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

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

255
views

0
downloads

[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

Suggestions

OpenMETU
Core

Neural network method for direction of arrival estimation with uniform cylindrical microstrip patch array Caylar, S.; Dural, G.; Leblebicioğlu, Mehmet Kemal (Institution of Engineering and Technology (IET), 2010-02-01) In this study, a new neural network algorithm is proposed for real-time multiple source tracking problem with cylindrical patch antenna array based on a previously reported Modified Neural Multiple Source Tracking (MN-MUST) algorithm. The proposed algorithm, namely cylindrical microstrip patch array modified neural multiple source tracking (CMN-MUST) algorithm implements MN-MUST algorithm on a cylindrical microstrip patch array structure. CMN-MUST algorithm uses the advantage of directive pattern of microst...
A fast and automatically paired 2-D direction-of-arrival estimation with and without estimating the mutual coupling coefficients Filik, Tansu; Tuncer, Temel Engin (American Geophysical Union (AGU), 2010-06-26) A new technique is proposed for the solution of pairing problem which is observed when fast algorithms are used for two-dimensional (2-D) direction-of-arrival (DOA) estimation. Proposed method is integrated with array interpolation for efficient use of antenna elements. Two virtual arrays are generated which are positioned accordingly with respect to the real array. ESPRIT algorithm is used by employing both the real and virtual arrays. The eigenvalues of the rotational transformation matrix have the angle ...
Nonplanar trapezoidal tooth log-periodic antennas: Design and electromagnetic modeling Ergül, Özgür Salih (American Geophysical Union (AGU), 2005-10-18) Nonplanar trapezoidal tooth log-periodic (LP) antennas are investigated by combining the wisdom of theoretical design procedures with the power of accurate numerical simulation environments. Once the theoretical design is completed, electromagnetic simulations employing accurate integral equation solvers are utilized to test and correct the original design. A two-element array of trapezoidal tooth LP antennas is designed. The array features beam-steering ability as a novelty, in addition to frequency indepe...
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) ...
EFFICIENT SOLUTIONS OF METAMATERIAL PROBLEMS USING A LOW-FREQUENCY MULTILEVEL FAST MULTIPOLE ALGORITHM Ergül, Özgür Salih (EMW Publishing, 2010-01-01) We present fast and accurate sloutions of electromagnetics problems involving realistic metamaterial structures using a lowfrequency multilevel fast multipole algorithm (LF-MLFMA). Accelerating iterative solutions using robust preconditioning techniques may not be sufficient to reduce the overall processing time when the ordinary high-frequency MLFMA is applied to metamaterial problems. The major bottleneck, i.e., the low-frequency breakdown, should be eliminated for efficient sloutions. We show that the co...

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.