Low Elevation Angles Research Articles

An Estimator for Weather Radar Doppler Power Spectrum via Minimum Mean Square Error

This article proposes a method for estimating the Doppler power spectrum (DPS) of a weather radar via minimum mean square error (MMSE). In order to detect severe weather phenomena that mostly occur within the lowest few kilometers of the atmosphere, weather radars have to direct their beams at low elevation angles, and the received signals from such observations usually contain reflections from the ground and buildings, so-called ground clutter. The MMSE estimator, which is an adaptive spectral estimator, allows weather radar DPSs to be obtained with excellently reduced ground clutter contaminations. The MMSE estimator was examined by numerical simulations, which supposed various precipitation and ground clutter scenarios and DPS estimation parameter values. The MMSE estimator provided DPSs almost as accurate as those from the traditional Fourier and windowed Fourier estimators in simulations with no ground clutter and much better DPSs than those estimators in the presence of ground clutter. Furthermore, the MMSE estimator gave better suppression of ground clutter contamination than the Capon estimator, which is another adaptive spectral estimator. As a result of statistical evaluations, ground clutter signals with a strong clutter-to-noise ratio of 70 dB appeared only in a narrow velocity range of the MMSE DPS, from −2 to 2 m/s, and caused degradation of the mean and standard errors outside this velocity range by just 1 dB. The MMSE estimator was also applied to signals received by actual weather radar, and DPS estimation of precipitation signals with similarly low ground clutter contamination was demonstrated.

Influence of the inhomogeneous troposphere on GNSS positioning and integer ambiguity resolution

The tropospheric delay is one of many error sources that affect the Global Navigation Satellite System (GNSS) positioning solutions. The widely used troposphere models assume a homogeneous atmosphere so that only the zenith delay needs to be determined and is mapped through an elevation-dependent mapping function. This procedure is to reduce the computational burden and keep the positioning model full-rank. However, this assumption fails for a realistic description of the troposphere, which is always asymmetrical at a certain elevation angle, especially during a weather event when the weather conditions are very complex. These imperfectly modelled tropospheric delays may influence the positioning accuracy and integer ambiguity resolution performance. In this case, this contribution aims to investigate the effects of the model errors due to the asymmetrical troposphere on GNSS estimations. The Numerical Weather Prediction (NWP) model is applied to generate the actual ray-tracing tropospheric delay in Western Europe, and the tropospheric model errors are calculated in a normal weather condition and a weather event condition by comparing the slant delay calculated from the NWP model and the mapping function. Case studies on the same GNSS station are conducted in two weather conditions: a normal troposphere condition and a weather event with heavy rainfall. The results based on the case studies show that the troposphere in the normal weather condition is nearly homogeneous that the azimuthal-dependent discrepancies of the tropospheric delay are less than 1cm at a very low elevation angle; meanwhile, the discrepancies between different azimuthal angles can reach to more than 25cm in the weather event. A single-frequency Single Point Positioning (SPP) model and a Precise Point Positioning (PPP) model that preserves the integer property of ambiguity are chosen for studying the estimation biases caused by the troposphere model errors. It turns out that almost all horizontal positioning biases of SPP and PPP are less than 1cm in the normal weather condition; however, the scales of the horizontal and 3D biases are concentrated in 1 to 10cm in the weather event for these two models. This contribution also contains the study of the actual integer ambiguity resolution success rate in the presence of the tropospheric model errors by applying the Monte Carlo simulation, and the success rates of PPP in the normal weather condition are consistent with the theoretical values calculated with the ideal troposphere which is totally symmetrical. However, the actual success rates in the weather event are extremely low at some epochs due to the tropospheric model errors, which means that wrong fixing may occur since the theoretical values cannot take into account these model errors. Note that the horizontal tropospheric gradients are not involved in the processing, which means that an optimistic performance might be expected if the gradients are considered.

