Algorithm Of Ensemble Pulsar Time And Application Of Pulsar Time

Pulsars, rapidly rotating neutron stars,have extremely stable rotating periods. Millisecond pulsars in particular have the derivative of rotating period up to 10 ?1 9 ~10?21, and are thus called the most stable clock of nature. These characteristics enable pulsars to be used in timing and monitoring the long-term stability of atomic clocks. The pulsar time defined by single pulsar is influenced by several noise resources, to weaken these influences, ensemble analysis method can be used to obtain the ensemble pulsar time so that the long-term stability of ensemble pulsar time can be improved. In this thesis, four algorithms, classical weighted average algorithm, wavelet and wavelet packet analysis algorithm, Wiener filtration analysis algorithm and Wiener filtration analysis in wavelet domain, are applied to synthetically make an ensemble pulsar time, where data are the residuals of the two millisecond pulsars PSR B1855+09 and PSR B1937+21 observed by Arecibo Observatory.The author investigated the classical weighted average algorithm developed by Petit and in which only one weight can be chosen within the whole interval of the observation on each single pulsar time, and the criterion for weight is the stabilityσz2 (τ) of each single pulsar time.The author investigated the wavelet multi-resolution analysis and wavelet packet analysis, and developed an ensemble pulsar time algorithm based on both of the two methods. Ensemble pulsar time can be obtained by decomposing the observation residuals of pulsars, extracting the components of different frequency domain, and then choosing the weight according to the stability of different component denoted with wavelet variance.The author studied some theories on filters. The pulsar timing residuals are caused by reference atomic clock and pulsar itself, and the two influences are uncorrelative. Considering this and the peculiarity of Wiener filtration, author brought forward an ensemble pulsar time algorithm of Wiener filtration. This technology allows to separate the error from an atomic clock and a pulsar itself in the post-fit pulsar timing residuals. The method allows to filter the atomic scale component from the pulsar phase variations and to integrate the remains to the ensemble pulsar time, and weights are chosen according to the mean square root.Wavelet analysis and Wiener filtration algorithm are combined and a new ensemble pulsar time algorithm called Wiener filtration analysis in wavelet domain are presented in this thesis, which can remove the influence of noise more effectively. The pulsar timing residuals are decomposed to different components with wavelet, and the influences of atomic clock of different components are removed by Wiener filtration, then the ensemble pulsar time can be obtained by inversing the wavelet transform acting on these remains.The computed result indicates that the latter three algorithms are far better than the first one, and Wiener filtration analysis in wavelet domain could be the best one among.At last, some primary information about the current status of X-ray pulsar autonomous navigation being developed by America and some other developed countries was studied. It is found that this research would have extensive application in the future, and China has been primarily qualified to carry out the study.