海洋大气环境中极易出现对流层波导这类异常折射条件，由此产生的异常电波传播现象会对无线电系统的正常运行和性能评估造成严重影响。因此，获取海上对流层波导的区域分布信息，并分析其对电波传输特性的影响，对于无线电设备利用或规避这些异常传播现象具有重要意义。

本文以抛物方程算法为基础，研究了实际海洋环境中粗糙海面边界条件及初始场的构造方法。重点关注北斗卫星导航系统(BDS)和全球定位系统(GPS)卫星信号，探讨了低仰角全球导航卫星系统(GNSS)海面散射信号分布特征，及其在对流层波导中的传播特性。结合气象研究与预报(WRF)模式，提出了利用多普勒天气雷达(DWR)实测回波数据和低仰角GNSS非相干海面散射信号接收功率反演区域非均匀对流层波导参数的方法。本文的主要研究内容及成果如下：

1. 建立了一种基于真实海洋环境参数海谱模型的粗糙海面边界条件修正模型。对于地基雷达信号和GNSS非相干海面散射信号，采用求解天线孔径场的传统方法对初始场进行构造。对于GNSS直达波与其相干海面散射信号形成的干涉波，则是在修正粗糙海面边界条件的基础上，严格遵循抛物方程推导过程中的相关设定，建立了对应的初始场模型。仿真结果表明，不同海域海况下的粗糙海面边界条件存在明显差异，特别是当入射角大于80º时，遮挡效应成为不可忽视的影响因素。此外，卫星仰角增大时，干涉波中右旋圆极化分量的振荡幅度减小，而左旋圆极化分量的幅值增大，且考虑遮挡效应时干涉波的振荡幅度进一步减小。

2. 利用WRF模式并结合P-J模型，对我国南海区域的蒸发波导高度时空变化进行了数值模拟，并通过与实测数据的对比分析验证了该方法的有效性。对于表面波导和抬升波导，则是在修正折射率剖面参数化模型的基础上，利用WRF模式对我国沿海地区及附近海域的对流层波导区域分布进行了数值模拟，并与由全球通信系统(GTS)高空气象站定时值观测资料计算得到的数据进行了对比分析。结果表明，利用WRF模式对表面波导和抬升波导的发生与剖面参数进行数值模拟的方法，同样具有一定的可行性。

3. 提出了一种利用DWR实测回波数据并结合WRF模式反演区域非均匀对流层波导参数的方法。由于所使用的多普勒天气雷达回波数据是该雷达的日常观测资料之一，再辅以波导参数的数值模拟结果，因此无需开展专门的数据采集试验，不失为反演波导参数的一种可行办法。以含基础层的表面波导为传输环境，并将波导参数的数值模拟结果作为其反演初值以提高算法效率。反演结果表明，在所选海域的大部分区域内，海杂波功率反演值和回波功率实测值在变化趋势上保持一致，两者之间的误差绝对值在大约90%的区域内小于5 dB，证明该方法具有一定的可靠性。

4. 利用一阶小斜率近似在小到中等风速时的近似展开方法，对低仰角GNSS信号的非相干双站海面散射系数进行了仿真计算。利用半确定性面元散射模型，对低仰角GNSS信号的确定性海面双站散射总场及其极化特征进行了分析。此外，还利用GNSS卫星星座和信号参数以及精密星历数据，对卫星发射天线输出功率、仰角和方位角信息进行了评估和计算。结果表明，当散射角较大时，散射场基本上为椭圆极化波，并且在卫星仰角较大的情况下以左旋圆极化波为主。

5. 以适用于GNSS地海面遥感的一般形式的双站雷达方程为基础，建立了低仰角GNSS非相干海面散射信号在对流层波导中的传输模型。以BDS卫星的B1I信号为例，通过对比分析不同对流层折射环境中传输特性的差异，表明该信号适用于反演无基础层表面波导。对于GNSS直达波与其相干海面散射信号形成的干涉波，则是在修正粗糙海面边界条件及初始场模型的基础上，建立了对应的传输模型。为了验证该模型的有效性，对不同对流层折射环境、卫星仰角以及海况下的干涉波信号传输特性进行了仿真计算。结果表明，当卫星仰角超过0.5°时，无论哪种类型的对流层波导都无法对B1I信号干涉波进行有效捕获。

6. 提出了一种利用低仰角GNSS非相干海面散射信号接收功率反演区域非均匀无基础层表面波导参数的方法。以BDS卫星的B1I信号为例，给出了一个基于单卫星单仰角信号的仿真算例，讨论了卫星仰角以及接收信号中噪声水平对反演结果的影响。结果表明，卫星仰角越低且信噪比越大时，反演精度也就越高。此外，还利用接收到的位于不同星座轨道(BDS和GPS)上的多卫星多仰角信号，对波导参数进行了反演。在与基于单卫星单仰角信号的反演结果进行对比分析后，表明利用多卫星多仰角信号确实可以提高反演精度。

In the marine atmospheric environment, it is highly common for the abnormal refraction conditions like tropospheric ducts to occur, and the resultant abnormal propagation phenomena of radio waves will seriously affect the regular operation and performance evaluation of radio devices. Therefore, obtaining the regional distribution information of tropospheric ducts and analyzing their impacts on the propagation characteristics of radio waves is of great significance for radio equipment to utilize or avoid these abnormal propagation phenomena.

Based on the parabolic equation (PE) theory, the construction methods of the initial PE reduced fields and the rough sea surface boundary conditions in the actual marine environment are studied in this paper. Focused on the signals from the Beidou Navigation Satellite System (BDS) and Global Positioning System (GPS) satellites, the characteristics of GNSS scattered signals from the sea surface at lower elevation angles and the propagation characteristics in tropospheric ducts are discussed. Combined with the Weather Research and Forecasting Model (WRF), the remote sensing and inversion methods for regionally inhomogeneous tropospheric duct parameters using the measurements of Doppler Weather Radar (DWR) echo data and the received powers of GNSS incoherent sea-scattered signals at lower elevation angles are proposed. The main research contents and results of this paper are as follows:

1. A modified model of the rough sea surface boundary conditions based on the sea wave spectrum model of the actual marine environment parameters is proposed. For the ground-based radar signals and GNSS incoherent sea-scattered signals, the traditional method to solve the antenna aperture fields is used to construct the initial PE reduced fields. As for the interference signals formed from the GNSS direct signals and coherent sea-scattered signals, the corresponding initial PE reduced fields are constructed strictly following the related settings in the PE derivation process under the modified rough sea surface boundary conditions. The simulation results show that the differences between the rough sea surface boundary conditions over various sea areas and under various sea states are obvious. Especially, the impacts of the shadowing effects at the incidence angles greater than 80º are unneglectable. As the elevation angle increases, the oscillation amplitudes of the right-handed circular polarization (RHCP) components of the interference signals decrease, while the amplitudes of the left-handed circular polarization (LHCP) components increase. The oscillation amplitudes of the interference signals further decrease with the consideration of the shadowing effects.

2. The numerical simulations of the spatiotemporal variations of the evaporation duct heights (EDH) over the South China Sea areas are conducted using the WRF model and the P-J model, and the validation of this method is verified through the comparisons with measured data. The regional distributions of tropospheric ducts over the coastal and nearby sea areas of China are numerically simulated using the WRF model and the parameterization models of the modified refractivity profiles of surface ducts and elevated ducts. This numerically simulated results are then compared with data calculated using the observations of Global Telecommunications System (GTS) upper-air meteorological stations. The results show that the method to numerically simulate the occurrence and profile parameters of surface ducts and elevated ducts using the WRF model is also feasible.

