全球定位系统

2023 Vol. 48, No. 5

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Review
Theory and Discussion
Technical Report and Application
GNSS environmental detection and remote sensing technology

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2023, 48(5)

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Review

Reflections on the national global emergency SAR system with BDS as the core-(Invited)

GUO Shuren, LI Gang, LAI Xin, SONG Zhen, LU Hongyang, LI Linze

2023, 48(5): 1-7. doi: 10.12265/j.gnss.2023200

[Abstract](464) [FullText HTML] (129) [PDF 2558KB](70)

Abstract:
Emergency SAR (Search and Rescue) is of great significance to human life and property, economic development, national interests and the responsibility of a major country. And it is an important part of promoting the modernization of the life security system and capability. With the global expansion of China’s strategic benefits, the demand of global emergency SAR is becoming increasingly urgent. This paper expounds on the emergency SAR system in China and analyzes the SAR technical ability with BeiDou Navigation Satellite System (BDS) as the core. The challenges faced by China’s global emergency SAR system are also studied in terms of user experience improvement, efficiency development, international standards. It is important to construct national global emergency SAR system with BDS emergency SAR service as the core. And it is necessary to eliminate pain points and blockages, realize information fusion and sharing, and comprehensively improve China’s global emergency search and rescue capability. Additionally, it is suggested to promote the BDS SAR service to fully enter the international standard system, provide new public service products for the world, and help build a community with a shared future for mankind.

Theory and Discussion

On the principle and applications of the joint adjustment method for GNSS/A positioning of the underwater geodetic control point-(Invited)

WANG Zhenjie, SUN Zhen, ZHAO Shuang, NIE Zhixi, ZHANG Shimei

2023, 48(5): 8-14. doi: 10.12265/j.gnss.2023059

[Abstract](297) [FullText HTML] (88) [PDF 2993KB](34)

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On the impact of the coordinate errors of the acoustic transducer on the positioning accuracy of the undersea geodetic control point, we proposed a joint adjustment method of the seafloor geodetic control point for GNSS/A underwater precise positioning, whose crux was treating the positions of both transducer and transponder as unknown parameters in the acoustic ranging equation. The paper further expounds the principle of the joint adjustment method, for the shortcomings in the proof of the superiority of the joint adjustment method and the lack of verification of deep-sea data, the strict superiority proof and the precision evaluation formula of the joint adjustment method are given in this paper. Using Songhua Lake data and South China Sea data for verification, the precision of seafloor geodetic control point positioning with the proposed method is improved by 2% to 26%. The application effect of the joint adjustment method in the lake area and the deep-sea area is shown.

Intermittent tracking algorithm and performance analysis of low earth orbit satellite navigation SNAP signals

LIU Jiyang, TANG Xiaomei, YUAN Muzi, WANG Feixue

2023, 48(5): 15-20. doi: 10.12265/j.gnss.2023126

[Abstract](346) [FullText HTML] (137) [PDF 2452KB](55)

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With the rapid development of satellite navigation systems, high-precision and trustworthy navigation based on low earth orbit (LEO) satellite has become a hot topic in current research. However, the safety and trustworthiness issues of LEO satellite navigation have always hindered its large-scale application. The authentication scheme based on spreading code and navigation data based authentication proposal (SNAP) has shown a good trend in solving the above problems. The focus of this paper is to solve the intermittent tracking algorithm and performance analysis of SNAP signals, and obtain the analytical expression of tracking error. The research results show that the error accumulation caused by intermittent tracking follows a Gaussian distribution, and its mean is proportional to the Doppler frequency shift rate, and the variance is equivalent to the loss of carrier-to-noise ratio. Compared with the carrier loop, the code loop is less affected by Doppler. The research results of this paper provide important theoretical reference for the design of receiver system parameters under intermittent tracking structure.

