An extended chirp scaling algorithm for spaceborne sliding spotlight synthetic aperture radar imaging

A system impulse response with low sidelobes is critical in synthetic aperture radar（SAR） images because sidelobes contribute to noise and interfere with nearby scatterers. However,the conventional tricks of sidelobe suppression are unable to be exactly applied to the case of spaceborne sliding spotlight SAR due to great azimuth shifts in both time and frequency domains. In this paper, an extended chirp scaling algorithm is presented for spaceborne sliding spotlight SAR data imaging. The proposed algorithm firstly uses the spectral analysis（SPECAN） technique to avoid the azimuth spectrum folding effect and then employs the chirp scaling（CS） algorithm to achieve data focusing, i.e., the so-called two-step approach. To suppress the sidelobe level, an efficient strategy for the azimuth spectral weighting which only involves matrix multiplications and short fast Fourier transformations（FFTs） is proposed, which is a post-process executed on the focused SAR image and particularly simple to be implemented. The SAR image processed by the proposed extended CS algorithm is very precise and perfectly phase-preserving. In the end, computer simulation results verify the analysis and confirm the validity of the proposed algorithm.     

Integration and calibration of a multi slit spectropolarimeter

Multi-slit spectropolarimeter is a next-generation spectropolarimeter to obtain vector magnetic field information at high spatial, spectral, and temporal resolution for studying the magnetic structures on the Sun. Once developed, it can be used as ground based instrument at solar observatories, also as a space payload for various solar missions. A high spectral resolution is invariably an important parameter for accurate vector magnetic field measurements and faster cadence is required for the study of dynamical evolution of structures (e.g., solar flares, sunspots etc.) on the Sun and hence better understanding on the physics behind their evolution.     

Identification of a 2D turbulent wind spectrum

Turbulent wind spectrum models usually involve nonrational terms. For such models the development of a Markovian time simulator relies on a rational approximation obtained by the way of an identification stage. This paper presents a general method to manage this identification stage, that provides us with a family of stable rational approximations which is proved to converge towards the true model as the dimension increases. We first give an exact but infinite dimensional state space representation of the spectrum. It is based on the use of a diffusive equation. For bi-dimensional (2D) signals it also uses decoupling by spatial Fourier transformation. Then the discretization of this exact model leads easily to stable finite dimensional approximations over a prescribed frequency range. This approach is applied to the identification of a theoretical 2D turbulent wind spectrum, and of a 1D turbulent wind spectrum estimated from in flight recorded data.     

Stability of relative equilibria of the full spacecraft dynamics around an asteroid with orbit–attitude coupling

The full dynamics of spacecraft around an asteroid, in which the spacecraft is considered as a rigid body and the gravitational orbit–attitude coupling is taken into account, is of great value and interest in the precise theories of the motion. The spectral stability of the classical relative equilibria of the full spacecraft dynamics around an asteroid is studied with the method of geometric mechanics. The stability conditions are given explicitly based on the characteristic equation of the linear system matrix. It is found that the linearized system decouples into two entirely independent subsystems, which correspond to the motions within and outside the equatorial plane of the asteroid respectively. The system parameters are divided into three groups that describe the traditional stationary orbit stability, the significance of the orbit–attitude coupling and the mass distribution of the spacecraft respectively. The spectral stability of the relative equilibria is investigated numerically with respect to the three groups of system parameters. The relations between the full spacecraft dynamics and the traditional spacecraft dynamics, as well as the effect of the orbit–attitude coupling, are assessed. We find that when the orbit–attitude coupling is strong, the mass distribution of the spacecraft dominates the stability of the relative equilibria; whereas when the orbit–attitude coupling is weak, both the mass distribution and the traditional stationary orbit stability have significant effects on the stability. We also give a criterion to determine whether the orbit–attitude coupling needs to be considered.     

星敏感器光谱探测能力用地面模拟测试系统设计

为实现对星敏感器光谱探测能力的测试和标定, 研制了一套可模拟恒星光谱的地面标定系统, 要求其光谱模拟精度优于10%. 采用光谱分布可控、光强可调的模拟照明系统作为地面标定系统的核心器件来模拟恒星光谱变化, 设计高成像质量准直光学系统使模拟星图成平行光出射, 在光学系统出瞳处产生星图, 完成具有恒星光谱信息的高精度星图模拟. 进而利用Lighttools建立标定系统的光谱仿真模型, 仿真结果表明恒星光谱模拟精度优于10%.      