3. An inversion method of regionally inhomogeneous tropospheric duct parameters using the measurements of DWR echo data and the WRF model is proposed. Since the DWR echo data used here are the regular observations of the radar, and then supplemented with the numerical simulation results of duct parameters, there is no need to conduct the specialized data collection experiments, which makes the proposed method feasible for inverting duct parameters. The surface duct with a base layer is taken as the transmission environment, and the numerical simulation results of duct parameters as their initial inverted values to improve the algorithm efficiency. The inversion results show that the inverted values of sea clutter powers and the measured values of echo powers are consistent in the variation tendencies in most of the selected sea area. The absolute errors between them are less than 5 dB in about 90% of the area, which proves that the method is reliable to a certain extent.

4. Based on an approximate expansion method of the small slope approximation of the first order (SSA1) at low-to-moderate wind speeds, the simulations of the incoherent bistatic scattering coefficients of GNSS signals at lower elevation angles are done. Additionally, the total bistatic scattering fields from the deterministic sea surfaces of GNSS signals at lower elevation angles and their polarization characteristics are analyzed using the semi-deterministic facet scattering model (SDFSM). Furthermore, the GNSS satellite constellation parameters, satellite signal parameters, and precise ephemeris data are used to evaluate and calculate the output powers of the transmitting antennas, elevation angles and azimuth angles of GNSS satellites. The results show that the scattering fields are elliptically polarized waves essentially at the larger scattering angles, and dominated by the LHCP components at the larger elevation angles.

5. Based on the generalized bistatic radar equation suitable for the remote sensing of land-sea surface parameters using GNSS signals, the transmission model of low-elevation GNSS incoherent sea-scattered signals in tropospheric ducts is proposed. Taking the B1I signals of BDS satellites as examples, the differences between the propagation characteristics in various tropospheric refraction environments indicate that the signals are suitable for inverting the profile parameters of surface duct without a base layer. For the interference signals formed from the GNSS direct signals and coherent sea-scattered signals, the corresponding transmission model is established on the basic of the modified rough sea surface boundary conditions and initial PE reduced fields. The simulations of the propagation characteristics of interference signals in various tropospheric refraction environments, at various elevation angles and under various sea states are done to verify the validation of the proposed model. The results show that the B1I interference signals cannot be effectively tapped in tropospheric ducts at the elevation angle larger than 0.5°.

6. An inversion method of regionally inhomogeneous tropospheric duct parameters using the received powers of GNSS incoherent sea-scattered signals at lower elevation angles is proposed. Taking the B1I signals of a BDS satellite as an example, a simulation using the signals at a single elevation angle is done. The impacts of the elevation angle and the noise level in the received signals on the inversion results are discussed. The results show that the lower the elevation angle and the higher the signal-to-noise ratio (SNR), the greater the inversion accuracy. Moreover, the signals of multiple satellites in various satellite constellations and orbits (BDS and GPS) at multiple elevation angles are used to invert duct parameters. After the comparisons with the inversion results using the signals of a single satellite at a single elevation angle, it is shown that the signals of multiple satellites at multiple elevation angles are helpful to improve the inversion accuracy indeed.