LSTM assisted in vehicle GNSS/INS integrated navigation algorithm and performance analysis

LIU Dongliang, CHENG Fang, SHEN Pengli, LI Xiaowan, HU Yuhang

2023, 48(5): 21-31. doi: 10.12265/j.gnss.2023111

[Abstract](358) [FullText HTML] (147) [PDF 5004KB](54)

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Aiming at the problem that the positioning accuracy of the vehicle mounted GNSS/INS integrated navigation system declines or even diverges when the GNSS signal is unlocked, a new algorithm based on long short memory (LSTM) neural network assisted integrated navigation is proposed to improve the positioning accuracy and achieve reliable, continuous and stable positioning. The experiment was conducted on mobile integration platform, and the results showed that when the GNSS signal lost lock for 30 seconds, the maximum position error of the LSTM assisted integrated navigation system in the east and north directions decreased by 77.45% and 17.39%, respectively, and the root mean square error (RMSE) decreased by 79.53% and 42.36%, respectively; When the GNSS signal loses lock for 100 seconds, the maximum position error values of LSTM assisted GNSS/INS in the east, north, and sky directions decreased by 60.07%, 98.30%, and 84.65%, respectively, while RMSE decreased by 61.96%, 97.98%, and 84.65%. LSTM assistance greatly improves the navigation performance of the onboard GNSS/INS integrated navigation system.

NLoS error suppression algorithm based on two-step Kalman filtering

JIA Shilei, WANG Qianxin

2023, 48(5): 32-37. doi: 10.12265/j.gnss.2023079

[Abstract](409) [FullText HTML] (168) [PDF 2592KB](50)

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In order to solve the problem of non-line-of-sight propagation error which affects the positioning accuracy in ultra wide band (UWB) positioning, a secondary elimination method of non line of sight (NLoS) error based on kalman filtering is proposed. This method makes use of the mutual independence between the NLoS error and the measurement error, separates the NLoS error from the total error with the help of Kalman filter, estimates it in real time, and uses the estimated value of the NLoS error as the basis for NLoS error identification and distance measurement correction. Time of arrival (TOA) ranging accuracy is improved by secondary estimation, discrimination and correction of TOA ranging value through Kalman filtering, thus accurate real-time positioning of UWB in indoor complex environment is realized. The simulation results show that this method can not only track and estimate NLoS errors, but also has strong sensitivity to the transition of line-of-sight (LoS)/NLoS environment. The location performance of NLoS error measurements after applying this method is close to the ideal state in LoS environment.

Performance analysis of GPS/Galileo/BDS three systems and all-frequency PPP-AR

DONG Haoshen, ZHANG Qiyuan

2023, 48(5): 38-45, 70. doi: 10.12265/j.gnss.2023161

[Abstract](303) [FullText HTML] (130) [PDF 3569KB](33)

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The accurate estimation of phase biases is an essential prerequisite for achieving precise point positioning ambiguity resolution (PPP-AR). However, the phase bias products provided by the current International GNSS Service (IGS) analysis centers (ACs) are limited in terms of frequency combinations, which restricts PPP-AR users to using observations from corresponding frequencies only. This results in the underutilization of multi-frequency GNSS observations. In order to realize flexible PPP-AR based on arbitrary GNSS frequency selection and observation combinations (referred to as all-frequency PPP-AR), we conducted an analysis using static observation data from over 100 globally distributed IGS stations for a week. We estimated the observable phase biases (OSBs) for all available frequencies and conducted static precise point positioning experiments using the open-source PRIDE PPP-AR software. The results indicate that the average standard deviations of pseudo-range and phase OSB products are 0.25 ns and 0.34 ns, respectively, satisfying the requirements for PPP ambiguity fixing. The average ambiguity fixing rates for Galileo and BDS-3 frequency combinations are 98.25% and 96.74%, and 90.31% and 91.64%, respectively. For BDS-2, the average ambiguity fixing rates are 81.27% and 86.02%. Compared to the reference frequencies, the positioning accuracy decreases by nearly 15% in all three directions for E1/E6 and G1/G5 combinations. The C2/C5 combination performs well in the east (E) and north (N) directions but exhibits a 22.8% decrease in accuracy in the up (U) direction. In the testing of the GPS, Galileo, and BeiDou Navigation Satellite System (BDS), the remaining frequency combinations, including C2/C7, C1/C5, C1/C6, C1/C7, E1/E7, and E1/E8, all exhibited stable positioning accuracy. The positioning accuracy of each frequency combination varied by 5% in the E, 5% in the N, and 15% in the U direction, with no significant deviation compared to the reference frequency. Therefore, full-frequency PPP-AR has achieved a considerable degree of reliability. Full-frequency PPP-AR takes full advantage of the multi-frequency GNSS observations, offering higher practical value compared to using observations from the base frequency alone. Furthermore, full-frequency PPP-AR allows users to select and combine GNSS frequencies according to their specific requirements, thereby better satisfying the needs of various applications.

