Industrial IoT (IIoT) sensing nodes for bearing monitoring often operate in high-noise environments, where acoustic and mechanical interference masks weak fault signatures and undermines diagnostic reliability. To address this challenge, we propose a lightweight multi-modal fusion framework for robust fault diagnosis under extreme noise. Our method first applies multi-resolution decomposition with selective reconstruction and adaptive enhancement to preserve fault-related components while suppressing interference. The enhanced signals are transformed from 1D time series into two-dimensional representations to jointly capture temporal dynamics and spectral characteristics. We then design a tri-branch multi-head attention architecture that integrates a multiscale recurrence plot network, a Gramian angular field network, and a lightweight residual network. Learnable attention weights enable adaptive fusion of complementary cross-modal features with low computational overhead. Extensive experiments on the CWRU benchmark show superior robustness from 0 dB to -6 dB SNR, with a mean accuracy above 99.6% and consistent gains over eight state-of-the-art methods. Additional tasks on single-domain diagnosis, cross-condition fault type recognition, and fault degree discrimination (T1–T3) confirm strong generalization and multi-scale adaptability, with average improvements of 2–4% over the second-best baseline and stable variance under noise. The compact architecture and high noise immunity indicate practical suitability for IIoT sensing nodes and edge deployment in complex industrial scenarios.

Consensus learning has been widely adopted in clustering tasks due to its robustness to noise and outliers, as well as its ability to aggregate diverse base results from multiple models. However, existing methods are often limited by feature alignment issues arising from heterogeneous feature dimensionalities and label permutation inconsistencies across models. To address these limitations, this paper introduces a novel Consensus Fuzzy Representation Learning (CFRL) framework. The CFRL framework initially employs various fuzzy clustering methods to generate diverse membership matrices, which are then transformed into affinity matrices to serve as base fuzzy representations. This transformation strategy not only effectively resolves feature alignment issues but also provides a unified processing mechanism for both single-view and multi-view data scenarios. To derive robust consensus features, the tensor Schatten$p$-norm encourages low-rank structure in the tensorized fuzzy representations, whereas an$l_{1}$-norm regularized error term captures and suppresses sparse noise. Moreover, a block diagonal regularizer is incorporated into the objective function, which guides the consensus feature matrix toward an optimal block diagonal structure. This structural constraint enhances cluster discriminability and enables reliable final cluster assignments. Comprehensive experimental evaluations validate that the proposed CFRL method achieves superior performance compared to state-of-the-art approaches.

Traffic flow prediction is fundamental to traffic information services, control, and guidance. The challenge to accurately model the traffic flow is to comprehensively capture dynamic, global spatial, and local temporal correlations. To address challenges in spatiotemporal dependencies, global similarity, and local dynamics, we propose a multilayer spatiotemporal correlation-aware graph attention network (MSTC-GAT) for traffic flow prediction. Our model contains a multilayer spatial structure-aware module [spatial graph attention network (S-GAT)] using a spatial GAT with hierarchical attention masks and a path-based node correlation matrix to effectively capture local and global spatial dependencies. The temporal structure-aware module [temporal graph attention networks (T-GATs)] constructs a short-term similarity matrix of nodes for the temporal GAT to capture local dynamic temporal dependencies. Finally, a spatiotemporal Transformer (ST-Transformer) fuses weighted spatiotemporal node embeddings to capture global dynamic dependencies for accurate prediction. We conduct extensive experiments on four public benchmark datasets compared with 10 state-of-the-art models. The experimental results demonstrate that the MSTC-GAT outperforms all comparisons for short- and long-term predictions.

This paper introduces the Chinese Tianmu-1 GNSS-R constellation of 22 small satellites launched in 2023–2024 and comprehensively evaluates the latest version of the in-orbit data. First, the mission design and instrument technology are described, which largely builds on the Fengyun-3/GNOS-II missions. Notable innovations include full-GNSS compatibility and dual-polarization antenna. Then, the spatiotemporal characteristics of the constellation are analyzed—specifically, coverage percentage and mean revisit time at different latitudes. Next, the accuracy of its science products including ocean surface winds and land soil moisture has been assessed, with two application cases demonstrating the mission’s utility for monitoring tropical cyclones and flooding. Finally, this paper for the first time evaluates Tianmu’s polarized observations including Horizontal (H), Vertical (V), Left-Hand Circularly-Polarized (LHCP) and Right-Hand Circularly-Polarized (RHCP). Analysis of the signal-to-noise ratio and reflectivity shows that the dual-polarimetric observations follow the trend of theoretical models and hold promise for advancing land remote sensing.