[1] 蔺发军, 刘成国, 成思等. 海上大气波导的统计分析[J]. 电波科学学报, 2005, 20(1): 64-68.
[2] Paulus R A. VOCAR: an experiment in variability of coastal atmospheric refracitivty[C]. In Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, August 08-12, 1994.
[3] Katzin M, Bauchman R W, Binnian W. 3- and 9-centimeter propagation in low ocean ducts[J]. Proceeding of the IRE, 1947, 35(7): 891-905.
[4] Anderson K D. Radar measurements at 16.5 GHz in the oceanic evaporation duct[J]. IEEE Transactions on Antennas and Propagation, 1989, 37(1): 100-106.
[5] Anderson K D. 94-GHz propagation in the evaporation duct[J]. IEEE Transactions on Antennas and Propagation, 1990, 38(5): 746-753.
[6] Stapleton J K, Wiss V R, Marshall R E. Measured anomalous radar propagation and ocean backscatter in the Virginia coastal region[C]. In Proceedings of the 31st International Conference on Radar Meteorology, Seattle, WA, USA, August 05-12, 2003.
[7] Kulessa A S, Woods G S, Piper B, et al. Line-of-sight EM propagation experiment at 10.25 GHz in the tropical ocean evaporation duct[J]. IEE Proceedings-Microwaves, Antennas and Propagation, 1998, 145(1): 65-69.
[8] Siddle D R, Warrington E M, Gunashekar S D. Signal strenght variations at 2 GHz for three sea paths in the British Channel Islands: Observations and statistical analysis[J]. Radio Science, 2007, 42: RS4019.
[9] Gunashekar S D, Warrington E M, Siddle D R. Long-term statistics related to evaporation duct propagation of 2 GHz radio waves in the English Channel[J]. Radio Science, 2010, 45: RS6010.
[10] Brekhovskikh L M. Waves in Layered Media[M]. 2nd ed. San Diego, California: Academic, 1980.
[11] 孙方, 王红光, 康士峰等. 大气波导环境下的射线追踪算法[J]. 电波科学学报, 2008, 23(1): 179-183,194.
[12] Zhao X F, Yang P L. A simple two-dimensional ray-tracing visual tool in the complex tropospheric environment[J]. Atmosphere, 2017, 8: 35.
[13] Baumgartner G B, Hitney H V, Pappert R A. Duct propagation modeling for the Integrated Refractive Effects Prediction System (IREPS)[J]. IEE Proceedings F: Communications, Radar and Signal Processing, 1983, 130(7): 630-642.
[14] Levy M. Parabolic equation methods for electromagnetic wave propagation[M]. London: The Institution of Electrical Engineers, 2000.
[15] Hitney H V. Hybrid ray optics and parabolic equation methods for mdar propagation modeling[C]. In Proceedings of 92 International Conference on Radar, Brighton, UK, October 12-13, 1992.
[16] Leontovich M A, Fock V A. Solution of the problem of propagation of electromagnetic waves along the earth's surface by the method of parabolic equations[J]. Acad. Sci. USSR. J. Phys., 1946, 10: 13-24.
[17] Hardin R H, Tappert F D. Application of the split-step Fourier method to the numerical solution of nonlinear and variable coefficient wave equations[J]. SIAM Review, 1973, 15: 423-429.
[18] Dockery G D. Modeling electromagnetic wave propagation in the troposhere using the parabolic equation[J]. IEEE Transactions on Antennas and Propagation, 1988, 36(10): 1464-1470.
[19] 唐琳婧, 王昆. 基于双向有限差分抛物方程法的海洋环境电波传播研究[J]. 电波科学学报, 2020, 35(3): 404-413.
[20] Zaporozhets A A. Modelling of radiowave propagation in urban environment[C]. In Proceedings of the 10th International Conference on Antennas and Propagation, Edinburgh, UK, April 14-17, 1997.
[21] Isaakidis S A, Xenos T D. Parabolic equation solution of tropospheric wave propagation using FEM[J]. Progress In Electromagnetics Research, 2004, 49: 257-271.
[22] Arshad K, Katsriku F, Lasebae A. An investigation of wave propagation over irregular terrain and urban streets using finite elements[C]. In Proceedings of the 6th WSEAS International Conference on Telecommunications and Informatics, Dallas, Texas, USA, March 22-24, 2007.
[23] Kuttler J R, Dockery G D. Theoretical description of the parabolic approximation/Fourier split-step method of representing electromagnetic propagation in the troposphere[J]. Radio Science, 1991, 26(2): 381-393.
[24] Dockery G D, Kuttler J R. An improved impedance-boundary algorithm for Fourier split-step solutions of the parabolic wave equation[J]. IEEE Transactions on Antennas and Propagation, 1996, 44(12): 1592-1599.
[25] Donohue D J, Kuttler J R. Propagation modeling over terrain using the parabolic wave equation[J]. IEEE Transactions on Antennas and Propagation 2000, 48(2): 260-277.
[26] Kuttler J R, Janaswamy R. Improved Fourier transform methods for solving the parabolic wave equation[J]. Radio Science, 2002, 37(2): 1021.
[27] Ament W S. Toward a theory of reflection by a rough surface[J]. Proceedings of the IRE, 1953, 41(1): 142-146.
[28] Miller A R, Brown R M, Vegh E. New derivation for the rough-surface reflection coefficient and for the distribution of sea-wave elevations[J]. IEE Proceedings H: Microwaves, Optics and Antennas, 1984, 131(2): 114-116.
[29] Fabbro V, Bourlier C, Combes P F. Forward propagation modeling above Gaussian rough surfaces by the parabolic shadowing effect[J]. Progress In Electromagnetics Research, 2006, 58: 243-269.
[30] Freund D E, Woods N E, Ku H C, et al. The effects of shadowing on modelling forward radar propagation over a rough sea surface[J]. Waves Random Complex Media, 2008, 18(3): 387-408.
[31] Benhmammouch O, Caouren N, Khenchaf A. Influence of sea surface roughness on electromagnetic waves propagation in presence of evaporation duct[C]. In Proceedings of 2009 International Radar Conference "Surveillance for a Safer World" (RADAR 2009), Bordeaux, France, October 12-16, 2009.
[32] Ayasli S. SEKE: A computer model for low altitude radar propagation over irregular terrain[J]. IEEE Transactions on Antennas and Propagation, 1986, 34(8): 1013-1023.
[33] Janaswamy R. A curvilinear coordinate-based split-step parabolic equation method for propagation prediction over terrain[J]. IEEE Transactions on Antennas and Propagation, 1998, 46(7): 1089-1097.
[34] Beilis A, Tappert F D. Coupled mode analysis of multiple rough surface scattering[J]. The Journal of the Acoustical Society of America, 1979, 66(3): 811-826.
[35] Feit M D, Fleck J A. Light propagation in graded-index optical fibers[J]. Applied Optics, 1978, 17(24): 3990-3998.
[36] Thomson D J, Chapman N R. A wide‐angle split‐step algorithm for the parabolic equation[J]. The Journal of the Acoustical Society of America, 1983, 74(6): 1848-1854.
[37] Saad Y, Lee D. A new algorithm for solving the wide angle wave equation[R]. New Haven: Department of Computer Science, Yale University ,1986.
[38] Collins M D. A split‐step Padé solution for the parabolic equation method[J]. The Journal of the Acoustical Society of America, 1993, 93(4): 1736-1742.
[39] Holm P D. Wide-angle shift-map PE for a piecewise linear terrain—A finite-difference approach[J]. IEEE Transactions on Antennas and Propagation, 2007, 55(10): 2773-2789.
[40] 郭琪, 黎子豪, 朱琼琼等. 基于全局透射边界条件的宽角抛物方程电波预测模型[J]. 电波科学学报, 2019, 34(4): 473-478.
[41] Ozgun O. Recursive two-way parabolic equation approach for modeling terrain effects in tropospheric propagation[J]. IEEE Transactions on Antennas and Propagation, 2009, 57(9): 2706-2714.
[42] Collins M D, Evans R B. A two-way parabolic equation for acoustic backscattering in the ocean[J]. The Journal of the Acoustical Society of America, 1992, 91(3): 1357-1368.