Analysis and comparison of satellite clock error prediction based on various deep learning algorithms

LU Yuwan, ZHENG Liquan, HU Chao

2023, 48(5): 46-55, 91. doi: 10.12265/j.gnss.2023138

[Abstract](461) [FullText HTML] (127) [PDF 7326KB](37)

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Aiming at the problems of the low applicability of the satellite clock error prediction model and the insufficient combination of the type of the satellite-borne atomic clock and the modeling characteristics in the prediction model, four kinds of neural network models suitable for nonlinear processing are proposed to predict satellite clock error. Firstly, the clock error data is preprocessed. Then, the firefly algorithm models were established by using the back-propagation (FA-BPNN) model, the Elman cyclic (Elman) model, the radial basis function (RBF) model, and the convolutional neural network data of 1 d and 7 d based on the CNN-LSTM model GPS precise clock error data from the Wuhan University International GNSS service (IGS) data analysis center (WHU) are used for clock error prediction At last, the effect of the prediction is analyzed and compared from the point of view of different modeling data and different batches of satellites with the same type of atomic clock and different batches of satellites with different types of atomic clock. The results show that: 1) the modeling accuracy of 1 d clock error data is higher than that of 7 d clock error data, and the RBF model has the greatest influence on the prediction accuracy with the increase of clock error data, and the prediction accuracy changes from sub-nanosecond to tens of nanosecond. 2) the prediction accuracy of the four neural network models is related to the satellite operating time in orbit and the type of atomic clock on board. The prediction performance of the satellites with long operating time in orbit is not necessarily bad, and the prediction performance of different types of atomic clock on different batches of satellites may be the same. The cesium atomic clock type satellite has the best prediction accuracy among the four neural network models.

Accuracy analysis of GPS L2C signal quality assessment by different tracking methods

DAI Zhihui, RAO Yongnan, GUO Yao

2023, 48(5): 56-63. doi: 10.12265/j.gnss.2023097

[Abstract](273) [FullText HTML] (72) [PDF 3915KB](24)

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The quality of satellite signals affects user performance, and signal quality evaluation can be achieved by utilizing the tracking results of software receivers. The pseudo-code of GPS L2C signal is composed of CM code and CL code time division multiplexing. According to its signal characteristics, different tracking methods can be used for tracking. The influence of different tracking methods on the accuracy of signal evaluation is analyzed, and the signal consistency and signal correlation performance are analyzed. Through simulation signal analysis and measured data verification, the results show that the joint tracking has higher evaluation accuracy than the single component tracking, and the evaluation results of each index are better than the evaluation results of a single branch. The use of joint tracking will bring smaller ranging error.

Pseudorange positioning model considering DCB correction and kinematic performance evaluation.

YE Shaochun, TANG Weijing, XU Wenbing

2023, 48(5): 64-70. doi: 10.12265/j.gnss.2023154

[Abstract](283) [FullText HTML] (92) [PDF 8868KB](17)

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In order to evaluate the performance of maritime single point positioning (SPP) performance, taking into account the fact that the broadcast satellite clock correction corresponds to the ionosphere-free (IF) combination or single-frequency B3, a multi-system single-frequency and dual-frequency IF SPP model is derived. The IF and single-frequency SPP positioning accuracy of GPS, GPS/Galileo, GPS/BDS and GPS/Galileo/BDS were evaluated using a set of offshore multi-system GNSS data measured by the unmanned surface vehicle (USV). The results show that compared with the GPS-only system, the SPP positioning performance after the system combination is improved with the plane accuracy of the GPS/Galileo/BDS IF SPP being better than 0.5 m, and the vertical direction accuracy being better than 0.6 m. Compared with the single-frequency SPP, the IF SPP has an improved positioning accuracy of about 1.0 m and 1.3 m in the horizontal and vertical directions, and the IF SPP has better positioning performance.