Дослідження залежності флуктуацій амплітуди GPS сигналів від метеорологічних факторів при проходженні через турбулентну атмосферу над сушею під малими кутами місця

Subject and Purpose. The paper investigates tropospherically caused fluctuations of signals from the GPS navigation system while the satellite is beyond the radio horizon. The intensity of GPS signal fluctuations under the influence of meteorological factors is studied, too. The purpose of the work is to determine relationship between the intensity of GPS signal fluctuations and the meteorological conditions when satellite elevation angles are small. Methods and Methodology. The methodology of the work is based on the search for the intensity of amplitude fluctuations of GPS satellite’s signals depending on the meteorological situation. The measurement approach is registration of the GPS satellite’s signal level just before the satellite crosses the horizon. The data processing after a series of experimental studies is based on the extraction of tropospheric fluctuations from the complete GPS signal by the moving average method. Results. Experimental studies of the turbulent component of signals from GPS satellites at low elevation angles have been carried out. It has been revealed that a conventional elevation boundary below which the tropospheric influence is predominant can be established due to the synchronism property which the orbits of the GPS satellites hold. It has been shown that variations in the mean square deviation (MSD) of GPS signal fluctuations caused by the troposphere and extracted from the complete signal are consistent with meteorological parameter changes. Conclusion. Analysis has been carried out to show that a meteorological dependence of the MSD statistics of GPS signal tropospheric fluctuations exists. The intensity of fluctuations rises with the convective activity in the troposphere. The conducted experiments suggest that periods of increased turbulence in the atmosphere can be detected with the use of GPS signals. For this purpose, the optical methods will not do.

Analysis of differential code biases and inter-system biases for GPS and NavIC satellite constellations

<abstract> <p>Multi Global Navigation Satellite System (GNSS) plays an essential role in navigation and geodesy fields for positioning, Navigation, and Timing (PNT) services. The predominant challenge of multi-GNSS is hardware bias errors such as Differential code Bias (DCB) and Inter System Biases (ISB). The estimation of DCB and ISB are essential for analyzing the GNSS system performance to improve the positional accuracy. Navigation with the Indian Constellation (NavIC) system consists of the entire constellation of seven Geo-Stationary satellites to cater to Position Navigation Time (PNT) services over India and adjacent areas. In this paper, the relation between DCB and ISB of Global Positioning System (GPS) and NavIC systems is investigated using two ground-based NovAtel GPS and three Accords NavIC Receivers data (January to April 2019) at Koneru Lakshamaiah Education Foundation (K.L. Deemed to University), Guntur, India (16.47°N, 80.61°E). The correlation results indicate that NavIC GSO satellites are more stable than GEO satellites from DCB and ISB analysis due to low elevation angles and multipath effects. A systematic bias error is observed between NavIC and GPS satellite systems from ISB and DCB results. The current research work outcome would be beneficial for modeling GNSS ionospheric Total Electron Content (TEC) for high precision multi-constellation and multi-frequency GNSS systems.</p> </abstract>

An Unbiased Multiparameter Algorithm of Retrieving Sea Surface Height Using Coastal GNSS Reflectometry

Due to the diffuse scattering on sea surface and dynamic geometry of coastal GNSS- R, the altimetry performance is strong dependent on elevation angle. As elevation angle decreases, the bias in retrieved height using DER and HALF retracker increases. In this paper, an multi-parameter estimator is proposed to combine the DER retracker and several HALF retrackers to obtain unbiased height. The simulated results show that the bias of the uncalibrated height using proposed algorithm has no significant dependence on elevation angle, but the RMSE for the low elevation angle case still are larger than that of the high elevation angle. In addition, the calibrated performance depends on the used fractional values so that proper fractional values should be chosen. The data from Dongying experiment acquiring GPS L1 CA and L5 signal and Qingdao experiment for BeiDou B1I signal are used to demonstrate proposed algorithm. After calibrating using proposed algorithm, regardless of GPS L1 CA, L5 or BeiDou B1I signal, the calibrated heights all are agreement with in-situ heights. Finally, the calibrated heights from BeiDou B1I signal are used to retrieve sea surface height. The results show that retrieved sea surface heights from GEO and IGSO/MEO satellites all appear the same trend with in-situ ones, furthermore, GEO satellites can provide the better retrieved performance than IGSO/MEO satellites. Through averaging the heights from several satellites and smoothing with the half-hour span, compared to in-situ sea surface height the RMSE of 0.67 m is obtained.