[43] 曹熙, 冯菊, 余洪鑫等. 基于双向抛物方程模型的雷达低角跟踪误差分析[J]. 电波科学学报, 2022, 37(6): 1057-1064.
[44] Zaporozhets A A. Application of vector parabolic equation method to urban radiowave propagation problems[J]. IEE Proceedings-Microwaves, Antennas and Propagation, 1999, 146(4): 253-256.
[45] Zaporozhets A A, Levy M F. Bistatic RCS calculations with the vector parabolic equation method[J]. IEEE Transactions on Antennas and propagation, 1999, 47(11): 1688-1696.
[46] Apaydin G, Sevgi L. Two-way propagation modeling in waveguides with three-dimensional finite-element and split-step Fourier-based PE approaches[J]. IEEE Antennas and Wireless Propagation Letters, 2011, 10: 975-978.
[47] Permyakov V A, Mikhailov M S, Malevich E S. Analysis of propagation of electromagnetic waves in difficult conditions by the parabolic equation method[J]. IEEE Transactions on Antennas and Propagation, 2019, 67(4): 2167-2175.
[48] Lentini N E, Hackett E E. Global sensitivity of parabolic equation radar wave propagation simulation to sea state and atmospheric refractivity structure[J]. Radio Science, 2015, 50: 1027-1049.
[49] Wagner M, Gerstoft P, Rogers T. Estimating refractivity from propagation loss in turbulent media[J]. Radio Science, 2016, 51: 1-19.
[50] 王倩南, 赵振维, 朱庆林等. 基于机载ADS-B信号地空传播试验数据分析[J]. 电波科学学报, 2018, 33(1): 85-92.
[51] Ozgun O, Sahin V, Erguden M E, et al. PETOOL v2.0: Parabolic Equation Toolbox with evaporation duct models and real environment data[J]. Computer Physics Communications, 2020, 256: 107454.
[52] Yang K, Wu Z S, Guo X, et al. Estimation of co-channel interference between cities caused by ducting and turbulence[J]. Chinese Physics B, 2022, 31(2): 024102.
[53] Yang K, Guo X, Wu Z S, et al. Using multi-source real landform data to predict and analyze intercity remote interference of 5G communication with ducting and troposcatter effects[J]. Remote Sensing, 2022, 14: 4515.
[54] Han J, Wu J J, Zhang L J, et al. A classifying-inversion method of offshore atmospheric duct parameters using AIS data based on artificial intelligence[J]. Remote Sensing, 2022, 14: 3197.
[55] Wang Y Z, Zhou T, Xu T H, et al. A sliced parabolic equation method to characterize maritime radio propagation[J]. Sensors, 2023, 23(10): 4721.
[56] Guo X M, Li Q L, Zhao Q, et al. A comparative study of rough sea surface and evaporation duct models on radio wave propagation[J]. IEEE Transactions on Antennas and Propagation, 2023, 71(7): 6060-6071.
[57] Yang S B, Li X F, Wu C, et al. Application of the PJ and NPS evaporation duct models over the South China Sea (SCS) in winter[J]. PLoS ONE, 2017, 12(3): e0172284.
[58] Pham C C, Nguyen X A. Determination of radio wave propagation conditions in the atmosphere of Hanoi using the radiosonde data of balloons[J]. ICT Express, 2022, 8(4): 611-617.
[59] Geng D, Zhao Z L, Fan Z Q, et al. Estimation of refractive index structure constant profile at high altitude in Gobi area based on meteorological rocket sounding data[J]. Journal of Atmospheric and Environmental Optics, 2023, 18(2): 99-107.
[60] Kabanov V A. Radiorefractometer setup and calibration for atmospheric refractive index measurement[J]. Telecommunications and Radio Engineering, 2017, 76(8): 731-742.
[61] López R N, Río V S. High temporal resolution refractivity retrieval from radar phase measurements[J]. Remote Sensing, 2018, 10: 896.
[62] Hallen H, Philbrick C R. Raman lidar measurements for boundary layer gradients and atmospheric refraction of millimeter-wave signals[J]. Proceedings of SPIE, 2020, 11410: 1141006.
[63] Louf V, Pujol O, Sauvageot H. The seasonal and diurnal cycles of refractivity and anomalous propagation in the Sahelian area from microwave radiometric profiling[J]. Oceanic Technology, 2016, 33(10): 2095-2112.
[64] Bean B R, Dutton E J. Radio Meteorology[M]. New York: Dover Publication, 1968.
[65] Jeske H. State and limits of prediction methods of radar wave propagation conditions over sea[M]// Zancla A. Modern topics in microwave propagation and air-sea interaction. Dordrecht: Springer Netherlands, 1973: 130-148.
[66] Rotheram S. Radiowave range prediction over the sea in evaporation ducting conditions (Tech. Rep. 77/37)[R]. Great Baddow: Marconi Research Laboratory, 1977.
[67] Fairall C W, Davidson K L. Evaporation duct measurements in the mid-Atlantic (Rep. 61-78-005)[R]. Monterey: Naval Postgraduate School, 1978.
[68] Liu W T, Katsaros K B, Businger J A. Bulk parameterization of air-sea exchanges of heat and water vapor including molecular constraints on the interface[J]. Journal of the Atmospheric Sciences, 1979, 36(9): 1722-1735.
[69] Paulus R A. Practical application of an evaporation duct model[J]. Radio Science, 1985, 20(4): 887-896.
[70] Paulus R A. Specification for environmental measurements to assess radar sensors[R]. San Diego: Naval Ocean Systems Center, 1989.
[71] Cook J, Burk S. Potential refractivity as a similarity variable[J]. Boundary-Layer Meteorology 1992, 58: 151-159.
[72] Musson-Genon L, Gauthier S, Bruth E. A simple method to determine evaporation duct height in the sea surface boundary layer[J]. Radio Science, 1992, 27(5): 635-644.
[73] Babin S M, Young G S, Carton J A. A new model of the oceanic evaporation duct[J]. Journal of Applied Meteorology, 1997, 36(3): 193-204.
[74] Frederickson P A, Davidson K L, Goroch A K. Operational bulk evaporation duct model for MORIAH (Tech. Rep. NPS/MR-2000-002, ver. 1.2)[R]. Monterey: Naval Postgraduate School, 2000.
[75] 刘成国, 黄际英, 江长荫等. 用伪折射率和相似理论计算海上蒸发波导剖面[J]. 电子学报, 2001, 29(7): 970-972.
[76] Ivanov V K, Shalyapin V N, Levadnyi Y V. Determination of the evaporation duct height from standard meteorological data[J]. Atmospheric and Oceanic Physics, 2007, 43(1): 36-44.
[77] Zhang J P, Wu Z S, Zhu Q L, et al. A four-parameter M-profile model for the evaporation duct estimation from radar clutter[J]. Progress in Electromagnetics Research, 2011, 114: 353-363.
[78] 张利军, 李建儒, 王红光等. 改进的蒸发波导RSHMU模型及预测性能分析[J]. 电波科学学报, 2022, 37(2): 198-205.
[79] 王石, 高山红. 一种蒸发波导的集合诊断方法及其数值预报应用[J]. 电子学报, 2019, 47(5): 1049-1057.
[80] Brookner E, Cornely P-R, Lok Y F. AREPS and TEMPER - getting familiar with these powerful propagation software tools[C]. In Proceedings of 2007 IEEE Radar Conference, Waltham, MA, USA, April 17-20, 2007.
[81] Burk S D, Thompson W T. Mesoscale modeling of summertime refractive conditions in the southern california bight[J]. Journal of Applied Meteorology, 1997, 36(1): 22-31.
[82] Hodur R M. The Naval Research Laboratory's Coupled Ocean/Atmosphere Mesoscale Prediction System(COAMPS)[J]. Monthly Weather Review, 1996, 125(7): 1414-1430.
[83] Grell G A, Dudhia J, Stauffer D R. A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5)[R]. Boulder: Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, 1995.
[84] Wang W, Bruyère C, Duda M, et al. WRF-ARW Version 3 Modeling System User’s Guide[R]. Boulder: Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, 2015.
[85] Haack T, Wang C G, Garrett S, et al. Mesoscale modeling of boundary layer refractivity and atmospheric ducting[J]. Journal of Applied Meteorology and Climatology, 2010, 49(12): 2437-2457.
[86] 刘桂艳, 高山红, 王永明等. 台风外围下沉区大气波导成因的数值模拟[J]. 应用气象学报, 2012, 23(1): 77-88.