The GNOS-II global navigation satellite system reflectometry (GNSS-R) Level 1 products from FENGYUN-3E, which include delay-Doppler map (DDM) and normalized bistatic radar cross section (NBRCS), significantly affect the inversion accuracy of geophysical parameters such as sea wind and soil moisture. This study uses data collected from FY-3E GNOS-II GNSS-R and data from ECMWF ERA-5 sea surface wind speed, covering the period from July 2022 to June 2023. In addition, CYGNSSv3.1 Level 1 data are used as a reference to evaluate NBRCS, observation geometry, GNSS satellite types, equivalent isotropic radiated power (EIRP) of GNSS and peak signal-to-noise ratio (SNR). The results show a strong correlation between FENGYUN-3E and approximately 1.5 million colocated cyclone global navigation satellite system (CYGNSS) specular points, with an overall NBRCS correlation coefficient of 0.882. Compared to CYGNSS, the FY-3E/GNOS-II specular reflector point offers broader coverage and the capability to process reflected signals from GPS, BDS, and GALILEO systems. However, FY-3E operates at a higher orbital altitude, resulting in reduced range-corrected gain (RCG), lower peak SNR, and a more scattered distribution of NBRCS. FY-3E successfully achieves stable NBRCS measurements across multiple GNSS systems. However, slight bias in NBRCS values is observed between different GNSS systems due to variations in EIRP calibration methods. These findings provide critical information for the practical application and future calibration of FY-3E Level 1 data.

Fengyun-3 (FY-3) series are operational satellite missions that can provide global GNSS-R observations using multiple GNSS systems. This abstract highlights the advancements in GNSS-R product development from FY-3E, FY-3F, and FY-3G. Currently available to the public are operational Level 1 and Level 2 wind products with a 25-km resolution. Additionally, a raw intermediate frequency product is accessible for scientific research. Upcoming product developments include the release of Level 2 12.5-km wind, Level 2 land soil moisture, Level 2 sea ice thickness, and Level 3 wind. Their algorithms and scientific impact will be discussed.

Abstract The method of deploying microservices based on container technology is widely used in cloud environments. This method can realize the rapid deployment of microservices and improve the resource utilization of cloud datacenters. However, resource allocation and deployment of container‐based microservices are key issues. With the continuous growth of computing‐ and storage‐intensive services, it is necessary to consider the deployment of microservices of different business types. This study establishes a multi‐objective optimization problem model with the similarity between containers and servers, load balance of clusters, and reliability of microservice execution as the optimization objectives. An improved artificial fish swarm algorithm is proposed for the container deployment of computing‐ and storage‐intensive microservices. The comprehensive experimental results show that, compared with the existing deployment strategies, the matching degree between the container and server, cluster load balance value, service execution reliability, and other performance parameters are improved while shortening the running time of the algorithm. In addition, under the constraint of load balancing, the resource utilization of the computing and storage server clusters is improved.

Reflected global navigation satellite system (GNSS) signals from Earth surface can be received by receivers at low Earth orbit for the remote sensing of geophysical parameters. While the technique has been studied for around 30 years, most early spaceborne GNSS reflectometry missions only adapted to receive GPS signals and the studies of reflected Galileo (GAL) signals in space are limited. The Navigation Satellite System Occultation Sounder II (GNOS-II) payload onboard the FY-3E satellite is the first mission that can operationally receive reflected GPS, BeiDou (BDS), and GAL signals at the same time. This letter presents the GAL reflectometry measurements from GNOS-II together with their calibration and wind speed (WS) retrieval methods. Results show that while GAL has a different signal modulation, the observables can be used to retrieve WSs using the same geophysical model functions (GMFs) of GPS after a dedicated calibration. The retrieved WSs from GAL also have a comparable accuracy as those from GPS and BDS.

With low signal power, Global Navigation Satellite System (GNSS) reflections in space are vulnerable to radio frequency interference (RFI) across the globe which can contaminate observations of GNSS reflectometry (GNSS-R) and introduce bias in the retrieved geophysical parameters. This paper presents a comprehensive analysis of the RFI in the Fengyun-3E Navigation Satellite System Occultation Sounder II (FY-3E/GNOS-II) GNSS-R data over the ocean. It was found that major sources of interference are the reflections of regional GNSS and Satellite-Based Augmentation Systems (SBAS), and external L-band interference signals from the ground. Furthermore, interference can have different impacts on the observations through increasing the noise power, decreasing the signal-to-noise ratio (SNR) or biasing observables depending on the type of interference and retrieval method. Some geography-dependent biases in the retrieved wind speeds were found to be related to RFI. An RFI mitigation method is then presented to calibrate observables and reduce geographical wind speed bias for the operational retrieval system. The bias and root-mean-square error of retrieved wind speeds from a region that is affected by RFI were reduced from 1.26, 2.78 to 0.04, 1.59 m/s, respectively.