Beam Split Algorithm for Height Measurement With Meter-Wave MIMO Radar

In order to improve the feasibility of low-elevation height measurement for meter-wave multiple-input multiple-output (MIMO) radar, a virtual sub-array-level beam splitting low-elevation height measurement algorithm is proposed. The algorithm can solve the coherence problems caused by low-angle multipath reflection, target reflection wave and direct wave coupling, and quickly measure the low elevation angle of the target on a flat ground, and then obtain the target height through the geometric relationship. First, establish an error graph in advance according to the radar frequency, antenna height and reflection coefficient; then combine the nine virtual channels of the three-element MIMO radar into three channels; then use the phase difference between adjacent channels to perform low-elevation encoding to confirm the target elevation range; The calculated amplitude error value is compared with the error curve diagram established in advance to obtain the target low elevation angle; finally, the target height data is obtained according to the geometric relationship. The signal model and error formula under complex terrain are finally derived. The simulation verifies the accuracy and superiority of the proposed algorithm on flat ground and complex undulating ground.

Visibility Anomaly of GNSS Satellite and Support from Regional Systems

In a multi-GNSS (global navigation satellite system) environment with operational GPS, GLONASS and Galileo Satellites, the Asia–Oceania region is expected to get better benefits of a large number of GNSS satellites for use. However, it is witnessed that during some parts of the day, no GNSS satellite is present above 60° elevation angle from many parts of the earth, including India. Real-time data from India show the regular absence of usable GPS satellites above 60° elevation angles during some parts of the day; addition of GLONASS and Galileo satellites does not improve the situation much. From Burdwan, West Bengal, India at least twice a day, no GNSS satellite is found above 60° elevation angles for more than 30 min. Simulation study for scattered places of India and data from IGS Centres confirm similar observations, except for the extreme northern region. The global scenario also supports these observations, while the individual operator’s country is free from the problem using their own navigational system. The consequences of the problem affect GNSS-based solutions; for locations with obstruction of GNSS signals from low elevation angles, the concurrent occurrence of this incidence poses a threat for seamless GNSS-based navigation through intermittent loss of solution and degraded solution quality. Regional navigation satellite systems (RNSS) help mitigate this problem within the respective service regions. For a large part of the globe, the problem may be allayed using GNSS–RNSS hybrid operation. The result would be important for location-specific GNSS mission planning in strategic, life and safety-critical applications.

Influence of the ray elevation angle on seafloor positioning precision in the context of acoustic ray tracing algorithm

In high precision underwater acoustic positioning, the ray tracing algorithm is often used to reduce the acoustic ray error. However, it is generally assumed that precision of the acoustic ray with low elevation angle is the same to that with high elevation angle. In the context of the ray tracing algorithm, with the Snell acoustic equation we derive a relationship between the ray tracing error and the observational elevation angle, and then a stochastic model of acoustic positioning is established referring to this relation. Experimental results show that the acoustic observation noise level is highly related to the elevation angle. This indicates that, the weight of observation with low elevation angle should be reduced in the seafloor positioning, and the proposed model can be used to reduce the influence of low elevation angle observations on the positioning accuracy.

Cloud attenuation statistics from radiometric measurements over a tropical location Kolkata, India

The objective of this study is to investigate cloud attenuation at 30 GHz frequency using ground-based microwave radiometric observations at a tropical location, Kolkata. At higher frequencies and lower elevation angles, cloud attenuation is of major concern at a tropical location. The location experiences high value of liquid water path (LWP), which is responsible for cloud attenuation, during the Indian summer monsoon (ISM) and pre-monsoon season. Significant amount of cloud attenuation has been observed during monsoon season at 30 GHz. Two years observations of exceedance probability of cloud attenuation and worst month statistics are presented. The variation of cloud attenuation with frequencies for different elevation angles has also been investigated. The seasonal and diurnal patterns of cloud attenuation are examined. Cloud attenuation, inferred from radiometric measurements before rain commencement, has been compared to rain attenuation at Ku-band. Exceedance probabilities of cloud and rain attenuation have been compared.