[87] Telišman-Prtenjak M, Horvat I, Tomažić I, et al. Impact of mesoscale meteorological processes on anomalous radar propagation conditions over the northern Adriatic area[J]. Journal of Geophysical Research: Atmospheres, 2015, 120(17): 8759-8782.
[88] Zhao Q Y, Haack T, Mclay J, et al. Ensemble prediction of atmospheric refractivity conditions for EM propagation[J]. Journal of Applied Meteorology and Climatology, 2016, 55(10): 2113-2130.
[89] Ulate M, Wang Q, Haack T, et al. Mean offshore refractive conditions during the CASPER East field campaign[J]. Journal of Applied Meteorology and Climatology, 2019, 58(4): 853-874.
[90] Liang Z C, Ding J L, Fei J F, et al. Maintenance and sudden change of a strong elevated ducting event associated with high pressure and marine low-level jet[J]. Journal of Meteorological Research, 2020, 34(6): 1287-1298.
[91] 胡昊, 丁菊丽, 张羽等. 一次伴随雷达异常地物回波的超视距探测成因分析与数值模拟研究[J]. 电波科学学报, 2022, 37(2): 189-197.
[92] Jin S G, Wang Q S, Dardanelli G. A review on multi-GNSS for earth observation and emerging applications[J]. Remote Sensing, 2022, 14: 3930.
[93] 中国卫星导航系统管理办公室. 北斗卫星导航系统发展报告 (4.0版)[R]. 2019年12月.
[94] 安豪, 严卫, 杜晓勇等. GNSS大气海洋遥感技术研究进展[J]. 全球定位系统, 2021, 46(6): 1-10.
[95] Wickert J, Dick G, Schmidt T, et al. GNSS remote sensing at GFZ: Overview and recent results[J]. ZfV: Zeitschrift für Geodäsie, Geoinformation und Landmanagement, 2020, 145(5): 266-278.
[96] Wickert J, Cardellach E, Martin-Neira M, et al. GEROS-ISS: GNSS REflectometry, Radio Occultation, and Scatterometry onboard the International Space Station[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9(10): 4552-4581.
[97] Camps A, Park H. Sensitivity of delay Doppler map in spaceborne GNSS-R to geophysical variables of the ocean[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022, 15: 8624-8631.
[98] Martin-Neira M. A Passive Reflectometry and Interferometry System(PARIS): Application to ocean altimetry[J]. ESA journal, 1993, 17(4): 331-355.
[99] Mashburn J, Axelrad P, Zuffada C, et al. Improved GNSS-R ocean surface altimetry with CYGNSS in the seas of Indonesia[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(9): 6071-6087.
[100] Asgarimehra M, Arnoldb C, Weigelb T, et al. GNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet[J]. Remote Sensing of Environment, 2022, 269: 112801.
[101] Munoz-Martin J F, Camps A. Sea surface salinity and wind speed retrievals using GNSS-R and L-band microwave radiometry data from FMPL-2 onboard the FSSCat mission[J]. Remote Sensing, 2021, 13: 3224.
[102] Beltramonte T, Braca P, Di-Bisceglie M, et al. Simulation-based feasibility analysis of ship detection using GNSS-R delay-Doppler maps[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 1385-1399.
[103] Edokossi K, Calabia A, Jin S G, et al. GNSS-reflectometry and remote sensing of soil moisture: A review of measurement techniques, methods, and applications[J]. Remote Sensing, 2020, 12: 614.
[104] Munoz-Martin J F, Perez A, Camps A, et al. Snow and ice thickness retrievals using GNSS-R: Preliminary results of the MOSAiC experiment[J]. Remote Sensing, 2020, 12: 4038.
[105] Foti G, Gommenginger C, Jales P, et al. Spaceborne GNSS reflectometry for ocean winds: First results from the UK TechDemoSat-1 mission[J]. Geophysical Research Letters, 2015, 42(13): 5435-5441.
[106] Carreno-Luengo H, Crespo J A, Akbar R, et al. The CYGNSS mission: On-going science team investigations[J]. Remote Sensing, 2021, 13: 1814.
[107] 航天东方红. 捕风一号双星发射，利用导航信号监测台风[J]. 国际太空, 2019, 6: 10-11.
[108] Yang G L, Bai W H, Wang J S, et al. FY3E GNOS II GNSS reflectometry: Mission review and first results[J]. Remote Sensing, 2022, 14: 988.
[109] Wu J M, Chen Y L, Gao F, et al. Sea surface height estimation by ground-based BDS GEO satellite reflectometry[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 5550-5559.
[110] Yan S H, Zhang A, Chen N C, et al. Using reflected signal power from the BeiDou geostationary satellites to estimate soil moisture[J]. Remote Sensing Letters, 2019, 10(1): 1-10.
[111] Lu W J, Ma G Y, Wan Q T. A review of voxel-based computerized ionospheric tomography with GNSS ground receivers[J]. Remote Sensing, 2022, 13: 3432.
[112] Razin M-R G, Voosoghi B. Modeling of precipitable water vapor from GPS observations using machine learning and tomography methods[J]. Advances in Space Research, 2022, 69(7): 2671-2681.
[113] Bevis M, Businger S, Chiswell S, et al. GPS meteorology: Mapping zenith wet delays onto precipitable water[J]. Journal of Applied Meteorology, 1994, 33(3): 379-386.
[114] Lanyi G E, Roth T. A comparison of mapped and measured total ionospheric electron content using global positioning system and beacon satellite observations[J]. Radio Science, 1988, 23(4): 483-492.
[115] Wei J, Shu Y M, Liu Y, et al. Retrieving accurate precipitable water vapor based on GNSS multi‐antenna PPP with an ocean‐based dynamic experiment[J]. Geophysical Research Letters, 2023, 50(6): e2023GL102982.
[116] Astudillo J M, Lau L, Tang Y T, et al. A novel approach for the determination of the height of the tropopause from ground-based GNSS obsevartions[J]. Remote Sensing, 2020, 12: 293.
[117] Yang H, He X F, Ferreira V, et al. Assessment of precipitable water vapor retrieved from precise point positioning with PPP-B2b service[J]. Earth Science Informatics, 2023, 16: 315-328.
[118] Kursinski E R, Hajj G A, Hardy K R, et al. Observing tropospheric water vapor by radio occultation using the Global Positioning System[J]. Geophysical Research Letters, 1995, 22(17): 2365-2368.
[119] Zuffada C, Hajj G A, Kursinski E R. A novel approach to atmospheric profiling with a mountain-based or airborne GPS receiver[J]. Journal of Geophysical Research-Atmospheres, 1999, 104(D20): 24,435-24,447.
[120] 胡雄, 张训械, 吴小成等. 山基GPS掩星观测实验及其反演原理[J]. 地球物理学报, 2006, 49(1): 22-27.
[121] Weiss J-P, Schreiner W S, Braun J J, et al. COSMIC-2 mission summary at three years in orbit[J]. Atmosphere, 2022, 13: 1409.
[122] Sun Y Q, Bai W H, Liu C L, et al. The FengYun-3C radio occultation sounder GNOS: A review of the mission and its early results and science applications[J]. Atmospheric Measurement Techniques, 2018, 11(10): 5797-5811.
[123] Wang D W, Tian Y S, Sun Y Q, et al. Preliminary in-orbit evaluation of Gnos on FY3D satellite[C]. In Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, July 22-27, 2018.
[124] Zhang P, Hu X Q, Lu Q F, et al. FY-3E: The first operational meteorological satellite mission in an early morning orbit[J]. Advances in Atmospheric Sciences, 2022, 39: 1-8.
[125] Cheng Y, Lin J, Shen X H, et al. Analysis of GNSS radio occultation data from satellite ZH-01[J]. Earth and Planetary Physics, 2018, 2(6): 499-504.
[126] Li J W, Wang H G, Wu Z S, et al. PSO algorithm of retrieving surface ducts by Doppler weather radar echoes[J]. Progress In Electromagnetics Research B, 2016, 65: 19-33.
[127] Wang B, Wu Z S, Zhao Z W, et al. Retrieving evaporation duct heights from radar sea clutter using particle swarm optimization (PSO) algorithm[J]. Progress In Electromagnetics Research M, 2009(9): 79-91.
[128] Wang B, Zhao Z W, Wu Z S, et al. Retrieving surface-based duct parameters from radar sea clutter using a particle swarm optimization approach[C]. In Proceedings of IET International Radar Conference, Guilin, China, April 20-22, 2009.