Ionospheric disturbance monitoring and GNSS positioning performance analysis during geomagnetic storms

SANG Wengang, LOU Guangzhen, ZHANG Xingguo, TIAN Maorong, ZHANG Guowei

2023, 48(5): 71-78. doi: 10.12265/j.gnss.2023127

[Abstract](491) [FullText HTML] (118) [PDF 3747KB](66)

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To analyze the disturbance patterns in the ionosphere and the changes in GPS positioning performance during magnetic storms, based on the IGS (International GNSS Service) global observation data and the GIM (Global Ionospheric Map), we conducted an analysis of the abnormal variation of total electron content (TEC) in the Northern Hemisphere during the geomagnetic storm event on August 26, 2018, as well as the GPS positioning performance. The results show that the TEC anomalies in the Northern Hemisphere exhibit latitude differences, with faster responses in higher latitude regions and larger variations in lower latitude regions, reaching up to 12 TECU (total electron content unit). During the magnetic storm, significant cycle slips were observed in the higher latitude regions, with a maximum decrease of 61.84% compared to magnetically quiet days. The data integrity of all stations decreased during the storm, with higher latitude regions experiencing a faster and more severe decline, reaching 38.65%. The decrease in data integrity of all stations occurred during the recovery phase of the storm. The data quality is consistent with the pattern of TEC anomalies. Analyzing the results of GPS dual-frequency dynamic precise point positioning (PPP), it was found that the positioning errors at higher latitude stations during the magnetic storm significantly increased, with horizontal and vertical root mean square errors reaching approximately 0.7 m and 1.8 m, respectively.

Accuracy evaluation of ionospheric prediction based on BP neural network model

SONG Binghong

2023, 48(5): 79-82, 102. doi: 10.12265/j.gnss.2023099

[Abstract](153) [FullText HTML] (103) [PDF 2349KB](21)

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In view of the characteristics of the high noise, nonlinear and non-stationary dynamic sequence of the total electron content (TEC) time series, based on the BP neural network (BPNN) model, the TEC data of the global ionospheric map (GIM) products provided by the center for orbit determination in Europe (CODE) in the middle and low latitudes, middle latitudes and high latitudes and the corresponding time points, longitude and latitude, solar radio flux F_10.7 data, equatorial geomagnetic activity index D_st The global geomagnetic activity index K_p data were trained and ionospheric prediction was carried out. The results confirmed that the BPNN model based on BP neural network can better predict the low latitude, middle latitude and high latitude ionospheric TEC values, and the average relative accuracy reached 90.5%, 88.7% and 85.35% respectively, the adjustment residuals are 1.505 TECU, 1.595 TECU, and 1.885 TECU, with RMSE values of 1.94 TECU, 2.13 TECU, and 3.08 TECU, respectively.

Technical Report and Application

Machine learning-based global positioning performance evaluation method of satellite navigation system

WANG Di, WANG Maolei, YANG Yufei, LI Haihang, GE Tiao

2023, 48(5): 83-91. doi: 10.12265/j.gnss.2023086

[Abstract](324) [FullText HTML] (152) [PDF 2877KB](37)

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For observation data such as pseudorange phase and broadcast ephemeris of satellite navigation systems, this paper adopts technical means such as feature extraction and model regression to find the intrinsic characteristics of the data from two dimensions of data type and observation time, excavate the feature associations between massive station data, and use machine learning methods to evaluate the global positioning performance of satellite navigation systems. The evaluation method proposed in this article has been validated on actual station data. The average positioning accuracy of 12 station models in China and surrounding areas, 1−MAPE, is 92.36%, with the worst being PTGG stations and 1−MAPE being 89.26%. The average positioning accuracy of 120 station models worldwide, 1−MAPE, is 86.59%, the worst being SCOR stations and 1−MAPE being 81.46%, which is in good agreement with the measured values obtained under the traditional mathematical statistical framework, It is shown that the method for evaluating satellite navigation and positioning performance based on machine learning models is feasible and effective. Machine learning models have strong evaluation capabilities and high generalization in big data statistical analysis, breaking through the current global positioning performance evaluation approach that only uses traditional mathematical statistics.