Global Navigation Satellite System Reflectometry (GNSS-R) is a burgeoning remote sensing observation technology that can retrieve global sea surface wind speeds using satellite signals reflected from the sea surface. The improvement of data quality and the accumulation of data volume of this technology provides data support for constructing interdisciplinary-based retrieval models. This article constructs a hybrid deep neural network model based on deep learning for wind speed retrieval, which can receive and perform feature mining on the entire delay waveform while simultaneously supporting multiple auxiliary features input and achieving joint fitting. Then a bias correction method based on cumulative distribution function (CDF) matching is introduced to mitigate bias, especially at high wind speeds. We verify the contribution of different attribute features in wind speed retrieval by designing a feature ablation analysis. The fluctuation variation of the retrieval accuracy in the time dimension and the retrieval results distribution in space are compared and analyzed. The root mean square error (RMSE) of retrieval results is 1.486m/s and can reach 1.399m/s under the 94.25% wind speed condition. After bias correction based on CDF matching, the retrieval accuracy at high wind speed is improved by 7.19%. Besides, this model also has good temporal stability and can reproduce large-scale wind fields while effectively mitigating retrieval bias on a global scale, showing great potential for operational applications.

GRSA (GNSS Remote Sensing ASIC) is a new generation space-borne and radiation-hardened GNSS remote sensing ASIC of NSSC (National Space Science Center, CAS). In comparison to the previous generation space-borne GNSS ASIC of NSSC named GOPA (GNSS Occultation Processing ASIC), GRSA adds new functionalities and possesses improved performance. It will be used in multiple space missions for POD (Precise Orbit Determination), GNSS-RO (Radio Occultation), and GNSS-R (Reflectometry). GRSA is now in program transformation phase in which program is being transferred into ASIC, after architecture design and VHDL (Very high speed integrated circuit Hardware Description Language) implementation. GRSA is capable of processing civil signals from all GNSS satellite constellations and integrates an on-chip processor to provide enough computing power so that complicated on-board applications can be carried out. It will take approximate one year to tape out.

Optimal load distribution and speed scaling in a heterogeneous data center that takes account of the tradeoff between the maintenance and operation costs and system performance are crucial issues of cloud computing. Due to the changing states of cloud centers and diversity of the task arrival rate, a static control model is infeasible for cloud computing. In this article, we aim to provide a novel multi-server control model with dynamic feedback to acquire dynamic states of the cloud system, and with queue waiting cost-awareness to optimize the queue wait time and load distribution in task assignment and server configuration management. Using the technology of speed scaling, each server in a data center is configured as an$M/M/1$queue system with variable service rate, and the service rate is a function of the length of the task queue. We formulate two optimization problems, the optimal load distribution problem and the optimal service rate controlling problem, and provide algorithms to solve these problems, facilitating load distributions and service rate adjustments. We also present numerical simulations to validate our model. The results show our model to be efficient in multi-server dynamic configurations and task assignments according to the feedback information for the tradeoff between the system cost and performance.

The Global Navigation Satellite System Reflectometry (GNSS-R) technique can measure ocean surface winds and other geophysical parameters from forward scattered GNSS (GPS, BeiDou, Galileo, etc.) signals. However, most early spaceborne missions only captured GPS signals while the study of spaceborne reflectometry using BeiDou signals (BDS-R) is limited. The GNOS-II payload onboard China’s FY-3E satellite has been operationally collecting a large number of BDS-R data since July 10, 2021. BDS is different from GPS in the orbit, signal frequency, chipping rate and Effective Isotropic Radiated Power (EIRP). Furthermore, BDS satellites have different generations and orbits. This paper, for the first time, comprehensively characterizes the spaceborne BDS-R observations over the ocean using the FY-3E GNOS-II data from different BDS satellite types including BDS-2 IGSO, BDS-2 MEO, BDS-3 IGSO and BDS-3 MEO. Their spatial coverage, spatial resolution, effective scattering area, incidence angle, range corrected gain, EIRP and signal-to-noise ratio have been analyzed and compared to those of GPS-R. Spaceborne BDS-R shows a lot of uniquenesses compared to GPS-R. The BDS-R observables are then calibrated separately for each type. An intercalibration is also applied to correct extra calibration errors. After the calibration, BDS-R observables and retrieved winds are consistent between each type and compared to those of GPS-R. Calibrated observables from FY-3E GNOS-II are also evaluated by comparing them to those measured by the Cyclone Global Navigation Satellite System (CYGNSS) mission and a theoretical model. The results of this paper can provide a reference for future BDS-R studies and spaceborne GNSS-R mission design.