[129] Zhang J P, S.Wu Z, Hu R X, et al. Estimating low-altitude atmospheric refractivity structure from multi-frequency radar returns[C]. In Proceedings of the 9th International Symposium on Antennas, Propagation and EM Theory, Guangzhou, China, November 29-December 02, 2010.
[130] Zhang J P, Wu Z S, Zhang Y S, et al. Evaporation duct retrieval using changes in radar sea clutter power versus receiving height[J]. Progress In Electromagnetics Research, 2012, 126: 555-571.
[131] Wang H G, Wu Z S, Kang S F, et al. Monitoring the marine atmospheric refractivity profiles by ground-based GPS occultation[J]. IEEE Geoscience and Remote Sensing Letters, 2012, 10(4): 962-965.
[132] Wang H G, Wu Z S, Lin L K, et al. Retrieving evaporation duct heights from power of ground-based GPS occultation signal[J]. Progress in Electromagnetics Research M, 2013, 30: 183-194.
[133] Han J, Wu J J, Wang H G, et al. Weight loss function for the cooperative inversion of atmospheric duct parameters[J]. Atmosphere, 2022, 13: 338.
[134] Zhang J P, Wu Z S, Zhao Z W, et al. Propagation modeling of ocean-scattered low-elevation GPS signals for maritime tropospheric duct inversion[J]. Chinese Physics B, 2012, 21(10): 109202.
[135] Wang B, Wu Z S, Zhao Z W, et al. A passive technique to monitor evaporation duct height using coastal GNSS-R[J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(4): 587-591.
[136] Reilly J P, Dockery G D. Influence of evaporation ducts on radar sea return[J]. IEE Proceedings F: Radar Signal Processing, 1990, 137(2): 80-88.
[137] Pappert R A, Paulus R A, Tappert F D. Sea echo in tropospheric ducting environments[J]. Radio Science, 1992, 27(2): 189-209.
[138] Rogers L T, Hattan C P, Stapleton J K. Estimating evaporation duct heights from radar sea echo[J]. Radio Science, 2000, 35(4): 955-966.
[139] Tabrikian J, Krolik J L, Vasudevan S. Estimating tropospheric refractivity parameters from radar sea clutter[C]. In Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics (SPW-HOS '99), Caesarea, Israel, June 16-16, 1999.
[140] Krolik J L, Tabrikian J, Vasudevan S, et al. Using radar sea clutter to estimate fefractivity profiles associated with the capping inversion of the marine atmospheric boundary layer[C]. In Proceedings of IEEE 1999 International Geoscience and Remote Sensing Symposium (IGARSS'99), Hamburg, Germany, June 28-July 02, 1999.
[141] Barrios A. Estimation of surface-based duct parameters from surface clutter using a ray trace approach[J]. Radio Science, 2004, 39: RS6013.
[142] Karimian A, Yardim C, Hodgkiss W S, et al. Estimation of radio refractivity using a multiple angle clutter model[J]. Radio Science, 2012, 47: RS0M07.
[143] Karimian A, Yardim C, Gerstoft P, et al. Multiple grazing angle sea clutter modeling[J]. IEEE Transactions on Antennas and Propagation, 2012, 60(9): 4408-4417.
[144] Vasudevan S, Krolik J L. Refractivity estimation from radar clutter by sequential importance sampling with a Markov model for microwave propagation[C]. In Proceedings of 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing, Salt Lake City, UT, USA, May 07-11, 2001.
[145] Anderson R, Vasudevan S, Krolik J L, et al. Maximum a posteriori refractivity estimation from radar clutter using a markov model for microwave propagation[C]. In Proceedings of IEEE 2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001), Sydney, NSW, Australia, July 09-13, 2001.
[146] Kraut S, Anderson R H, Krolik J L. A generalized Karhunen-Loeve basis for efficient estimation of tropospheric refractivity using radar clutter[J]. IEEE Transactions on Signal Processing, 2004, 52(1): 48-60.
[147] Yardim C, Gerstoft P, Hodgkiss W S. Estimation of radio refractivity from Radar clutter using Bayesian Monte Carlo analysis[J]. IEEE Transactions on Antennas and Propagation, 2006, 54(4): 1318-1327.
[148] Vasudevan S. Recursive Bayesian refractivity estimation using radar sea clutter return[D]. Durham: Duke Univesity, 2002.
[149] Vaudevan S, Anderson R, Kralk J L. Map sequence estimation of microwave refractivity from radar clutter via a particle filtering implementation of the Viterbi algorithm[C]. In Proceedings of 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing, Orlando, FL, USA, May 13-17, 2002.
[150] Yardim C, Gerstoft P, Hodgkiss W S. Tracking refractivity from clutter using kalman and particle filters[J]. IEEE Transactions on Antennas and Propagation, 2008, 56(4): 1058-1070.
[151] Yardim C, Gerstoft P, Hodgkiss W S. Tracking atmospheric ducts using radar clutter: evaporation duct tracking using Kalman filters[C]. In Proceedings of 2007 IEEE Antennas and Propagation Society International Symposium, Honolulu, HI, USA, June 09-15, 2007.
[152] Douvenot R, Fabbro V, Gerstoft P, et al. A duct mapping method using least squares support vector machines[J]. Radio Sciene, 2008, 43: RS6005.
[153] Douvenot R, Fabbro V, Bourlier C, et al. Retrieve the evaporation duct height by least-squares support vector machine algorithm[J]. Journal of Applied Remote Sensing, 2009, 3(1): 033503.
[154] Guo X W, Wu J J, Zhang J P, et al. Deep learning for solving inversion problem of atmospheric refractivity estimation[J]. Sustainable Cities and Society, 2018, 43: 524-531.
[155] Gerstoft P, Rogers L T, Krolik J L, et al. Inversion for refractivity parameters from radar sea clutter[J]. Radio Science, 2003, 38(3): 8053.
[156] Gerstoft P, Rogers L T, Hodgkiss W S, et al. Refractivity estimation using multiple elevation angles[J]. IEEE Journal of Oceanic Engineering, 2003, 28(3): 513-525.
[157] Gerstoft P, Rogers L T, Hodgkiss W S, et al. Refractivity-from-clutter using global environmental parameters[C]. In Proceedings of IEEE 2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001), Sydney, NSW, Australia, July 09-13, 2001.
[158] Yardim C, Gerstoft P, Hodgkiss W S, et al. Refractivity from clutter (RFC) estimation using a hybrid genetic algorithm-Markov chain Monte Carlo method[C]. In Proceedings of 2005 IEEE Antennas and Propagation Society International Symposium, Washington, DC, USA, July 03-08, 2005.
[159] Yardim C, Gerstoft P, Hodgkiss W S. Statistical maritime radar duct estimation using a hybrid genetic algorithm-Markov chain Monte Carlo method[J]. Radio Science, 2007, 42: RS3014.
[160] Rogers L T, Hattan C P, Krolik J L. Using radar sea echo to estimate surface layer refractivity profiles[C]. In Proceedings of IEEE 1999 International Geoscience and Remote Sensing Symposium (IGARSS'99), Hamburg, Germany, June 28-July 02, 1999.
[161] Zhang J P, Wu Z S, Wang B. An adaptive objective function for evaporation duct estimations from radar sea echo[J]. Chinese Physics Letters, 2011, 28(3): 034301.
[162] Fountoulakis V, Earls C. Duct heights inferred from radar sea clutter using proper orthogonal bases[J]. Radio Science, 2016, 52(10): 1614-1626.
[163] Douvenot R, Fabbro V, Gerstoft P, et al. Real time refractivity from clutter using a best fit approach improved with physical information[J]. Radio Science, 2010, 45: RS1007.
[164] Karimian A, Yardim C, Gerstoft P, et al. Refractivity estimation from sea clutter: An invited review[J]. Radio Science, 2011, 46: RS6013.
