A time-resolved picture of our Milky Way's early formation history.

The formation of our Milky Way can be split up qualitatively into different phases that resulted in its structurally different stellar populations: the halo and the disk components1-3. Revealing a quantitative overall picture of our Galaxy's assembly requires a large sample of stars with very precise ages. Here we report an analysis of such a sample using subgiant stars. We find that the stellar age-metallicity distribution p(τ, [Fe/H]) splits into two almost disjoint parts, separated at age τ ≃ 8 Gyr. The younger part reflects a late phase of dynamically quiescent Galactic disk formation with manifest evidence for stellar radial orbit migration4-6; the other part reflects the earlier phase, when the stellar halo7 and the old α-process-enhanced (thick) disk8,9 formed. Our results indicate that the formation of the Galaxy's old (thick) disk started approximately 13 Gyr ago, only 0.8 Gyr after the Big Bang, and 2 Gyr earlier than the final assembly of the inner Galactic halo. Most of these stars formed around 11 Gyr ago, when the Gaia-Sausage-Enceladus satellite merged with our Galaxy10,11. Over the next 5-6 Gyr, the Galaxy experienced continuous chemical element enrichment, ultimately by a factor of 10, while the star-forming gas managed to stay well mixed.

The evolution of hot Jupiters revealed by the age distribution of their host stars.

The unexpected discovery of hot Jupiters challenged the classical theory of planet formation inspired by our solar system. Until now, the origin and evolution of hot Jupiters are still uncertain. Determining their age distribution and temporal evolution can provide more clues into the mechanism of their formation and subsequent evolution. Using a sample of 383 giant planets around Sun-like stars collected from the kinematic catalogs of the Planets Across Space and Time project, we find that hot Jupiters are preferentially hosted by relatively younger stars in the Galactic thin disk. We subsequently find that the frequency of hot Jupiters declines with age as [Formula: see text]. In contrast, the frequency of warm/cold Jupiters shows no significant dependence on age. Such a trend is expected from the tidal evolution of hot Jupiters' orbits, and our result offers supporting evidence using a large sample. We also perform a joint analysis on the planet frequencies in the stellar age-metallicity plane. The result suggests that the frequencies of hot Jupiters and warm/cold Jupiters, after removing the age dependence are both correlated with stellar metallicities as [Formula: see text] and [Formula: see text], respectively. Moreover, we show that the above correlations can explain the bulk of the discrepancy in hot Jupiter frequencies inferred from the transit and radial velocity (RV) surveys, given that RV targets tend to be more metal-rich and younger than transits.

A Novel Detection Scheme in Image Domain for Multichannel Circular SAR Ground-Moving-Target Indication.

Circular synthetic aperture radar (CSAR), which can observe the region of interest for a long time and from multiple angles, offers the opportunity for moving-target detection (MTD). However, traditional MTD methods cannot effectively solve the problem of high probability of false alarm (PFA) caused by strong clutter. To mitigate this, a novel, three-step scheme combining clutter background extraction, multichannel clutter suppression, and the degree of linear consistency of radial velocity interferometric phase (DLRVP) test is proposed. In the first step, the spatial similarity of the scatterers and the correlation between sub-aperture images are fused to extract the strong clutter mask prior to clutter suppression. In the second step, using the data remaining after elimination of the background clutter in Step 1, an amplitude-based detector with higher processing gain is utilized to detect potential moving targets. In the third step, a novel test model based on DLRVP is proposed to further reduce the PFA caused by isolated strong scatterers. After the above processing, almost all false alarms are excluded. Measured data verified that the PFA of the proposed method is only 20% that of the comparison method, with improved detection of slow and weakly moving targets and with better robustness.

Vibration compensation method based on instantaneous ranging model for triangular FMCW ladar signals.

Triangular frequency-modulated continuous-wave (FMCW) laser radars (ladars) are extremely sensitive to vibration errors. An FMCW ladar 3D imaging system may suffer from severe vibrations and can use only one-period echoes for the ranging of each observation spot; consequently, it can provide only few measurement results. These vibrations may cause large errors because conventional vibration compensation methods are ineffective when applied to fast disturbances with limited measurement results. To solve this problem, we analyze the influence of vibrations on FMCW ladar ranging and propose a vibration compensation method based on an instantaneous ranging model for one-period triangular FMCW ladar signals. We first use a synchrosqueezing wavelet transform to extract time-frequency curves of the up- and down-dechirp signals and then build an instantaneous ranging model that can characterize local vibration errors. Based on the instantaneous ranges, we remove the disturbance vibration errors by taking the mean values of the instantaneous ranges and obtain the target range by using the triangular relations of the up and down observations. Experiments based on synthetic and real data verify the effectiveness of the proposed method and its superiority over the three-point method and Doppler shift method in compensating for vibrations with different frequencies and noise levels.

Extended GLRT Detection of Moving Targets for Multichannel SAR Based on Generalized Steering Vector.