The International Reference Ionosphere (IRI) is an ionospheric empirical model established by assimilation and fusion of different kinds of ionospheric observation data, which can provide ionospheric parameters such as NmF2, hmF2, TEC in the range of 50-2000 km given a specified position and time. Accuracy verification of the model can provide an important scientific reference for its accuracy improvement and a priori condition for its subsequent applications. In this work, the NmF2 observed by the Global Navigation Satellite System (GNSS) occultation sounder (GNOS) mounted on FY3C(FY3C/GNOS) during geomagnetic quiet and storm periods are compared with the corresponding predictions of IRI-2016 to evaluate the error characteristics of the IRI-2016 model. After the comparison of median values of NmF2 in 9°×18° grids, we get that IRI-2016 model overestimates NmF2 compared to those of FY3C/GNOS no matter in quiet period or storm period. The biases of NmF2 relative errors between IRI-2016 and FY3C/GNOS are 10.02% and 26.88% in quiet and storm period, respectively. The results indicate the precision consistency between IRI-2016 and FY3C/GNOS in quiet period and the accuracy decrease of IRI-2016 in storm period. We also find that the NmF2 prediction accuracy of IRI-2016 at daytime are better than that at nighttime in both quiet and storm period, which is probably due to the absence of strong daytime photochemical control in F2 layer at nighttime and the time-varying ionospheric plasma irregularities after midnight.

The GNOS (GNSS Occultation Sounder) is the China's second GNSS (Global Navigation Satellite System) radio occultation payload for atmospheric and ionospheric sounding onboard FY-3D (Fengyun-3D) satellite meteorological satellite, which was launched on November 15th2017. This paper presents the technical characters of flight module manufactured by National Space Science Center (NSSC), Chinese Academy of Sciences, and the on-orbit performance of the FY-3D GNOS instrument. Firstly, we show the main technical parameters, including constellations and frequencies, position and occultation antenna gain, channel number, clock stability and so on. The on-orbit test result of the carrier phase accuracy and the precise orbit determination is shown. Meanwhile, the ability of occultation events received per day and the preliminary reversion accuracy are introduced in this paper.

Global Navigation Satellite System Occultation Sounder II (GNOS II) is an integrated GNSS remote sensing instrument which combines POD (Precise Orbit Determination), GNSS Radio Occultation (GNSS-RO) and GNSS Reflectometry (GNSS-R). It will provide more and higher quality radio occultation data and new reflected GNSS signal Delay Doppler Mapping (DDM), compared with its predecessor GNOS which were used in FY3C and FY3D satellites. GNOS II will be used on-board FY3E satellite since 2020 to monitor the ionosphere, neutral atmosphere, sea wave and wind field of earth. This paper presents the latest status and progress of Fengyun-3E GNOS II mission. Main features and parameters of the GNOS II , especially the improvements during the development of the GNOS II Flight Model, are illustrated.

Global Navigation Satellite System-Reflectometry (GNSS-R) is a remote-sensing technique for Earth surface observation. Global Navigation Satellite System Occultation Sounder (GNOS) II is an instrument, developed by National Space Science Center (NSSC), which can perform both GNSS radio occultation (RO) and GNSS-R. The GNSS-R module of GNOS II is capable of generating real-time Delay-Doppler mapping (DDM) for measuring wind speed over sea. Besides this basic scientific function, GNOS II can also record raw IF data for further study on reflection signal's feature and improvement on instrument's algorithm. To process the raw data collected by GNOS II, an off-line data processing software called multifunctional GNSS-R processing software (MRPS) has been developed. MRPS is mainly designed for processing raw data recorded by GNOS II to generate DDM synchronized with real-time DDM, and it can also process raw data collected by general GNSS recorder. Before converting raw data into DDM samples, MRPS first evaluates the quality of recorded signal. Then conventional GNSS-R (cGNSS-R) technique is applied to generate DDM. And a re-tracking algorithm is realized to compensate for the misalignment between DDM samples. This software has been used to process simulation data and airborne data collected by GNOS II and will be used to process spaceborne data in the future.