[165] Zhao X F, Huang S X. Atmospheric duct estimation using radar sea clutter returns by the adjoint method with regularization technique[J]. Journal of Atmospheric and Oceanic Technology, 2014, 31(6): 1250-1262.
[166] Hitney H V. Modelling tropospheric ducting effects on satellite-to-ground paths[C]. In Proceedings of the Electromagnetic Wave Propagation Panel Symposium, Rotterdam, The Netherlands, October 04-07, 1993.
[167] Douchin N, Bolioli S, Christophe F, et al. Theoretical study of the evaporation duct effects on satellite-to-ship radio links near the horizon[J]. IEE Proceedings-Microwaves, Antennas and Propagation, 1994, 141(4): 272-278.
[168] Anderson K D. Tropospheric refractivity profiles inferred from low elevation angle measurements of Global Positioning System (GPS) signals[C]. In Proceedings of the Sensor and Propagation Panel Symposium, Bremerhaven, Germany, September 19-22, 1994.
[169] Anderson K D. Using the Global Positioning System to detect surface-based ducts[C]. In Proceedings of the Battlespace Atmospherics Conference, San Diego, CA, USA, December 02-04, 1997.
[170] Balvedi G C, Walter F. GPS signal propagation in tropospheric ducts[C]. In Proceedings of the XXIXth URSI General Assembly, Chicago, IL, USA, August 09-16, 2008.
[171] Balvedi G C, Walter F. Analysis of GPS signal propagation in tropospheric ducts using numerical methods[C]. In Proceedings of the 11th URSI Commission Open Symposium on Radio Wave Propagation and Remote Sensing, Rio De Janeiro, RJ, Brazil, October 30-November 02, 2007.
[172] Dong C, Wu Z S, Zhao Z W, et al. Impact of low marine atmospheric refractivity profiles on GPS signals' propagation[C]. In Proceedings of the 9th International Symposium on Antennas, Propagation and EM Theory (ISAPE 2010), Guangzhou, China, November 29-December 02, 2010.
[173] Li G C, Guo L X, Liang Y. Simulation modelling the GPS signal propagation in the tropospheric ducts[C]. In Proceedings of the 9th International Symposium on Antennas, Propagation and EM Theory (ISAPE 2010), Guangzhou, China, November 29-December 02, 2010.
[174] Zhang J P, Wu Z S, Wang B, et al. Modeling low elevation GPS signal propagation in maritime atmospheric ducts[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2012, 80: 12-20.
[175] Wu X, Wu Z S. Modeling of GPS signal propagation in tropospheric duct on spherical rough sea surface[C]. In Proceedings of the 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE), Hangzhou, China, December 03-06, 2018.
[176] Liao Q X, Sheng Z, Shi H Q, et al. Estimation of surface duct using ground-based GPS phase delay and propagation loss[J]. Remote Sensing, 2018, 10(5): 724.
[177] Elfouhaily T, Chapron B, Katsaros K, et al. A unified directional spectrum for long and short wind-driven waves[J]. Journal of Geophysical Research-Oceans, 1997, 102(C7): 15781-15796.
[178] Pierson W J, Moskowitz L. A proposed spectral form for fully developed wind seas based on the similarity theory of S. A. Kitaigorodskii[J]. Journal of Geophysical Research, 1964, 69(24): 5181-5190.
[179] Hasselmann D E, Dunckel M, Ewing J A. Directional wave spectra observed during JONSWAP 1973[J]. Journal of Physical Oceanography, 1980, 10(8): 1264-1280.
[180] Torsethaugen K, Haver S. Simplified double peak spectral model for ocean waves[C]. In Proceedings of the 14th International Offshore and Polar Engineering Conference, Toulon, France, May 23-28, 2004.
[181] Panahi R, Ghasemi A, Shafieefar M. Development of a bi-modal directional wave spectrum[J]. Ocean Engineering, 2015, 105: 104-111.
[182] Hwang P A. Doppler frequency shift in ocean wave measurements: Frequency downshift of a fixed spectral wave number component by advection of wave orbital velocity[J]. Journal of Geophysical Research-Oceans, 2006, 111: c06033.
[183] 文圣常, 余宙文. 海浪理论与计算原理[M]. 北京: 科学出版社, 1984.
[184] 袁永华. 海港水文规范[M]. 北京: 人民交通出版社, 2013.
[185] 吴庚坤, 姬光荣, 姬婷婷等. 基于文氏改进谱的二维粗糙海面模型及其电磁散射研究[J]. 物理学报, 2014, 63(13): 134203.
[186] Goda Y. A comparative review on the functional forms of directional wave spectrum[J]. Coastal Engineering Journal, 1994, 41(01): 1-20.
[187] Lygre A, Krogstad H. Maximum entropy estimation of the directional distribution in ocean wave spectra[J]. Journal of Physical Oceanography, 1986, 16(12): 2052-2060.
[188] Joung S J, Shelton J. 3 Dimensional ocean wave model using directional wave spectra for limited capacity computers[C]. In Proceedings of Ocean Technologies and Opportunities in the Pacific for the 90's, Honolulu, HI, USA, October 01-03, 1991.
[189] Toporkov J V, Brown G S. Numerical simulations of scattering from time-varying, randomly rough surfaces[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(4): 1616-1625.
[190] 吴涛. 不同海域多频段海杂波特性差异与主要影响因素分析[D]. 西安: 西安电子科技大学, 2019.
[191] Okino N, Kakazu Y, Morimoto M. Extended depth-buffer algorithms for hidden-surface visualization[J]. IEEE Computer Graphics and Applications, 1984, 4(5): 79-88.
[192] Bourlier C, Berginc G, Saillard J. One- and two-dimensional shadowing functions for any height and slope stationary uncorrelated surface in the monostatic and bistatic configurations[J]. IEEE Transactions on Antennas and Propagation, 2002, 50(3): 312-324.
[193] Meissner T, Wentz F J. The complex dielectric constant of pure and sea water from microwave satellite observations[J]. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(9): 1836-1849.
[194] Ishimaru A. Wave propagation and scattering in random media[M]. New York: Academic Press, 1978.
[195] Beard C I. Coherent and incoherent scattering of microwaves from the ocean[J]. IRE Transactions on Antennas and Propagation, 1961, 9(5): 470-483.
[196] Freund D E, Woods N E, Ku H C, et al. Forward Radar propagation over a rough sea surface: a numerical assessment of the Miller-brown approximation using a horizontally polarized 3-GHz line source[J]. IEEE Transactions on Antennas and Propagation, 2006, 54(4): 1292-1304.
[197] Hannah B M. Modelling and simulation of GPS multipath propagation[D]. Brisbane: Queensland University of Technology, 2001.
[198] Bucco D, Chisholm J M. Comparison of scattering models for predicting radar multipath effects over the sea[C]. In Proceedings of Modeling and Simulation Technologies Conference, New Orleans, LA, USA, August 11-13, 1997.
[199] Northam D Y. A stochastic simulation of low grazing angle, forward scatter, over-water multipath effects[R]. Washington: Naval Resaerch Lab, 1983.
[200] Voronovich A G, Zavorotny V U. Full-polarization modeling of monostatic and bistatic radar scattering from a rough sea surface[J]. IEEE Transactions on Antennas and Propagation, 2014, 62(3): 1362-1371.
[201] 刘成国. 蒸发波导环境特性和传播特性及其应用研究[D]. 西安: 西安电子科技大学, 2003.
[202] 余贵水, 刘爱国, 杨云生. 蒸发波导诊断的Babin模型及其敏感性分析[J]. 宇航计测技术, 2015, 35(2): 53-56.
[203] Mesnard F, Sauvageot H. Climatology of anomalous propagation radar echoes in a coastal area[J]. Journal of Applied Meteorology and Climatology, 2010, 49(11): 2285-2300.
[204] Huuskonen A, Saltikoff E, Holleman I. The operational weather radar network in Europe[J]. Bulletin of the American Meteorological Society, 2014, 95(6): 897-907.
[205] Bruen M. Using radar information in hydrological modeling: COST 717 WG-1 activities[J]. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 2000, 25(10-12): 1305-1310.
