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Summary: Research on returned samples can provide ground truth for the study of the geological evolution history of the Moon. However, previous missions all collected samples from the near side of the Moon, which is significantly different from the far side of the Moon in terms of the thickness of the lunar crust, magma activity, and composition. Therefore, the samples from the far side of the Moon are of great significance for a comprehensive understanding of the history of the Moon. China’s Chang’e-6 (CE-6) probe has successfully landed on the lunar far side and will return samples in the coming days. With the precise location of the CE-6 landing site, a detailed analysis of the geological background is conducted in this research. The landing site of CE-6 is within the Apollo crater, which is inside the largest impact basin on the Moon, i.e., the South Pole-Aitken (SPA) basin. According to the numerical simulation of the formation process of the SPA basin, CE-6 landed at the edge of the SPA impact melting zone, which is presumably composed of impact melt of the lunar mantle. The Apollo crater subsequently excavated deep material again, which constitutes the basement of the CE-6 landing area. Later, erupted basalt covered these basement rocks, and they also constitute the main source of the CE-6 samples. Based on the dating method of crater size-frequency distribution, we find that the basalt is ∼2.50 Ga. The CE-6 samples also possibly contain basement rocks as excavated and ejected by craters, and they can provide crucial information for our understanding of lunar geological history along with the basalt samples.

Adaptive antenna arrays are widely used to protect Global Navigation Satellite System (GNSS) receivers from interference. However, conventional blind anti-jamming array processing methods can cause satellite signal attenuation, which reduces signal tracking precision and measurement accuracy. To alleviate this problem, this paper proposes the noncoherent channel combining method for GNSS signal tracking with an adaptive antenna array. A two-stage processing architecture is applied in the proposed method, where the first stage implements interference suppression, and the second stage achieves noncoherent channel combining. The proposed method has the advantage of blind characteristics that can be implemented without any other auxiliary information. It also reveals a unified processing architecture for anti-jamming array processing methods. Thus, a detailed comparison and analysis of the proposed method with several typical blind anti-jamming methods is performed. Simulation results demonstrate the effectiveness of the proposed method and its superiority over existing methods in terms of tracking performance.

In this study, we investigate event-triggered distributed fusion estimation for asynchronous Markov jump systems subject to correlated noises and fading measurements. The measurement noises are interrelated, and they are simultaneously coupled with the system noise. The sensor samples measurements uniformly, and the sampling rates of the sensors are different. First, the asynchronous system is synchronized at state update points; then, the local filter is obtained. Furthermore, a variance-based event-triggered strategy is introduced between the local estimator and the fusion center to decrease the energy consumption of network communication. Then, a distributed fusion estimation algorithm is proposed using a matrix-weighted fusion criterion. Finally, the effectiveness of the algorithm is verified using computer simulations.

Antenna arrays with adaptive filtering can protect the integrity and functionality of global navigation satellite system (GNSS) receivers against interference. However, a major problem with existing adaptive array processing algorithms is that they cause phase distortions and introduce bias errors into the carrier phase measurement, limiting high-precision applications. In this paper, a robust phase compensation technique is proposed to reduce the phase distortion. First, a phase bias detection method is developed to trigger the phase compensation technique. Then, the phase bias is estimated using a robust estimation method and compensated for in the GNSS receiver. The proposed technique operates in real time and causes no processing delay, while requiring only a minor modification to existing GNSS receivers. This technique is applied to the power inversion adaptive antenna, and can also be extended to a wide variety of adaptive antennas. The simulation experiments verify the applicability of the proposed technique and also confirm its superiority over existing techniques.