GRSA (GNSS Remote Sensing ASIC) is designed to be a radiation hardened GNSS remote sensing ASIC. GRSA follows the design of the first generation space-borne GNSS ASIC of NSSC named GOPA (GNSS Occultation Processing ASIC), but adds some new features to improve functions and the data quality. GRSA is capable of processing signals from all satellite navigation systems. It could be used in space missions for POD (Precise Orbit Determination), GNSS-RO (Radio Occultation), and GNSS-R (Reflectometry). On-chip processors will be integrated so that the signal processing board will be much simpler in the future than the existing designed. GRSA is now in architectural design and VHDL implementation phase. It will take 2 to 3 years to design and tape out.

In the past three decades, GNSS-R/IR has emerged as a new and promising remote sensing technique. Its applications have extended from ocean surface to land scenario. However, to our knowledge, few works focus on the soil salinity detection by GNSS-R/IR. For the first time, this paper studies the feasibility of soil salinity detection by using the microwave scattering models. As the reflected signals or interferometric signals of the GNSS constellations are collected from the first Fresnel zone, Fresnel reflectivities at both linear and circular polarizations are used to simulate the coherent scattering of soil salinity. In order to consider the azimuth angle effects, i.e. to consider the scattering coming from the specular cone, the advance integral equation model is employed. Our scattering simulations at both linear and circular polarizations indicate that soil salinity is detectable at some angles. The polarizations and angles should be carefully considered to find the best combinations for detection.

GNSS-R (Global Navigation Satellite System-Reflectomery) has emerged as a new and promising remote sensing techniques. In the recent two years, several airborne experimental campaigns have been carried out to demonstrate the possibility of wetland monitoring by GNSS-R. However, to our knowledge, there are no theoretical models for this new application. As for GNSS-R, whose working mode is an essential bistatic radar, the received power is DDM (Delay Doppler Map). A wetland GNSS-reflections simulator is presented. This model is based on the integral bistatic radar equation by taking into consideration the wetland, system impulse responses and geometry observation system. The wetland parameters affect the DDM waveforms through the BRCS (bistatic radar cross sections), which is a function of soil (surface roughness, soil moisture, soil freeze/thaw state) and vegetation parameters (vegetation moisture, biomass and growth). The simulator contains the inundated wetlands including two kinds of Aspen, whose effects on the final GNSS reflected power (DDM) can be predicted by the simulator. The developed simulator can assist as mechanism tools for wetland monitoring with GNSS-R technique, and this model can provide theoretical backup for wetland mapping, data analysis and experiment design.

In the past three decades, GNSS-R (reflectometry) /IR (interferometric reflectometry) has emerged as a new and promising remote sensing technique. Many researchers have paid much attention and dedicated on its prosperity and development. As for land surface, its applications have extended from soil moisture to snow depth (snow water equivalence) and vegetation parameters retrievals. To our knowledge, we have reviewed the progress on GNSS-R/IR land surface scattering models and presented our recent research on this subject. The developments of our bistatic scattering models, DDM simulators and forward GNSS multipath simulators are presented. The developed land surface models are oriented towards bare or vegetation- covered soil moisture, vegetation biomass/growth. Also the new application of GNSSR/IR on soil freeze/thaw process detection is also included in our models.

The dual-system compatible Global Navigation Satellite System(GNSS) occultation sounder (GNOS) for Beidou Navigation Satellite System (BDS) and Global Positioning System(GPS) was launched into orbit with FY3C satellite on September 23, 2013, in which we can get an important ionospheric parameter: F2-layer peak electron density (NmF2), it can limit the maximum feasible frequency for ground signal propagation, as well as defining the minimum required frequency for transionospheric radio wave propagation, so it's a crucial parameter for charactering ionosphere and the space weather. In this presentation, we verify the precision of ionospheric BDS radio occultation (BDSRO) data obtained by FY3C/GNOS through NmF2 comparisons between BDSRO and ionosondes. The results show that the correlation coefficient of NmF2 data between BDSRO and ionosondes is 0.96, the bias is 10.21 % and the standard deviation (std) is 19.61 %. The NmF2 precision of BDSRO at daytime is higher than that of nighttime; When Beidou satellites are at Inclined Geosynchronous Satellite Orbit (IGSO), its precision is higher than that at Geosynchronous orbit (GEO) and Medium Earth Orbit (MEO).