[206] Macphersonc B. Radar data in NWP models, an outline of COST-717 working group 3[J]. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 2000, 25(10-12): 1225-1227.
[207] Saltikof E, Huuskonen A, Hohti H, et al. Quality assurance in the FMI Doppler Weather radar network[J]. Boreal Environment Research, 2010, 15: 579-594.
[208] Szturc J, Ośródka K, Jurczyk A. Quality control algorithms applied on weather radar reflectivity data[M]// Bech J, Chau J L. Doppler radar observations: Weather radar, wind profiler, ionospheric radar, and other advanced applications. Rijeka: InTech, 2012: 289-306.
[209] Moisseev D N, Chandrasekar V. Polarimetric spectral filter for adaptive clutter and noise suppression[J]. Journal of Atmospheric and Oceanic Technology, 2009, 26(2): 215-228.
[210] Stagliano J J, Kerce J C, Hall G M, et al. Prediction and mitigation of anomalous propagation with the Total Atmospheric Effects Mitigation (TAEM) system[C]. In Proceedings of the 24th International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, New Orleans, USA, January 20-24, 2008.
[211] Peter J R, Seed A, Steinle P J. Application of a Bayesian classifier of anomalous propagation to single-polarization radar reflectivity data[J]. Journal of Atmospheric and Oceanic Technology, 2013, 30(9): 1985-2005.
[212] Battan L J. Radar observation of the atmosphere[M]. Chicago: University of Chicago Press, 1973: 29-44.
[213] Skolnik M I. Radar Handbook[M]. 3rd ed. New York: McGraw‐Hill, 2008.
[214] Nathanson F E, Reilly J P, Cohen M. Radar Design Principles[M]. 2nd ed. New York: McGraw-Hill, 1991.
[215] Gregers-Hansen V, Mital R. An empirical sea clutter model for low grazing angles[C]. In Proceedings of 2009 IEEE Radar Conference, Pasadena, CA, USA, May 04-08, 2009.
[216] Gregers-Hansen V, Mital R. An improved empirical model for radar sea clutter reflectivity[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(4): 3512-3524.
[217] Stark H, Woods J W. Probability and random processes with applications to signal processing[M]. 3rd ed. Upper Saddle River: Prentice Hall, 2001: 518-524.
[218] Blum C, Li X D. Swarm Intelligence in Optimization[M]// Blum C, Merkle D. Swarm Intelligence: Introduction and Applications. Berlin: Springer Verlag, 2008: 43-85.
[219] Chan H L, Fung A K. A numerical study of the Kirchhoff approximation in horizontally polarized backscattering from a random surface[J]. Radio Science, 1978, 13(5): 811-818.
[220] Chen K S, Fung A K. A Bragg scattering model for skewed sea surface[C]. In Proceedings of Conference Proceedings on Engineering in the Ocean Environment, Washington, DC, USA, September 24-26, 1990.
[221] Voronovich A. Small-slope approximation for electromagnetic wave scattering at a rough interface of two dielectric half-spaces[J]. Waves in random media, 1994, 4(3): 337-368.
[222] Chen K S, Fung A K, Weissman D E. A backscattering model for ocean surface[J]. IEEE Transactions on Geoscience and Remote Sensing, 1991, 30(4): 811-817.
[223] Wu Z S, Zhang J P, Guo L X, et al. An improved two-scale model with volume scattering for the dynamic ocean surface[J]. Progress in Electromagnetics Research, 2009, 89: 39-56.
[224] Johnson J T, Shin R T, Kong J A, et al. A numerical study of the composite surface model for ocean backscattering[J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(1): 72-83.
[225] Zavorotny V U, Voronovich A G. Scattering of GPS signals from the ocean with wind remote sensing application[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(2): 951-964.
[226] Zuffada C, Fung A, Parker J, et al. Polarization properties of the GPS signal scattered off a wind driven ocean[J]. IEEE Transactions on Antennas and Propagation, 2004, 52(1): 172-187.
[227] Voronovich A G, Zavorotny V U. The transition from weak to strong diffuse radar bistatic scattering from rough ocean surface[J]. IEEE Transactions on Antennas and Propagation, 2017, 65(11): 6029-6034.
[228] Zhang M, Chen H, Yin H C. Facet-based investigation on EM scattering from electrically large sea surface with two-scale profiles: Theoretical model[J]. IEEE Trans. Geosci. Remote Sens., 2011, 49(6): 1967-1975.
[229] Linghu L X, Wu J J, Wu Z S, et al. Parallel computation of EM backscattering from large three-dimensional sea surface with CUDA[J]. Sensors, 2018, 18(11): 3656.
[230] 陈珲. 动态海面及其上目标复合电磁散射与多普勒谱研究[D]. 西安: 西安电子科技大学, 2012.
[231] 中国卫星导航系统管理办公室. 北斗卫星导航系统公开服务性能规范 (3.0版)[R]. 2021年5月.
[232] 中国卫星导航系统管理办公室. 北斗卫星导航系统空间信号接口控制文件-公开服务信号B1I (3.0版)[R]. 2019年2月.
[233] Department of Defense (DoD), USA. Global Positioning System Standard Positioning Service Performance Standard (5th edition)[R]. April 2020.
[234] GPS Interface Control Working Group (ICWG). NAVSTAR GPS Space Segment/Navigation User Interfaces (IS-GPS-200M)[R]. April 2021.
[235] GPS Interface Control Working Group (ICWG). NAVSTAR GPS Space Segment/ User Segment L5 Interfaces (IS-GPS-705H)[R]. March 2021.
[236] GPS Interface Control Working Group (ICWG). NAVSTAR GPS Space Segment/ User Segment L1C Interfaces (IS-GPS-800H)[R]. April 2021.
[237] 李振昌, 李仲勤, 寇瑞雄. 非滑动式与滑动式拉格朗日插值法在BDS精密星历内插中的比较分析[J]. 天文研究与技术, 2019, 16(1): 54-60.
[238] Voronovich A G, Zavorotny V U. Theoretical model for scattering of radar signals in Ku- and C-bands from a rough sea surface with breaking waves[J]. Waves Random Media, 2001, 11(3): 247-269.
[239] Brown G S. A theory for near-normal incidence microwave scattering from first-year sea ice[J]. Radio Science, 1982, 17(1): 233-243.
[240] Peacock N R, Laxon S W. Sea surface height determination in the Arctic Ocean from ERS altimetry[J]. Journal of Geophysical Research-Oceans, 2004, 109(C7): C07001.
[241] Quartly G D. Monitoring and cross-calibration of altimeter σ0 through dual-frequency backscatter measurements[J]. Journal of Atmospheric and Oceanic Technology, 2000, 17(9): 1252-1258.
[242] Alonso-Arroyo A, Zavorotny V U, Camps A. Sea ice detection using U.K. TDS-1 GNSS-R data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(9): 4989-5001.
[243] Voronovich A G, Zavorotny V U. Bistatic radar equation for signals of opportunity revisited[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(4): 1959-1968.
[244] Semmling A M, Beckheinrich J, Wickert J, et al. Sea surface topography retrieved from GNSS reflectometry phase data of the GEOHALO flight mission[J]. Geophysical Research Letters, 2014, 41(3): 954–960.
[245] Cardellach E, Li W Q, Rius A, et al. First precise spaceborne sea surface altimetry with GNSS reflected signals[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2000, 13: 102-112.
[246] Li W Q, Cardellach E, Fabra F, et al. Lake level and surface topography measured with spaceborne GNSS-Reflectometry from CYGNSS mission: Example for the Lake Qinghai[J]. Geophysical Research Letters, 2018, 45(24): 13,332-13,341.
[247] Wang K N, Ao C O, Juárez M T. GNSS-RO refractivity bias correction under ducting layer using surface-reflection signal[J]. Remote Sensing, 2020, 12(3): 359.
[248] Sokolovskiy S, Schreiner W, Zeng Z, et al. Observation, analysis, and modeling of deep radio occultation signals: Effects of tropospheric ducts and interfering signals[J]. Radio Science, 2014, 49(10): 954-970.