis function neural networks (RBFNN) ...
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Citation Formats

S. Caylar, M. K. Leblebicioğlu, and G. Dural, “A new neural network approach to the target tracking problem with smart structure,” RADIO SCIENCE, pp. 0–0, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38108.