Global Navigation Satellite System (GNSS) Radio Occultation measurements can remote sensing Earth's neutral atmosphere and ionosphere. Meanwhile, another GNSS remote sensing technique named GNSS Reflectometry (GNSS-R) has been developed rapidly, which can retrieve sea surface wind speed. The GNSS Occultation Sounder (GNOS) II instrument has been designed to integrate these two GNSS remote sensing techniques in one payload of the third batch FengYun-3 (FY-3) satellites. This paper presents the advancements in research of GNOS II and instrument performance. The qualified module of GNOS II has been manufactured by National Space Science Center (NSSC), Chinese Academy of Sciences. We show that the phase center variety is low enough for the new designed precise orbit determination (POD) antenna to increase the accuracy of precise orbit determination. A wide coverage atmosphere occultation antenna and a 65nm technics ASIC are used in the new generation GNOS instrument. As an important improvement, the GNOS II can generate Delay Doppler Maps (DDMs) of GNSS signals scattered from the ocean surface. The result of test shows that the GNOS II instrument has high performance in precision of code, carrier phase and real-time navigation.

The Global Navigation Satellite System (GNSS) radio occultation (RO) observation data is widely used for numerical weather prediction (NWP) and global climate monitoring (GCM). However, the residual higher-order ionospheric error (RIE) can still be significant. To further mitigate the RIEs, characterization and quantification of RIEs in bending angles have been performed by using end-to-end simulations. In this study, the seasonal characteristics of the RIEs in bending angles were analyzed by using larger ensembles of profiles from end-to-end simulations. The results indicated that the RIE is a major source of the bending angle in lower mesosphere and upper stratosphere (LMUS), and its bias has a clear negative tendency that in line with our previous studies. The preliminary analysis showed that, globally the average bias and standard deviation of RIEs changed slightly, while regionally they changed obviously. For the northern hemisphere middle latitude (NHM) region, the largest average bias and standard deviation of RIEs happened in summer, while the smallest ones happened in winter. This study helps to inform future RIE mitigation schemes for ensuring benchmark quality stratospheric RO data.

Global Navigation Satellite System-Reflectometry (GNSS-R) becomes a popular remote-sensing technique for its wide coverage and low cost. GNSS-R works as a bi-static radar receiving weak signals of GNSS satellites reflected from the surface of the Earth. In order to obtain high quality observations, the reflected signals need to be tracked by the open-loop. So the key to the GNSS-R instrument is the calculation of specular point. In this paper, a modified gradient descent algorithm is applied to predict the position of specular point. And an experiment is carried out to test the performance of the algorithm. It turns out that the algorithm has valid results and high real-time performance.

GNOS is a scientific instrument for monitoring the Earth's neutral atmosphere and ionosphere. It provides vertical profiles of atmospheric temperature, pressure and humidity, as well as ionospheric electron density. GNOS is one of the important payloads on Fengyun3-D low-earth orbit satellite launched at November 15th2017, and began to work on November 25th2017. GNOS on FY3-D improved a lot in both function and performance compared with GNOS on FY3-C satellite that had been launched in September 2013. This paper introduces the FY3-D GNOS's improvements compared with FY3-C GNOS, and describes the expected results of FY3-D GNOS. In-orbiting validation is ongoing, and the assessment of the FY3-D GNOS will be finished in the first half of next year. Preliminary results will be given in the conference.

This paper presents the latest development of NSSC's GNOS-2 instrument. GNOS-2 adds new GNSS-R features to the successful GNOS receiver, which provides POD and occultation observations, on FY3C and FY3D. GNSS-R data of GNOS-2 could be used to study the state of sea and land. First flight of GNOS-2 is expected to be on-board FY3E satellite. The software system of GNOS-2's engineering model is introduced in this paper. A real-time DDM module developed based on segment correlation and FFT, as well as a raw data sampling module, are designed to receive the reflected GPS/BD signal from a wide code and frequency range. Main features and parameters of the GNSS-R software are illustrated. Lab test results are shown.

The remote sensing technique using X band and K band microwave signals between two Low-Earth-Orbit(LEO-LEO) satellites can characterize atmosphere temperature, humidity and pressure from low troposphere up to mesosphere without auxiliary background information. This paper firstly introduces the principle of the technique and then our LEO-LEO occultation system is presented. To achieve demanded amplitude and phase measurement precision, the structure and features of the LEO-LEO receiver are introduced. The transmitter and receiver have been basically completed. The ground test will be done within a few months.

Since Global Navigation Satellite System (GNSS) signals were not designed for remote sensing, GNSS Reflection (GNSS-R) signals from the earth surface are so weak, especially for space borne GNSS-R receiver cases, which limits its application for earth surface remote sensing. To achieve stronger GNSS-R signals, this thesis analyzed the effect of GNSS Left-Hand Circularly Polarized (LHCP) antenna's central beam direction on the ocean reflected signals' SNR around Specular utilizing GREEPS simulator. It was found that the available maximum SNR and the corresponding incident angle was varied when the LHCP's central beam direction was different. The greatest maximum SNR was available when central beam direction's nadir off-pointing was 26° and the corresponding incident angle was 32° .The added SNR compared with the case with central beam direction's nadir off-pointing being 0° and the corresponding incident angle being 4° was more than 3 dB.

