Time filter

Source Type

Beijing, China

Wang B.,Unit 61081 | Wang B.,Zhengzhou University | Sui L.,Zhengzhou University | Wang W.,Unit 61741 | Ma C.,Unit 61206
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | Year: 2015

One of key issues in the aspect of GPS-based attitude determination that must be solved is to estimate the unknown integer ambiguities. Single-epoch attitude ambiguity resolution can be achieved by using MC-Lambda method, which fully exploited the known geometry constraints of the multi-antennae configuration. This method does not need to consider cycle slip problem. However, the float solution precision of integer ambiguity is low based on GPS pseudo-range and carrier phase observations, which leads to large ambiguity search space and low search efficiency. For this reason, choosing the direction cosine matrix to describe the attitude and GPS/Gyro attitude determination model was established. The float solution of integer ambiguity was calculated by matrix kalman filter algorithm, and then the fixed solution of integer ambiguity was obtained by MC-Lambda method. Simulation experimental results showed that the accuracy of float solution by Kalman filter algorithm with constraints of direction cosine matrix are improved, so the computational efficiency and the fixing success rate of the fixed integer ambiguity are all improved, particularly when GPS observations is in the bad observation condition. ©, 2015, Wuhan University. All right reserved. Source

Zhang X.-F.,CAS Institute of Geology and Geophysics | Zhang X.-F.,Science and Technology on Aerospace Flight Dynamics Laboratory | Liu L.-B.,CAS Institute of Geology and Geophysics | Liu S.-T.,Unit 61741 | Wu Y.-P.,Unit 61741
Chinese Journal of Geophysics (Acta Geophysica Sinica) | Year: 2015

During geomagnetic storms, the coupling magnetosphere-ionosphere-thermosphere system is a rather complex phenomenon, and the thermospheric mass density exhibits large deviations from the climatological behavior upon the conjunct effect of Joule/particle heating, Lorentz force, thermal expansion, upwelling, and horizontal wind circulation. Due to different weight effects, thermospheric responses might vary with different storms, and even for the same storm case resulting from unlike methods of data process. In order to know more about the seasonal, magnetic local time (MLT) and latitude dependencies and the time delay characteristic of the thermospheric response to geomagnetic storms, we investigate the thermospheric response to 267 geomagnetic storms in which the Dst minimum, Dstmin, is below -50 nT during 2002-2008. The data of thermospheric mass density normalized to 400 km is derived from the high-accuracy accelerometer on board the CHAMP satellite. Each orbit is first divided into an ascending and a descending half, which are subdivided into five latitudinal segments, namely ±60°, ±30°and 0°. In order to investigate the dependence of MLT, density data are sorted into 4 different MLT sectors: 05:00MLT to 09:00MLT as the dawn sector, 10:00MLT to 16:00MLT as the noon sector, 17:00MLT to 21:00MLT as the dusk sector, and 22:00MLT to 04:00MLT as the night sector. To investigate seasonal variations, the available data are subdivided into three local seasons: the northern hemisphere winter (December-February, DJF), combined equinoxes (March-May, MAM, and September-November, SON), and the northern hemisphere summer (June-August, JJA). Dstmin is used to identify four categories of geomagnetic storms: weak storms (-30>Dstmin ≥-50 nT), moderate storms (-50>Dstmin≥-100 nT), intense storms (-100>Dstmin≥-200 nT) and great storms (Dstmin <-200 nT). By this means the effects of magnetic local time, latitude, season and intensity of storm are separated. Since the quiet-time density (ρq) shows much dependence on the solar activity, season, and local time, the density deviation from quiet-time values, rather than the total storm-time density (ρ) itself, seems better suited for describing the storm effect. There are two ways to define the deviation, one is the absolute difference (δρa=ρ-ρq), and the other is the percentage difference (δρr=δρa/ρq). As there is no general agreement on which expression is more appropriate, both the absolute and the percentage variations for each event are presented to produce a complete picture. Considering that the MSIS model underestimates the total mass density in the crest region resulting from its missing double peaks at low latitudes completely, the CHAMP measurements from the day prior to the storm is taken as a quiet-time reference density. The thermospheric mass density reacts after geomagnetic activity with a delay time, which is expected to depend on latitudes, MLT and seasons. Besides the superposed epoch comparisons for different conditions during storms, in which epoch time zero is chosen as the time of Dstmin, time delays between Dstmin and maxima of densities which are divided into different season, latitude, and MLT, have been computed for each storm event and the statistical result accounted for the biggest proportion describes quantitatively the time intervals. Besides some characteristics that have been mentioned in previous research, our statistical results reveal some new or more detailed variations about the responses of thermospheric mass density to geomagnetic storms, and the main conclusions are as follows: 1) The absolute enhancements of thermospheric density during storms show a north-south asymmetry dependence on both the intensity of storms and the magnetic local time. In the northern hemisphere summer, for great storms and the nightside of moderate storms, controlled by higher Joule heating rates and prevailing summer-to-winter winds, stronger density enhancements occur in the summer hemisphere. On the dayside of northern hemisphere summer, due to the faster propagation of the disturbance from high to low latitudes in the summer hemisphere, the thermospheric density enhancements happen near 30 degree in the northern (summer) hemisphere peak ahead of those in the southern (winter) hemisphere. While probably affected by the higher rate of the energy transferred to the thermosphere partly dependent on the strength of the background magnetic field which is weaker in the Southern hemisphere due to shifted position of the dipole in positive Z-direction, on the dayside of northern hemisphere summer during intense and moderate storms, δρa of the southern (winter) hemisphere was stronger than that of the northern (summer) hemisphere, and on the dayside near equinoxes for most storms, the thermospheric density enhancements near 30 degree of the northern hemisphere peaked 1~2 h ahead of that of the southern hemisphere. 2) Thermospheric densities of low latitudes enhancing after that of high latitudes during storms, the delay time during great storms is shorter than that of other weaker storms, and the time-lag during nightsie is shorter than that of dayside, indicating that propagation of energy deposited in polar regions to lower latitudes seems faster in the night-side sector during stronger storms. Only for great storms, the percentage difference δρr of dayside sector in low latitudes is higher than that of high latitudes, and the density of low latitudes peaks earlier than that of high latitudes, implying some other heating source in low latitudes play an important role during great storms. 3) Affected by the storm-time disturbance-driven thermospheric meridional circulation, the thermospheric density enhancements of the equator approach their maxima fastest at the equinoxes, and the time delay relative to Dstmin is 1 h, 2 h for the density of dayside, night-side, respectively. At the nightside either in summer or in winter, the thermospheric density of the equator tends to peak 3 h after Dstmin. While for the dayside, the time interval that thermospheric density at the equator approached its maximum is dependent on seasons, and it is shortest for the northern hemisphere winter. 4) At dayside, the thermospheric density enhancement at the equator tends to peak after 3h the density of 60oapproached its maximum, which is independent of seasons. While at nightside of equinoxes and northern hemisphere winter, the thermospheric density at the equator tends to peak before that of high latitudes done, meanwhile the density enhancement maxima of those latitudes were comparable, implying some other heating source working. Although the thermospheric density at the equator tends to respond with 0~2 h delay relative to the response of Dst index during most storms, while in some cases, the density at the equator enhances before the Dst index responded. ©, 2015, Science Press. All right reserved. Source