A generalized likelihood ratio test (GLRT) with the constant false alarm rate (CFAR) property was recently developed for adaptive detection of moving targets in focusing synthetic aperture radar (SAR) images. However, in the multichannel SAR-ground moving-target indication (SAR-GMTI) system, image defocus is inevitable, which will remarkably degrade the performance of the GLRT detector, especially for the lower radar cross-section (RCS) and slower radial velocity moving targets. To address this issue, based on the generalized steering vector (GSV), an extended GLRT detector is proposed and its performance is evaluated by the optimum likelihood ratio test (LRT) in the Neyman-Pearson (NP) criterion. The joint data vector formulated by the current cell and its adjacent cells is used to obtain the GSV, and then the extended GLRT is derived, which coherently integrates signal and accomplishes moving-target detection and parameter estimation. Theoretical analysis and simulated SAR data demonstrate the effectiveness and robustness of the proposed detector in the defocusing SAR images.

A Coherence Improvement Method Based on Sub-Aperture InSAR for Human Activity Detection.

Human activity detection plays an important role in social security monitoring. Since human activity is very weak, it is necessary to employ the repeat-pass Interferometric Synthetic Aperture Radar (InSAR) technique to detect the potential activity between two data acquisitions; a high level of coherence is required for detection. With the object of detecting human activity of interest, this paper presents a coherence improvement approach based on sub-aperture InSAR for human activity detection. Different sub-apertures contain different scattering information of the target, as they represent the backscatter of the target from a different range of angles. Integrating corresponding sub-aperture interferometric results can improve the coherence between two complex images compared to the entire synthetic aperture, as well as removing a little disturbance in some circumstances. To validate the method presented in this paper, the actual airborne Ka-band frequency modulated continuous wave (FMCW) InSAR data acquired by the Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS) are utilized. The experimental results demonstrate that the proposed method can effectively improve the coherence between two complex SAR images and can validly detect human activity of interest.

Coherent Markov Random Field-Based Unreliable DSM Areas Segmentation and Hierarchical Adaptive Surface Fitting for InSAR DEM Reconstruction.

A digital elevation model (DEM) can be obtained by removing ground objects, such as buildings, in a digital surface model (DSM) generated by the interferometric synthetic aperture radar (InSAR) system. However, the imaging mechanism will cause unreliable DSM areas such as layover and shadow in the building areas, which seriously affect the elevation accuracy of the DEM generated from the DSM. Driven by above problem, this paper proposed a novel DEM reconstruction method. Coherent Markov random field (CMRF) was first used to segment unreliable DSM areas. With the help of coherence coefficients and residue information provided by the InSAR system, CMRF has shown better segmentation results than traditional traditional Markov random field (MRF) which only use fixed parameters to determine the neighborhood energy. Based on segmentation results, the hierarchical adaptive surface fitting (with gradually changing the grid size and adaptive threshold) was set up to locate the non-ground points. The adaptive surface fitting was superior to the surface fitting-based method with fixed grid size and threshold of height differences. Finally, interpolation based on an inverse distance weighted (IDW) algorithm combining coherence coefficient was performed to reconstruct a DEM. The airborne InSAR data from the Institute of Electronics, Chinese Academy of Sciences has been researched, and the experimental results show that our method can filter out buildings and identify natural terrain effectively while retaining most of the terrain features.

Analysis and compensation of telescopes' gaps effect on aperture synthesis in a multi-channel synthetic aperture ladar system.

The azimuth multi-channel synthetic aperture ladar (SAL), which arranges multiple telescopes along the flight direction of the platform, transmits signals through a single telescope and receives echoes by multiple telescopes simultaneously to obtain data. The aperture synthesis technology, which has the ability to achieve high resolution through multiple small telescopes, is applied to the multi-channel SAL system to realize the reconstruction of the complete azimuth Doppler spectrum in a short observation time. However, there are gaps inevitably between telescopes, which degrade the results of aperture synthesis. In this work, the effect of gaps on the instantaneous Doppler spectrum of each channel and the influence on the result of the azimuth impulse compression after aperture synthesis are analyzed. In addition, an estimation method of gaps based on the phase errors between channels is proposed to reduce the influence. The estimation accuracy of the proposed method is analyzed, and the effectiveness of the method is verified with simulations. The estimated gaps are used to compensate for the phase discontinuity of the azimuth signal after aperture synthesis caused by gaps. The method improves the result of aperture synthesis and reduces the side-lobe of the azimuth impulse compression after aperture synthesis.

Overview of the LAMOST survey in the first decade.

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), also known as the Guoshoujing Telescope, is a major national scientific facility for astronomical research located in Xinglong, China. Beginning with a pilot survey in 2011, LAMOST has been surveying the night sky for more than 10 years. The LAMOST survey covers various objects in the Universe, from normal stars to peculiar ones, from the Milky Way to other galaxies, and from stellar black holes and their companions to quasars that ignite ancient galaxies. Until the latest data release 8, the LAMOST survey has released spectra for more than 10 million stars, ∼220,000 galaxies, and ∼71,000 quasars. With this largest celestial spectra database ever constructed, LAMOST has helped astronomers to deepen their understanding of the Universe, especially for our Milky Way galaxy and the millions of stars within it. In this article, we briefly review the characteristics, observations, and scientific achievements of LAMOST. In particular, we show how astrophysical knowledge about the Milky Way has been improved by LAMOST data.