GOPA is a radiation hardened GNSS baseband ASIC produced on the 65 nm 7-layer metal process technology. GOPA is capable of processing signals from GPS and BDS. A lot of lab tests had been carried out after tape-out of GOPA. The experiment results showed that the performances of GOPA were in good agreement with the design goals, the TID, SEL and SEU of the ASIC fulfilled the design requirements. GOPA will be used in the following GNOS series. The first flight of GOPA on GNOS series will be in 2018.

In Global Navigation Satellite System Radio Occultation (GRO), the tropospheric temperature and humidity can only be retrieved separately from refractivity by co-using a priori humidity or temperature information. Fortunately, the LEO-LEO (Low Earth Orbit) microwave occultation (LMO) exploits both the refraction and absorption of signals to solve the temperature-humidity ambiguity, and so it can retrieve the pressure, temperature, and humidity profiles independently. Furthermore, using LMO, ozone profiles can be retrieved by the signals around ozone absorption lines, and the liquid water and ice cloud variables can also be retrieved as by-products. In this paper, the measurement principle and capabilities of LMO technique are provided as an overview based on available literature; and then a pre-study of LMO including orbit design, frequency channels selection, performance analysis, and transmitter and receiver design/development is presented. The encouraging performance prospects of LMO give us confidence that it is highly worthwhile to pursue a space-borne demonstration mission.

Global Navigation Satellite System (GNSS) Occultation Sounder (GNOS) instruments were designed for the FengYun-3 (FY-3) series of meteorological satellites for sounding the Earth's atmosphere and ionosphere by radio occultation. Meanwhile, another GNSS remote sensing technique named GNSS reflectometry (GNSS-R) has been developed rapidly as well. To integrate these two GNSS remote sensing techniques in one payload, to help save the satellite's space, power and mass, a new instrument named GNOS II has been designed for the FY-3E satellite. The FY-3E satellite is anticipated to monitor the ionosphere, neutral atmosphere, sea wave and wind field by using GNSS signals in the future. So far, these two functional modules have been validated by ground-based, airborne or space-based campaigns. The GNOS II configuration and main performances characteristics are presented in this paper. According to its demonstrated performance, one can draw the conclusion that GNOS II will provide more and higher quality radio occultation data and new reflected GNSS signal delay Doppler maps (DDMs) for sea wave and wind field detection.

In order to understand the space-borne GNSS Reflection (GNSS-R) performance, an end to end simulator named GREEPS (GNSS-R End-to-End Performance Simulator) was developed by National Space Science Center (NSSC), Chinese Academy of Sciences. The simulator consists of four functional modules: Mission analysis module, forward modeling module, observation system modeling module and inversion/retrieval and precision Analysis module. This paper introduces each module's structure and capabilities. The preliminary simulation results are shown, including average and maximum number of simultaneously reflected GNSS satellites for 24 hours, coverage ratio between the ± inclination of LEO for 24 hours, the sensitivity of Delay Doppler Map (DDM) to the wind field, and wind field and ocean altimetry retrieval precision analysis. GREEPS is a powerful and useful simulation software for space-borne GNSS-R mission and payload design, it will speed up the space-borne GNSS-R applications in China.

The GNOS instruments are GNSS radio occultation payloads for atmospheric and ionospheric sounding onboard FY-3 meteorological satellites. The first GNOS instrument has been in orbit since September 23, 2013 when the FY-3C satellite was launched. The next generation GNOS instrument is being developed for the 3rd batch of FY-3 series satellites. This paper presents the new instrument's characteristics in design and main performance in occultation tracking. We show that the phase center variety is low enough for the choke-ring antenna new designed to increase the accuracy of precise orbit determination. A wide coverage atmosphere occultation antenna and a 65nm technology ASIC are used in the new generation GNOS instrument. The new GNOS instrument will acquire higher quality occultation data due to its better performance.