Key questions on solar wind–Moon interaction are reviewed. As the nearest celestial body to Earth, Moon’s space environment is distinctive to Earth’s mainly because of lack of a significant atmosphere/ionosphere and a global magnetic field. From a global respective, solar wind can bombard its surface, and the solar wind materials cumulated in the soil record the evolution of the Solar System. Many small-scale remanent magnetic fields are scattered over the lunar surface and, just as planetary magnetic fields protect planets, they are believed to divert the incident solar wind and shield the local lunar surface beneath, thus producing unique local surface environment that is critical to activities of human beings/facilities, thus providing unique landing sites to explore the origins of lunar swirls and remanent magnetic fields. Evidences have hinted that this local interaction, however, may be also distinct with the interacting scenario on planets, and the specific process has not been revealed because of lack of in situ observations in the near-Moon space or on the ground. The global and local solar wind interactions of the Moon represent 2 types of characteristic interaction of celestial bodies with stellar wind in deep space, i.e., the interactions of nonmagnetized bodies and of small-scale magnetized bodies, both of which may occur on asteroids and Mars. The deep-space celestial bodies, either difficult or impossible to reach for human beings or artificial satellites, are hard to measure, and the exploration of the Moon can reveal the mystery of stellar wind interaction on these bodies.

This paper presents a review of the scientific research progress of the lunar in-situ spectroscopy and radar, focusing on the important results obtained by the Chang'E-3 and Chang'E-4 missions. In terms of the spectral detection, we report the composition, the photometric characteristics, space weathering information and thermal radiation characteristics of the lunar surface. In terms of radar detection, the detection of geological subsurface structures of the Moon, the detection of possible cavities/lava-tubes, and the inversion of the dielectric properties of the lunar regolith are described. Finally, the future development trends of lunar in-situ spectroscopy and radar detection are discussed.

Understanding crust–atmosphere interactions on Venus is fundamentally important to interpretations of Venus’ surface spectroscopic data. Olivine, in basaltic crust, is oxidized under a heated CO2 atmosphere. However, the oxidation rates, product assemblages and spectral characteristics of olivine samples with different Fa# values remain largely unclear. Herein, we investigated the oxidation of olivine with different Fa# values (Fa09, Fa29 and Fa71) under CO2 atmosphere at 470 °C and 900 °C and characterized the oxidation products (both microscopically and macroscopically), conversion rates and VNIR spectra. The results showed that the oxidation of olivine produced magnesioferrite, magnetite, laihunite, hematite and maghemite at 470 °C and hematite, magnetite, magnesioferrite and amorphous SiO2 at 900 °C. Both high temperature and high Fa# values accelerated the oxidation rates. The production of oxide coatings on olivine grains (74 μm in size) was estimated to be completed within tens to hundreds of years at 470 °C in natural settings, with even shorter periods under higher temperatures. Thus, CO2 oxidation would quickly eliminate olivine spectral characteristics, and spectral parameters at 850 and 1020 nm, as well as other relevant spectral windows (considering shifts induced by the elevated temperature), could be used to trace olivine oxidation processes. This work presented a case study connecting microscopic features to spectral characteristics for Venus’ surface–atmosphere interactions. Further studies considering more realistic Venus’ surface–atmosphere conditions will be essential to better interpret the measured spectroscopic data and determine the origins of the high emissivity detected on elevated terrain on Venus.

Forest fires are important factors that influence and restrict the development of forest ecosystems. In this paper, forest-fire-risk prediction was studied based on random forest (RF) and backpropagation neural network (BPNN) algorithms. The Heihe area of Heilongjiang Province is one of the key forest areas and forest-fire-prone areas in China. Based on daily historical forest-fire data from 1995 to 2015, daily meteorological data, topographic data and basic geographic information data, the main forest-fire driving factors were first analyzed by using RF importance characteristic evaluation and logistic stepwise regression. Then, the prediction models were established by using the two machine learning methods. Furthermore, the goodness of fit of the models was tested using the receiver operating characteristic test method. Finally, the fire-risk grades were divided by applying the kriging method. The results showed that 11 driving factors were significantly correlated with forest-fire occurrence, and days after the last rain, daily average relative humidity, daily maximum temperature, daily average water vapor pressure, daily minimum relative humidity and distance to settlement had a high correlation with the risk of forest-fire occurrence. The prediction accuracy of the two algorithms in regard to fire points was higher than that for nonfire points. The overall prediction accuracy and goodness of fit of the RF and BPNN algorithms were similar. The two methods were both suitable for forest-fire occurrence prediction. The high-fire-risk zones were mainly concentrated in the northwestern and central parts of the Heihe area.