Characteristics of Ionospheric Irregularities Using GNSS Scintillation Indices Measured at Jang Bogo Station, Antarctica (74.62°S, 164.22°E)

AbstractGlobal Navigation Satellite System (GNSS) signals strongly depend on the ionospheric conditions, which are composed of electrons and ions generated by solar radiation and particle precipitation. Ionospheric plasma irregularities may cause the scintillation of the GNSS signals or even the loss of signal lock, resulting in the reduction of positioning accuracy and timing precision. Phase scintillation phenomenon is known to occur frequently at high latitudes and primarily related to a significant plasma density gradient, which is due to fast plasma flows in the polar region, energetic particle precipitation in the auroral region, polar cap patches, or several instability mechanisms. Statistical studies are required to understand the characteristics of ionospheric (both phase and amplitude) scintillations at high latitudes. Here, we report the results of ionospheric scintillation measurements at Jang Bogo Station (JBS; 74.62°S, 164.22°E), located inside the polar cap region in Antarctica. The occurrence rates of ionospheric scintillations over the JBS are recorded for 2 years (2017–2018) during solar minimum conditions. The occurrence rates of amplitude scintillations increase only at lower elevation angles (below 30°), which are hard to determine whether the source is ionospheric irregularity or ambient noise such as multipath. In contrast, the occurrence rates of phase scintillations depend on the azimuth angle, season, magnetic activity, magnetic local time, and signal frequency. The results of our analysis suggest that users of the GNSS should consider these parameters to prepare for the degradation of the GNSS performance at high latitudes in the Southern Hemisphere.

Enhanced signalling provisioning for UAV‐enabled MEC: A GWFRFT‐based energy‐spreading transmission approach

With the high mobility, flexibility and manoeuvrability, unmanned aerial vehicles (UAVs)-enabled mobile edge computing (MEC) plays an important role in many applications that lack of available terrestrial infrastructures, such as disaster response, emergency relief and military scenarios. However, the high mobility of UAVs may severely degrade the implementation of UAV-enabled MEC in computation-intensive or delay-sensitive scenarios from a physical layer signalling perspective, e.g. frequency selective fading effect caused by the low altitude and low elevation angle routes of UAVs. In this study, a generalised weighted-type fractional Fourier transform (GWFRFT) based signal energy-spreading transmission (EST) scheme is proposed for signalling and quality of service (QoS) provisioning for UAV-enabled MEC. In the proposed scheme, the communication signal energy is redistributed evenly at the time-frequency plane to enhance the robustness of UAV communications against the severe fading channels. The signalling provisioning mechanism of the GWFRFT-EST scheme is analysed and simulated under poor air-to-ground channels with low Rician K-factor. Simulation results show that the proposed method greatly improves the bit error rate performance with a negligible computational complexity increase.

An advanced residual error model for tropospheric delay estimation

Global navigation satellite systems (GNSS) are widely used for safety-of-life positioning applications. Such applications require high integrity, availability, and continuity of the positioning service. Integrity is assessed by the definition of a protection level, which is an estimation of the maximum positioning error at extremely low probability levels. The emergence of multi-frequency civilian signals and the availability of satellite-based augmentation systems improve the modeling of ionospheric disturbances considerably. As a result, in many applications the tropospheric delay tends to become one of the limiting factors of positioning—especially at low elevation angles. The currently adopted integrity concepts employ a global constant to model the variance of the residual tropospheric delay error. We introduce a new approach to derive residual tropospheric delay error models using the extreme value analysis technique. Seventeen years of global numerical weather model fields are analyzed, and new residual error models are derived for some recently developed tropospheric delay models. Our approach provides models that consider both the geographical location and the seasonal variation of meteorological parameters. Our models are validated with a 17-year-long time series of zenith tropospheric delay estimates as provided by the International GNSS Service. The results show that the developed models are still conservative, while the maximal residual error of the tropospheric delay is still improved by 39–55%. This improvement yields higher service availability and continuity in safety-of-life applications of GNSS.

