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

Caylar, Selcuk
Leblebicioğlu, Mehmet Kemal
Dural, Gülbin
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) are trained for detection of the angular sectors which have source or sources. A spatial filter stage applied individually to the every angular sector which is classified in the first stage as having source or sources. Each individual spatial filter is designed to filter out the signals coming from all the other angular sectors outside the particular source detected angular sector. This stage considerably improves the performance of the algorithm in the case where more than one angular sector have source or sources at the same time. Insertion of this spatial filtering stage is the main contribution of this paper. The third stage consists of a neural network trained for DoA estimation. In all three stages neural network's size and the training data are considerably reduced as compared to the previous approach, without loss of accuracy
IEEE Antennas and Propagation Society International Symposium, APS 2006


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Çaylar, Selçuk; Dural Ünver, Mevlüde Gülbin; Department of Electrical and Electronics Engineering (2007)
In this study, a neural network(NN) based algorithm is proposed for real time multiple source tracking problem based on a previously reported work. The proposed algorithm namely modified neural network based multiple source tracking algorithm (MN-MUST) performs direction of arrival(DoA) estimation in three stages which are the detection, filtering and DoA estimation stages. The main contributions of this proposed system are: reducing the input size for the uncorrelated source case (reducing the training tim...
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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 ef...
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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,” presented at the IEEE Antennas and Propagation Society International Symposium, APS 2006, Albuquerque, NM, Amerika Birleşik Devletleri, 2006, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=36148970924&origin=inward.