Hematite, a ferric mineral with diagnostic features in the visible and infrared spectral range, has recently been discovered in the polar regions of the Moon by the Chandrayaan-1 Moon Mineralogy Mapper (M3). The oxygen involving the oxidization process producing lunar hematite is supposed to originate from the Earth’s upper atmosphere, and hematite with different ages may have preserved information on the oxygen evolution of the Earth’s atmosphere in the past billions of years. The discovery of lunar hematite may provide insight into the understanding of the oxidation products on the Moon and other airless bodies. In this work, we analyze hematite abundance distribution in the lunar polar regions, showing that the content of hematite on the lunar surface increases with latitude, and is positively correlated with surface water abundance. We suggest that the latitude dependence of hematite is derived from the latitude dependence of water, which indicates that water may play an essential role in the formation of hematite. The correlation between hematite and the optical maturity parameter (OMAT) was analyzed and a significant positive correlation was observed, which suggests that the hematite in the polar regions is the result of gradual and persistent oxidation reactions. In addition, based on the analysis of oxygen particles in the Earth wind, it was found that O+ and O2+ are much more abundant, suggesting that low-energy O+ or O2+ ions escaping from the upper atmosphere of the Earth may play a crucial role in the formation of hematite in the lunar polar regions.

CAD/CAM (computer-aided design and computer-aided manufacturing) technology has been widely applied in clinical dentistry, but the material safety remains a concern. To investigate the impacts of CAD/CAM metallic materials on trace metals and biocompatibilities, selective laser melted (SLM) cobalt-chromium (Co-Cr) alloys and computer numeric controlled milled (CNC milled) commercially pure titanium (CP-Ti) were placed on the maxilla of beagle dogs for 6 months. The trace metals in the oral mucosa, blood, liver, kidney, and hair were then determined by inductively coupled plasma mass spectrometry (ICP-MS). The histopathologic changes and biocompatibilities of tissues were examined by hematoxylin and eosin (H&E) staining, terminal deoxynucleotidyl transferase (TdT)-mediated dUTP-digoxigenin nick end labeling (TUNEL) method, immunohistochemistry (IHC) assay, Western blot analysis, and liver and kidney function tests. Our results showed that trace metals released from these two CAD/CAM metallic materials accumulated transiently in the oral mucosa and whole blood. The trace metals released from SLM Co-Cr alloys could also transiently accumulate in the plasm and hair. In addition, these two CAD/CAM metallic materials both induced apoptosis and histopathologic changes in the oral mucosa, with SLM Co-Cr alloys inducing a higher level of apoptosis. In contrast, both materials did not exert autophagic effects on the oral mucosa or affect the trace metals, functions, or biocompatibilities of the liver and kidney. Therefore, this study suggests that CAD/CAM metallic materials should be selected carefully, especially in patients with metal- and apoptosis-related diseases, and CNC-milled CP-Ti can be recommended to patients on account of its better biocompatibility and safety.

