Comparison of corellation method and artifitial neural networks for determining of object position by ultrawideband fields
Abstract
Background: Global and local positioning systems have a wide area of civil and military applications. Transport, logistics, precise agriculture, industrial technologies, safety systems need a strict definition of objects position on plane or in space. Existing modern positioning systems have some drawbacks in utilization and restrictions in application.
Objectives: To improve a system of local positioning on a plane that does not need a time synchronization using the impulse ultrawideband electromagnetic field of two spaced bow-tie antennas and analysis and recognition of time forms of received waves by artificial neural networks and cross correlation method. To carried out the investigation of stability of the positioning system operation in presence of an interference in the form of additive white noise.
Materials and methods: The electromagnetic simulation of excitation and radiation of the antennas is carried out by finite difference time domain method. The classification of received impulse form by known samples is realized by two alternative method, i.e. correlation approach and artificial neural networks.
Results: The utilization of correlation method and artificial neural networks permitted to realize the positioning system with angular resolution of 1 degree. The probability distributions of recognized angles for different levels of additive noise in received signals for these two techniques are obtained.
Conclusion: The comparison of artificial neural network application and correlation method for angle recognition shows that artificial neural networks can demonstrate a better precision than correlation approach. artificial neural network gives a correct angle recognition after statistical averaging of classification results even for the signal to noise ratio 0 dB. Artificial neural networks demonstrate a in three times shorter time of numerical simulation than we need for cross correlation function calculation. The application of shorter electromagnetic impulse increases the quality of angle classification in presence of the noise for both presented methods.
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References
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