BeiDou data quality analysis based on range CORS

FENG Jianghai, YU Guodong, WANG Chunyang, ZHANG Dai, FENG Jihua, AN Na

2023, 48(5): 92-102. doi: 10.12265/j.gnss.2023082

[Abstract](266) [FullText HTML] (94) [PDF 6491KB](25)

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Since International Global Navigation Satellite System Service (IGS) started Multi-GNSS Experiment (MGEX) in 2011, multi-GNSS compatibility and interoperability have become a research hotspot. International GNSS Monitoring and Assessment System (iGMAS) were initiated for the first time in order to monitor and evaluate the running status and performance indicators of GNSS. In view of this, starting from the users, this paper makes quantitative analysis on the data integrity rate, cycle ratio, pseudorange multipath, carrier to noise ratio (CNR), pseudorange measurement accuracy of continuously operating reference station (CORS) data, and discusses the method of monitoring and evaluation of the BeiDou data quality in the range area based on the range CORS, so as to provide a scientific and quantifiable satellite environmental accuracy index for high-precision weapon test.

Analysis of GNSS interference localization techniques

WU Tao, HU Yanxia, TIAN Tian, ZHANG Jianting

2023, 48(5): 103-111. doi: 10.12265/j.gnss.2023100

[Abstract](493) [FullText HTML] (141) [PDF 2326KB](103)

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When GNSS is subjected to radio frequency interference (RFI), the performance of GNSS is very easy to decline sharply or even fail to work. Reducing the system vulnerability is still a realistic demand and an important direction of development. In recent years, interference localization, as a direct elimination method of anti-interference, has been rapidly developed in means and performance, and has been increasingly paid attention to and widely used. For suppression interference sources, the principles and characteristics of interference localization techniques are summarized and analyzed in depth in this paper. The techniques are classified into three categories: propagation parameter measurement, azimuth direction finding and direct positioning. The advantages and disadvantages of these methods and their application scenarios are compared and summarized.

Progress and Enlightenment of US PNT Information Source Construction

CHEN Hanlong, GONG Liang, LI Rui, ZHENG Xiaoxue

2023, 48(5): 112-116, 135. doi: 10.12265/j.gnss.2023142

[Abstract](294) [FullText HTML] (101) [PDF 2355KB](55)

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The relevant policies and overall goals in the field of USA positioning, navigation and timing (PNT) are combed through. The construction progress, service capabilities and fusion applications of important PNT information sources, such as GPS modernization, GPS and LEO communication satellite fusion, e-Loran system construction and autonomous navigation projects, are analyzed and summarized in detail. It indicates that the United States has clarified the development context of PNT system, and the related construction has entered the substantive stage. At the same time, this paper puts forward specific suggestions for the future development, integration and construction of PNT information sources in China.

GNSS environmental detection and remote sensing technology

Ground-based GNSS is used for multi-parameter inversion of surface environment in frozen soil areas

LI Jingtao, ZHANG Shuangcheng, LIU Ning, CHEN Xiongchuan, WANG Jie, FENG Zhijie

2023, 48(5): 117-124. doi: 10.12265/j.gnss.2023162

[Abstract](226) [FullText HTML] (101) [PDF 5182KB](33)

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Seasonal frozen soil has the physical characteristics of periodic surface uplift/settlement, and traditional measurement methods can no longer meet the current high-precision and real-time monitoring needs. Ground-based GNSS is a low-cost, all-day, all-weather, and emerging ground-based remote sensing technology that can achieve continuous monitoring. In this paper, based on the observation data of SG27 station of the U.S. Continental plate boundary observation (PBO) GNSS netuork program from 2013 to 2021, the ground-based GNSS technology is used to interpret the snow in typical abnormal years in the Permafrost region of Barrow, Alaska, and the surface deformation, station deformation, soil moisture, and atmospheric water vapor changes in the last nine years of long time series snow free period. The retrieval accuracy of snow depth in abnormal years is verified through the PBO measured snow data, Verify that the inversion result is the deformation of the permafrost active layer through the deformation results of the measuring station, and conduct correlation analysis between water vapor and soil moisture. The results show that the absolute coefficient R² of retrieved snow depth and measured snow depth is 0.8155, the root mean square error (RMSE) is 0.0643, and the mean absolute error (MAE) is 0.0402; Through the trend chart of water vapor and soil moisture changes, it is found that there is a weak lag relationship between the two on the rainfall threshold, but only in the trend rather than the amplitude. It shows that ground-based GNSS has great application potential in long-term permafrost environmental monitoring..