A visible and near-infrared imaging spectrometer (VNIS) loaded by the Chang’e-4 rover is the primary method for detecting the mineral composition of the lunar surface in the landing region. However, different data processing methods yield inconsistent mineral modes in measured lunar soil and rocks. To better constrain the mineral modes of the soil and rocks measured by Chang’e-4 VNIS, a noritic-gabbroic rock with a mineral composition similar to that of the lunar highland rocks is measured by scanning electron microscopy (SEM), the spare flight model of Chang’e-4 VNIS and TerraSpec-4 of ASD. Backscattered electron and energy dispersive spectrometry show that olivine, pyroxene, and plagioclase modal mineral abundances are 12.9, 35.0, and 52.2%, respectively. The estimated results of the spectrum by the Hapke radiative transfer model are 7.5, 39.3, and 53.2% for olivine, pyroxene, and plagioclase, respectively, which is consistent with to those of SEM mapping within error. In contrast, the estimated results of the modified Gaussian model are 29 and 71% for olivine and pyroxene, respectively, indicating the absence of plagioclase. Based on our implemented Hapke model, we decode the data of the two rocks detected by the rover on the 3rd and 26th lunar days of mission operations. The obtained results suggest that both rocks are norite or gabbro with noticeable differences. The first rock, with more olivine and pyroxene, may have been excavated from the Finsen crater. The second rock, with more plagioclase, may have been ejected from the southwestern edge of the Von Kármán crater, indicating the initial lunar crust.

The Zhurong rover successfully landed in southern Utopia Planitia as part of the Tianwen-1 mission on 15 May 2021. One of the objectives of the Mars Surface Composition Detector (MarSCoDe) onboard the rover is to investigate mineral compositions on the Martian surface by measuring the near-infrared reflectance spectra. Before conducting spectral interpretation, in-flight data calibration is a crucial step due to the significant differences between the laboratory and the Martian environment. The work of the MarSCoDe spectrometer is based on an acousto-optic tunable filter (AOTF). The temperature variation of the AOTF could induce wavelength offset, making mineral identification uncertain. We first analyzed the viewing geometry of the spectral measurements of the calibration targets on the Mars rover according to its attitude to identify the anomalous data. The wavelength offsets were then determined by fitting the absorption positions of CO2 at ~1400 and ~2000 nm, representing the primary composition of the Martian atmosphere. The results showed 2–8 nm wavelength offsets, which correlated well with AOTF temperatures. The artifacts were removed in the wavelength-corrected reflectance spectra, which is critical to identify the material types on Mars, especially water-related minerals.

With the development of information technology, the Internet of Things (IoT) has the characteristics of strong permeability, large use of action, and good comprehensive benefits. It promotes the development of the IoT technology in the detection of structural engineering. It is conducive to the development of intelligent, refined, and networked structures. Crack is the most common threat to the safety of bridges. Historical data show that the safety accidents caused by cracks account for more than 90% of the total bridge disasters. After a long period of engineering practice and rigorous theoretical analysis, it was found that 0.3 mm is the maximum allowable for bridge cracks. If the width exceeds the limit, the integrity of the bridge will be destroyed, and even a collapse accident will occur. Therefore, it is very important to identify cracks in bridge structure effectively and provide effective information for structural disaster reduction projects in time. Based on the structure of the IoT and the structural characteristics of the bridge engineering, this paper analyzed the practical application value of the IoT technology in the crack identification of bridge structures and established a bridge structure health monitoring system based on the IoT technology. On this basis, this paper also studied a digital and intelligent bridge crack detection method to improve the efficiency of bridge safety diagnosis and reduced the risk factor. First, the collected bridge crack photographs were preprocessed, the bridge crack convolution neural network classification model was established, and the model was simulated and trained using MATLAB. The bridge crack classification was obtained. The simulation results showed that the overall accuracy rate was greater than 90%.

