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Identification Of X-ray Pulsar Accumulation On Pulse Profile Based On SOPC

Posted on:2015-11-08Degree:MasterType:Thesis
Country:ChinaCandidate:S S LiuFull Text:PDF
GTID:2322330518489101Subject:Physical Electronics
Abstract/Summary:PDF Full Text Request
X-ray pulsar autonomous navigation technology with high accuracy,good concealment,high security,low cost and other significant advantages,is the main research direction of spacecraft autonomous navigation.Because of X-ray wavelength too short to detect X-ray pulsar signals on the ground,therefore,the development of X-ray pulsar navigation simulation experiment system is very necessary on the ground,can provide ground experiments system data support for future X-ray pulsar navigation in space,the occurrence of reducing the uncertainty elements of the test.The object of this study is the development of X-ray detectors stitching time measurement circuit is the background and the X-ray pulsar navigation ground test systems simulated pulse photon arrival time data for the study of object.Launching a cumulative pulse profile recognition algorithm of the photon arrival time data accumulated,in order to combine the front of the TDC and the superposition of epoch module study proposed solutions based on SOPC technology.The main contents are as follows:Firstly,description the purpose and significance of this project,from the X-ray pulsar navigation technology's basic theory,a detailed exposition of the historical development and research status abroad based on the X-ray pulsar navigation.Meanwhile SOPC technology and accumulated pulse profile recognition methods were explored,and lay a solid foundation for the subsequent chapters research.Secondly,existing the issue of the photon phase histogram might not get a pulse profile,and raised to the maximum peak corresponding BIN around the outline of the three BIN solutions corresponding to the amplitude setting a threshold value,the simulation results show that this method is feasible.In order to reduce the noise impact on the identification,respectively,using a wavelet-based threshold and a EMD-based threshold method for accumulated pulse profile denoising study.For the cumulative pulse profile is relatively high SNR,when using the threshold method to deal with accumulation pulse profiles is still exist a problem that useful information is also filtered,and proposed a combination method of denoising cumulative pulse profile based on EMD and median filtering.Simulation results show that this method can effectively filter the cumulative pulse profile noise.Due to the epochs superposition of different for the start time,the cumulative pulse profile occurs shift issue with the standard pulse profile phase.As a result,proposed the treatment for bispectra dimension reduction after cumulative pulse profile recognition based on singular value decomposition.This method first bispectral transformation cumulative pulse profile,extraction translation invariant feature values,and then use the singular value decomposition method for bispectral feature dimension reduction,feature vectors obtained for final identification.Simulation results show that the method used to identify the cumulative pulse profile is feasible.Finally,build a corresponding hardware platform on Xilinx Virtex-? series FPGA chip XC2VP30 as the core of the development board,and by making crosstool chain,cutting Linux kernel and making root file system,the success of Linux ported to XUP Virtex-? Pro,consisting of an experimental simulation system.In this environment designed a identification system of the X-ray pulsar navigation ground test system that can be epochs superimposed the front of the photons with five different pulsar cycle.After got five phases the phase of the photon histogram,respectively lanuched its pulse profile determination,denoising,feature extraction,and ultimately identify the source of emulation simulated is which the outline of pulsar signal.
Keywords/Search Tags:SOPC, pulsars, the cumulative pulse profile, the cumulative pulse profile identification, wavelet transform, EMD, median filter, feature extraction, dual spectrum, singular value decomposition
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