With the development of global navigation satellite system (GNSS) remote sensing, radio occultation (RO) has become an important atmospheric observation technique that mainly be used for numerical weather prediction (NWP) and global climate monitoring (GCM). However, residual ionopheric error (RIE) can still be significant after an ionospheric error elimination by linear combination of dual-frequency RO bending angles. Lots of quantification and analysis of RO bending angle RIEs has been conducted by using quasi-realistic end-to-end simulations. In this study, the RIEs in RO observations have been investigated by comparative analysis of COSMIC RO measurements and ECMWF model data. The results illustrate that the RIE is a major source of the bending angle in lower mesosphere and upper stratosphere, and its bias has a clear negative tendency that in line with our empirical studies based on simulation RO data. This study helps to inform future RIE mitigation schemes for ensuring benchmark quality stratospheric RO data.

This paper presents the latest development of NSSC's integrated GNSS remote sensing instrument. This new instrument is flexible designed for a variety of GNSS science needs based on the successful GNOS receiver, but with more functional modules. The goal of this instrument is to be put onboard of future Chinese space-borne platforms to provide precise position and timing information for high-demand space missions and to monitor ionosphere, atmosphere and the earth's surface. A DDM module was developed based on FFT, as a part of the instrument, to receive the reflected signal from a wide code and frequency range. The stored data could be used to study the state of sea and land. An airborne experiment was carried out in order to verify the performance of the module. The retrieval results show consistency with the on-site observables.

GNOS (GNSS Occultation Sounder) is an instrument developed by National Space Science Center (NSSC), Chinese Academy of Sciences. It was first successfully launched in September 23, 2013, as a payload of FY3C. More than 700 occultation events were received every day. The modified GNOS will also be on-board the FY3D satellite scheduled to launch in 2016. It contains three major improvements including increasing occultation channel numbers, employing open loop tracking on GPS L2C and Compass B1I and improving the gain of the antenna. In order to confirm the performance of GNOS instrument, a mountain-based experiment was carried out in China's Hebei Province on Mt. Wuling (40.598°N, 117.478°E) from June 16thto June 18th, 2015. By analyzing the experimental data, the performance of open-loop tracking on GPS L2C and Compass B1I was well validated.

Global Navigation Satellite System Reflectometry (GNSS-R) was regarded as a promising way to observe atmospheric duct by utilizing low elevation angle ocean surface reflected signals. To invest the Delay maps' feature of low elevation angle reflected signals in the atmospheric duct, a shipborne GNSS-R campaign was conducted in July, 2015 by the scientific investigation ship called Shiyan 3 on the South China Sea. During the campaign, the atmospheric temperature, pressure, and relative humidity which were used to detect atmospheric duct were recorded by GPS radiosondes and meteorological recorder. The GNSS-R payload developed by National Space Science Center (NSSC) and fixed on the rail of Shiyan3 was used to generate Delay maps. Preliminary results showed that atmospheric duct, especially evaporation duct, existed almost all the time in the experimental ocean region. Ocean surface reflected signals with elevation angle less than 10° were received and formed delay maps successfully. Affected by the direct signal and specular reflected signal's strong interference, apparent code correlation peaks appeared on Delay maps' tail. The experimental values of correlation peaks and simulated code autocorrelation were synthetically used to fit the curve of direct signal and specular reflected signal's strong interference utilizing the least square method. After removing the interference, cleaner reflected signals without direct and specular reflection signals were obtained.

This paper presents the error characteristics of MSISE-90, and data analysis is performed using statistical comparison. In this experiment, the absolute error, root mean square error and standard deviation of temperature and pressure for each month, latitude and geometric height are calculated, and the curve of annual global error characteristics is obtained at the same time. The result shows that there are obvious monthly periodic variations of the temperature and pressure error data. The annual global error increases with height: the annual global error of temperature is more than 3% at the height of 70km, while the annual global error of pressure is more than 15% at the same height. This article get a detailed monthly and annual average error characteristics of MSISE-90 model, which lay the foundation for using MSISE-90 model as a priori background field in the accurate processing of remote sensing data.

GNOS is a dual-frequency GPS/Beidou receiver developed for GNSS radio occultation studies. It is developed and manufactured by National Space Science Center(NSSC) under a contract with the China Meteorological Administration(CMA) and is designed to provide vertical profiles of atmospheric temperature, pressure, humidity, as well as ionospheric electron density on a global scale. GNOS first flight mission is on-board the Chinese FY3C meteorological satellite, launched on Sep, 2013. It will also be on-board the follow-up FY3 satellites in the future. This paper focuses on the current GNOS design and characteristics for the FY3C mission. The instrument performance derived from analysis of measurement data in laboratory and mountain-based occultation validation experiments is presented. The comparison between Open Loop and Close Loop are shown. The refractivity profiles of GNOS obtained during the mountain-based experiment are also compared with those from radiosondes.