In-situ measurements of the spectral information on the lunar surface are of significance to study the geological evolution of the Moon. China’s Chang’E-4 (CE-4) Yutu-2 rover has conducted several in-situ spectral explorations on the Moon. The visible and near-infrared imaging spectrometer (VNIS) onboard the rover has acquired a series of in-situ spectra of the regolith at the landing site. In general, the mineralogical research of the lunar surface relies on the accuracy of the in-situ data. However, the spectral measurements of the Yutu-2 rover may be affected by shadows and stray illumination. In this study, we analyzed 106 CE-4 VNIS spectra acquired in the first 24 lunar days of the mission and noted that six of these spectra were affected by the shadows of the rover. Therefore, a method was established to correct the effects of the rover shadow on the spectral measurements. After shadow correction, the FeO content in the affected area is corrected to 14.46 wt.%, which was similar to the result calculated in the normal regolith. Furthermore, according to the visible images, certain areas of the explored sites were noted to be unusually bright. Considering the reflectance, geometric information, and shining patterns of the multi-layer insulation (MLI), we examined the influence of the specular reflection of the MLI on the bright spot regionsd, and found that the five sets of data were likely not affected by the specular reflection of the MLI. The results indicated that the complex illumination considerably influences the in situ spectral data. This study can provide a basis to analyze the VNIS scientific data and help enhance the accuracy of interpretation of the composition at CE-4 landing sites.

Visible and infrared imaging spectroscopy have greatly revolutionized our understanding of the diversity of minerals on Mars. Characterizing the mineral distribution on Mars is essential for understanding its geologic evolution and past habitability. The traditional handcrafted spectral index could be ambiguous as it may denote broad mineralogical classes, making this method unsuitable for definitive mineral investigation. In this work, the target detection technique is introduced for specific mineral mapping. We have developed a new subpixel mineral detection method by joining the Hapke model and spatially adaptive sparse representation method. Additionally, an iterative background dictionary purification strategy is proposed to obtain robust detection results. Laboratory hyperspectral image containing Mars Global Simulant and serpentine mixtures was used to evaluate and tailor the proposed method. Compared with the conventional target detection algorithms, including constrained energy minimization, matched filter, hierarchical constrained energy minimization, sparse representation for target detection, and spatially adaptive sparse representation method, the proposed algorithm has a significant improvement in accuracy about 30.14%, 29.67%, 29.41%, 9.13%, and 8.17%, respectively. Our algorithm can detect subpixel serpentine with an abundance as low as 2.5% in laboratory data. Then the proposed algorithm was applied to two well-studied Compact Reconnaissance Imaging Spectrometer for Mars images, which contain serpentine outcrops. Our results are not only consistent with the spatial distribution of Fe/Mg phyllosilicates derived by spectral indexes, but also denote what the specific mineral is. Experimental results show that the proposed algorithm enables the search for subpixel, low-abundance, and scientifically valuable mineral deposits.

The Chang’E-4 (CE-4) spacecraft landed successfully on the far side of the Moon on 3 January 2019, and the rover Yutu-2 has explored the lunar surface since then. The visible and near-infrared imaging spectrometer (VNIS) onboard the rover has acquired numerous spectra, providing unprecedented insight into the composition of the lunar surface. However, the noise in these spectral data and its effects on spectral interpretation are not yet assessed. Here we analyzed repeated measurements over the same area at the lunar surface to estimate the signal–noise ratio (SNR) of the VNIS spectra. Using the results, we assessed the effects of noise on the estimation of band centers, band depths, FeO content, optical maturity (OMAT), mineral abundances, and submicroscopic metallic iron (SMFe). The data observed at solar altitudes

This paper is concerned with the state estimation problem for a class of non-uniform sampling systems with missing measurements where the state is updated uniformly and the measurements are sampled randomly. A new state model is developed to depict the dynamics at the measurement sampling points within a state update period. A non-augmented state estimator dependent on the missing rate is presented by applying an innovation analysis approach. It can provide the state estimates at the state update points and at the measurement sampling points within a state update period. Compared with the augmented method, the proposed algorithm can reduce the computational burden with the increase of the number of measurement samples within a state update period. It can deal with the optimal estimation problem for single and multi-sensor systems in a unified way. To improve the reliability, a distributed suboptimal fusion estimator at the state update points is also given for multi-sensor systems by using the covariance intersection fusion algorithm. The simulation research verifies the effectiveness of the proposed algorithms.