Identifying areas of high economic-potential copper mineralization using ASTER data in the Urumieh–Dokhtar Volcanic Belt,Iran

This study investigates the application of spectral image processing methods to ASTER data for mapping hydrothermal alteration zones associated with porphyry copper mineralization and related host rock. The study area is located in the southeastern segment of the Urumieh–Dokhtar Volcanic Belt of Iran. This area has been selected because it is a potential zone for exploration of new porphyry copper deposits. Spectral transform approaches, namely principal component analysis, band ratio and minimum noise fraction were used for mapping hydrothermally altered rocks and lithological units at regional scale. Spectral mapping methods, including spectral angle mapper, linear spectral unmixing, matched filtering and mixture tuned matched filtering were applied to differentiate hydrothermal alteration zones associated with porphyry copper mineralization such as phyllic, argillic and propylitic mineral assemblages.     

Studies of the geocenter motion using 16-years DORIS data

An accuracy of geocenter motion estimation is strongly dependent on the geodetic network size and stations distribution over the Earth’s surface. From this point of view DORIS system has an advantage, as its ground network of beacons consists of more than 50 sites, equally distributed over the Earth’s surface. Aiming to study variations of the geocenter movements, the results of DORIS data analysis for the time span 1993.0–2009.0 (inawd06.snx series), performed at the Analysis Centre of the Institute of astronomy of the Russian Academy of Sciences, have been used. DORIS data processing was made with GIPSY/OASIS II software, developed by Jet Propulsion Laboratory and modified for DORIS data processing by Institute Géographique National. Standard deviations of stations coordinates are estimated at the level 0.5–4.0 cm (internal consistency), depending on the number of satellites used in the solution. RMS of estimated components of the DORIS satellites orbits, compared with the solutions of other IDS analysis centres, do not exceed 1–2 cm. Weekly solutions for coordinates have been transformed from free network solutions (inawd06.snx series) to a well defined terrestrial reference frame ITRF2005 with the use of seven parameters of Helmert transformation, which were examined with a view to study variations of the geocenter movements (ina05wd01.geoc time series). In order to estimate linear trend, amplitudes, periods and phases of geocenter variation a method of linear regression was applied. The evaluated amplitudes of annual variations are of the order of 5–7 mm for X and Y components and 27–29 mm for Z component. Semi-annual amplitudes are also noticeable in all components (1–34 mm for X, Y and Z components). Secular trends in the DORIS geocenter coordinates are: −1.2, −0.1 and −0.3 mm/year for X, Y and Z directions respectively.     

TOPSAR data focusing based on azimuth scaling preprocessing

Both Doppler spectral aliasing and azimuth output time folding simultaneously exist in TOPSAR (Terrain Observation by Progressive Scans) raw data. Resampling in both Doppler frequency and azimuth time domain can resolve the azimuth aliasing problem but with the seriously increased computational complexity and memory consumption. According to the special characteristics of TOPSAR raw data support in the slow time/frequency domain (TFD), the presented azimuth scaling preprocessing step is introduced to not only resolve the Doppler spectral aliasing problem but also reduce the increased azimuth samples. Furthermore, the correction of sawtoothed azimuth antenna pattern (AAP) becomes easy to be implemented. The following conventional stripmap processor can be adopted to focus the residual TOPSAR raw data but with the result of azimuth aliased TOPSAR image. The mosaic approach, which has been presented to unfold azimuth aliased ScanSAR image, is exploited to resolve the problem of azimuth output folding in TOPSAR mode. Simulation results and pulse response parameters are given to validate the presented imaging approach.     

MIMO系统功率比特自适应算法研究

发射功率受限的自适应调制系统,由于调制方式有限,实际使用的发射功率通常小于受限的发射功率,对这一部分剩余功率进行再分配和利用,能够提高频谱效率。文章对M IMO系统中功率和比特自适应算法进行了研究,提出对剩余功率在空域进行再分配的自适应算法。仿真结果表明,在空域采用等功率分配,再进行空域剩余功率再分配,能够提高频谱效率,并且复杂度低,易于实现。     

Estimating sea level rise around Australia using a new approach to account for low frequency climate signals

Regional sea level studies help to identify the vulnerable areas to the sea level rise. This study investigates the impact of climate modes on sea level variations and trends around Australia using altimetry data, climate indices, and sea level records from tide gauge stations. Here, we show that the sea level variations are negatively correlated with climate indices to the north and west of Australia. The spectral analyses of the climate indices and tide gauge data suggest that a low frequency signal with a period of 11 years emerges during the mid 1980s. Since the 25-year length of the satellite altimetry record is yet too short to detect low frequency signals, their effect on the estimation of regional sea level trend is unknown. Therefore, we estimate the sea level trend with consideration of this signal and using a two-step method. All signals with periods shorter than 7.5 years are first removed from sea level time series and then the trend is estimated using the parametric model that includes the 11-year signal. The skill of the parametric model in explaining the variations in sea level anomaly validates the presence of the 11-year signal detected in the spectrograms of the tide gauge data and climate indices. The average sea level trend for the study area is estimated as 3.85 ± 0.15 mm/year.