CORS stations for integrated monitoring of surface environmental parameters

FENG Zhijie, ZHANG Shuangcheng, ZHOU Xin, CHEN Xiongchuan

2023, 48(5): 125-135. doi: 10.12265/j.gnss.2023150

[Abstract](346) [FullText HTML] (101) [PDF 3399KB](28)

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Continuously operating reference stations (CORS), as an emerging navigation and positioning continuously operating reference station system developed by combining Global Navigation Satellite System (GNSS) and network communication technology, has the advantages of fast, efficient, high-precision, networked and so on. It can not only measure the position and movement of the ground surface, but also monitor the changes of environmental parameters on the ground surface with the help of refractive and reflective features of GNSS signals. In this paper, we propose a multi-parameter integrated monitoring system of surface environment by using CORS station for “snow depth, soil moisture, atmospheric water vapor, and surface deformation”, which is used to expand the wide application of CORS station in ecological environment. Taking Qiqihar CORS station BFQE as an experimental case, firstly, the GNSS observation data (including SNR data), ephemeris data and meteorological data received by the CORS station during the experimental period are obtained and pre-processed; secondly, the non-linear least squares and Lomb-Scargle spectral analysis methods are applied to the re-sampled SNR data to decipher the shallow soil humidity and surface snow depth in the specific period. Then, the surface deformation sequence and atmospheric water vapor sequence of the station were obtained by the International GPS service for Geodynamics (IGS) using the relative positioning technique; finally, the correlation analysis was carried out by combining the results of the above surface environmental parameters to obtain the response relationship between the parameters. The experimental results show that the CORS station used for integrated monitoring of the surface environment can effectively monitor the temporal changes of multiple parameters, and the environmental parameters obtained from the inversion have a certain response relationship with each other. The atmospheric water vapor content affects the spatial and temporal distribution and intensity of rainfall, and the atmospheric water vapor inversion values are highly correlated with rainfall in trend. During the snowy period, the increase in atmospheric water vapor is accompanied by an increase in snow depth during snow accumulation periods. Rainfall formed by the increase of atmospheric water vapor is the main source of soil moisture, and the interpreted soil moisture always shows an increasing trend after heavy rainfall. The average correlation between soil moisture and measured data based on single stars is 0.75, and the correlation of the results of multi-satellite fusion interpretation reaches 0.89, and the root-mean-square error of soil moisture content is 0.87%. The surface deformation time series is stable in the north (N) and east (E) directions, and the deformation in the up (U) direction has some responsive fluctuations with atmospheric water vapor, snow depth and soil moisture.

Research on GNSS-R model and delay-Doppler characteristics of reflected signal from sea surface

WAN Linyu, YANG Pengju, WU Rui, CAO Xinliang, REN Xincheng

2023, 48(5): 136-142. doi: 10.12265/j.gnss.2023153

[Abstract](479) [FullText HTML] (112) [PDF 5700KB](53)

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The modeling of sea surface reflected signal of GNSS is of great significance for Global Navigation Satellite System-Reflectometry (GNSS-R) remote sensing applications. Aiming at the modeling problem of GNSS reflected signal on the sea surface, the Z-V model is adopted in this paper to study the characteristics of one-dimensional time delay correlation power and two-dimensional delay-Doppler correlation power of GNSS reflected signal. The variation of one-dimensional correlation power is analyzed under different wind speeds, and the influence of time-delay interval and Doppler interval on delay-Doppler map (DDM) is also discussed in detail. Numerical results show that the correlation power of GNSS reflected signal is sensitive to sea surface wind speed, and appropriate time delay and Doppler interval parameters should be selected in DDM waveform simulation. The GNSS-R model can simulate the correlation power of GNSS reflected signal under different sea conditions, which is able to provide theoretical model support for GNSS-R reflected signal simulation and marine remote sensing applications.