Zhang X.-F.,Unit 61741 | Zhang X.-F.,Science and Technology on Aerospace Flight Dynamics Laboratory | Liu J.,Unit 61741 | Wu Y.-P.,Unit 61741 | And 3 more authors.
Chinese Journal of Geophysics (Acta Geophysica Sinica) | Year: 2013

Using hourly averaged data of >2 MeV electron fluxes measured with GOES 7/9/10/11 satellites during 1988-2010, this paper investigates statistically the conditions of solar wind and geomagnetic activities during relativistic electrons flux (Fe) enhancements, and describes the dependence of relativistic electrons at geosynchronous orbit (GEO) on local time and magnetic storms. The results are as follows: (1) The local time dependence of GEO relativistic electrons is influenced by solar wind and geomagnetic activities. The noon/midnight electron flux ratio grows with higher solar wind velocity (Vsw). On conditions of the Dst index above -50 nT, relativistic electrons show regular variation with local time, while during storms with Dst<-50 nT, the maximum electrons flux may not measured at local noon. During the declining phase of a solar cycle relativistic electron fluxes approaching maximum, the solar wind velocity, Kp index and the cube root of solar wind density (N) show better correlations with electron fluxes after 39~57 h, 57~80 h and 12~24 h, respectively. (2) Before about two years of solar minimum and near the equinoxes, occurrence frequencies of intense relativistic electron flux enhancement events, in which the daily maximum relativistic electron flux Femax≥104 pfu, increase, while weaker events with 104>Femax≥103 pfu exhibit no such solar cycle and seasonal dependences. For most intense events, relativistic electron fluxes begin to increase during main phases of magnetic storms, while for weaker events, relativistic electron fluxes tend to increase during recovery phases. (3) The solar wind density shows as a good indicator of subsequent relativistic electron activities. For most electron flux enhancement events, relativistic electron flux decreases to its minimum after 0~1 days of the maximum solar wind density, Nmax, while approaching the maximum after 0~2 days of the minimum solar wind density, Nmin. (4) Above 90% of relativistic electron events occurred on conditions of high wind solar velocities and geomagnetic disturbances, which are as follows: Vswmax>516 km/s, Dstmin<-31 nT, Nmin<2.8 cm-3, Nmax>14.1 cm-3, Bzmin<-2.9 nT, AEmax>698 nT. (5) For all magnetic storms, occurrence probability of daily maximum electron flux above 103pfu after Dstmin, is about 53%, the percent of intense, weak events being 36%, 64%, respectively, which is hardly affected by intensities of storms. During storms, solar wind velocity, density, and the AE index are important indicators for subsequent relativistic electron activities. Source

Discover hidden collaborations