Compact S-band and X-band antennas for CubeSats

This paper presents compact S-band and X-band antenna products dedicated to CubeSat applications and their radio frequency performances. The S-band antenna covers simultaneously the 2.025–2.110 GHz telecommand and the 2.2–2.29 GHz telemetry band. It has a hemispherical radiation pattern with superior gain and lower axial ratio values at low elevation angles compared to other S-band antennas on the market. On the other side, the X-band antenna is optimized for payload TM at the frequencies 8.025–8.4 GHz. The antenna gain is higher than 10 dBi over ± 10° in all planes and the axial ratio is excellent. Both antennas are smaller than a 1 U surface and have unequalled RF performances. All processes and materials have strong space heritage and benefit from the Cnesadvanced label. These antennas are thus perfectly suited for professional CubeSat missions with high level of performance and reliability.

An Analysis of an Ostensible Anticyclonic Tornado from 9 May 2016 Using High-Resolution, Rapid-Scan Radar Data

AbstractTornadic supercells moved across parts of Oklahoma on the afternoon and evening of 9 May 2016. One such supercell, while producing a long-lived tornado, was observed by nearby WSR-88D radars to contain a strong anticyclonic velocity couplet on the lowest elevation angle. This couplet was located in a very atypical position relative to the ongoing cyclonic tornado and to the supercell’s updraft. A storm survey team identified damage near where this couplet occurred, and, in the absence of evidence refuting otherwise, the damage was thought to have been produced by an anticyclonic tornado. However, such a tornado was not seen in near-ground, high-resolution radar data from a much closer, rapid-scan, mobile radar. Rather, an elongated velocity couplet was observed only at higher elevation angles at altitudes similar to those at which the WSR-88D radars observed the strong couplet. This paper examines observations from two WSR-88D radars and a mobile radar from which it is argued that the anticyclonic couplet (and a similar one ~10 min later) were actually quasi-horizontal vortices centered ~1–1.5 km AGL. The benefits of having data from a radar much closer to the convective storm being sampled (e.g., better spatial resolution and near-ground data coverage) and providing more rapid volume updates are readily apparent. An analysis of these additional radar data provides strong, but not irrefutable, evidence that the anticyclonic tornado that may be inferred from WSR-88D data did not exist; consequently, upon discussions with the National Weather Service, it was not included in Storm Data.

Raytracing atmospheric delays in ground-based GNSS reflectometry

Several studies have recognized that Global Navigation Satellite System Reflectometry (GNSS-R) is subject to atmospheric propagation delays. Unfortunately, there is little information in the peer-reviewed literature about the methods and algorithms involved in correcting for this effect. We have developed an atmospheric ray-tracing procedure to solve rigorously the three-point boundary value problem of ground-based GNSS-R observations. We defined the reflection-minus-direct or interferometric delay in terms of vacuum distance and radio length. We clarified the roles of linear and angular refraction in splitting the total delay in two components, along-path and geometric. We have introduced for the first time two subcomponents of the atmospheric geometric delay, the geometry shift and the geometric excess. We have defined corresponding atmospheric altimetry corrections necessary for unbiased altimetry retrievals. Using simulations, we examined the interferometric atmospheric delay for a range of typical scenarios, where it attained centimeter-level values at low satellite elevation angles ~ 5° for a 10-m high station. We found a linear and exponential dependence on reflector height and satellite elevation angle, respectively. A similar trend was found for the atmospheric altimetry correction, albeit with an amplified meter-level magnitude. The two delay components were similar near the horizon while the angular one vanished at zenith. For the altimetry correction components, both remained non-zero at zenith. We thus quantified the atmospheric bias in GNSS-R sea level retrievals.

