Neural network based beamforming for linear and cylindrical array applications

Güreken, Murat
In this thesis, a Neural Network (NN) based beamforming algorithm is proposed for real time target tracking problem. The algorithm is performed for two applications, linear and cylindrical arrays. The linear array application is implemented with equispaced omnidirectional sources. The influence of the number of antenna elements and the angular seperation between the incoming signals on the performance of the beamformer in the linear array beamformer is studied, and it is observed that the algorithm improves its performance by increasing both two parameters in linear array beamformer. The cylindrical array application is implemented with twelve microstrip patch antenna (MPA) elements. The angular range of interest is divided into twelve sectors. Since three MPA elements are used to form the beam in each sector, the input size of the neural network (NN) is reduced in cylindrical array. According to the reduced size of NN, the training time of the beamformer is decreased. The reduced size of the NN has no degradation in forming the beams to the desired directions. The angular separation between the targets is an important parameter in cylindrical array beamformer.


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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...
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Kavut, Selçuk; Yücel Diker, Melek; Department of Electrical and Electronics Engineering (2008)
We introduce a steepest-descent-like search algorithm for the design of Boolean functions, yielding multiple desirable cryptographic properties in their Walsh and autocorrelation spectra together. The algorithm finds some Boolean functions on 9, 10, 11, 13 variables with very good cryptographic properties unattained in the literature. More specifically, we have discovered 9-variable rotation symmetric Boolean functions (RSBFs) having nonlinearity of 241, which exceeds the bent concatenation bound and has re...
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Olgun, Muhammet Ertuğ; Akar, Gözde; Department of Electrical and Electronics Engineering (2008)
In this work, a new deinterleaving algorithm that can be used as a part of an ESM system and its implementation by using an FPGA is studied. The function of the implemented algorithm is interpreting the complex electromagnetic military field in order to detect and determine different RADARs and their types by using incoming RADAR pulses and their PDWs. It is assumed that RADAR signals in the space are received clearly and PDW of each pulse is generated as an input to the implemented algorithm system. Cluste...
Fpga implementation of jointly operating channel estimator and parallelized decoder
Kılcıoğlu, Çağlar; Yılmaz, Ali Özgür; Department of Electrical and Electronics Engineering (2009)
In this thesis, implementation details of a joint channel estimator and parallelized decoder structure on an FPGA-based platform is considered. Turbo decoders are used for the decoding process in this structure. However, turbo decoders introduce large decoding latencies since they operate in an iterative manner. To overcome that problem, parallelization is applied to the turbo codes and the resulting parallel decodable turbo code (PDTC) structure is employed for coding. The performance of a PDTC decoder and...
Hierarchical parallelisation strategy for multilevel fast multipole algorithm in computational electromagnetics
Ergül, Özgür Salih (Institution of Engineering and Technology (IET), 2008-01-03)
A hierarchical parallelisation of the multilevel fast multipole algorithm (MLFMA) for the efficient solution of large-scale problems in computational electromagnetics is presented. The tree structure of MLFMA is distributed among the processors by partitioning both the clusters and the samples of the fields appropriately for each level. The parallelisation efficiency is significantly improved compared to previous approaches, where only the clusters or only the fields are partitioned in a level.
Citation Formats
M. Güreken, “Neural network based beamforming for linear and cylindrical array applications,” M.S. - Master of Science, Middle East Technical University, 2009.