A simplification of rigorous atmospheric raytracing based on judicious rectilinear paths for near-surface GNSS reflectometry

Atmospheric delays are known to cause biases in Global Navigation Satellite System Reflectometry (GNSS-R) altimetry applications, such as for sea-level monitoring. The main quantity of interest is the reflection-minus-direct or interferometric atmospheric delay. Recently, we have presented a rigorous raytracing procedure to account for linear and angular refraction in conjunction with reflection as observed from near-surface platforms. Here, we demonstrate the feasibility of simplifying the ray trajectory by imposing a rectilinear wave propagation model. Two variants were assessed, based on the apparent or refracted satellite direction on the one hand and the geometric or vacuum conditions on the other hand. The former was shown to agree with rigorous results in terms of interferometric radio length while the latter agreed in terms of the interferometric vacuum distance. Upon a judicious combination of the best aspects of the two rectilinear cases, we have defined a mixed variant with excellent agreement with rigorous raytracing in terms of interferometric atmospheric delay. We further showed that mapping functions developed for GNSS positioning cannot be reused for GNSS-R purposes without adaptations. Otherwise, the total atmospheric delay may be underestimated by up to 50% at low elevation angles. The present work facilitates the adaptation of existing atmospheric raytracing software for GNSS-R purposes.

VMF3o: the Vienna Mapping Functions for optical frequencies

The troposphere is considered as one of the major error sources in space geodetic techniques. Thus, accurate troposphere delay models are essential to provide high-quality products, such as reference frames, satellite orbits, or Earth rotation parameters. In this paper, a new troposphere delay model for satellite laser ranging, the Vienna Mapping Functions 3 for optical frequencies (VMF3o), is introduced. The model parameters are derived from ray-traced delays generated by an in-house ray-tracing software. VMF3o comprises not only zenith delays and mapping functions, but also linear horizontal gradients, which are not part of the standard SLR analysis yet. The model parameters are dedicated to a signal wavelength of 532 nm. Since some SLR stations operate also with other wavelengths, VMF3o provides a correction formula to transform the model parameters to any requested wavelength between 350 and 1064 nm. A test demonstrates that the correction formula approximates slant delays calculated at different wavelengths very accurately. The remaining error for slant delays at a wavelength of 1064 nm adds up to only a few millimetres at 10^{circ } elevation angle. A comparison study of the modelled delays that are derived from VMF3o and ray-traced delays was carried out to examine the quality of the model approach. The remaining differences of modelled and ray-traced delays are expressed as mean absolute error. At 5^{circ } elevation angle, the mean absolute error is only a few millimetres. At 10^{circ } elevation angle, it is at the 1 mm level. The results of the comparison also reveal that introducing linear horizontal gradients reduces the mean absolute error by more than 80% for low elevation angles.

Low Elevation Angle Estimation with Range Super-Resolution in Wideband Radar.

Height detection of a low elevation angle target is crucial in radar applications. Due to the presence of the multiple path reflections, elevation angle estimation is difficult with conventional narrowband radar waveforms. The reflection ground area parameters are especially hard to obtain for modeling. In this paper, we proposed a wideband, low elevation angle estimator based on range super-resolution, achieving a high robustness to variations in reflection coefficients. A relaxation (RELAX) algorithm was applied as the range super-resolution algorithm to separate the direct target echo and the reflected signal thanks to the relatively abundant frequency diversity. The grazing angle was obtained by synthesizing the steering vector of the direct signal and the range structure relationship between the two signal components. Theoretical analysis and simulation results confirmed the improved behavior of the proposed robust estimator in contrast to other conventional algorithms.

Characteristics and Applications of the Ground-Based X Band Low Elevation Angle Brightness Temperatures under Low Sea State Based on Measured Data

In ground-based microwave radiometer remote sensing, low-elevation-angle (−3°~3°) radiation data are often discarded because they are considered to be of little value and are often difficult to model due to the complicated mechanism. Based on the observed X-band horizontal polarization low elevation angle microwave radiation data and the meteorological data at the same time, this study investigated the generation mechanism of low elevation angle brightness temperature (LEATB) and its relationship with meteorological data, i.e., temperature, humidity, and wind speed, under low sea state. As a result, one could find that the LEATB was sensitive to the atmosphere at the elevation angle between 1° to 3°, and a diurnal variation of the LEATB reached up to 10 K. This study also found a linear relationship between the LEATB and sea surface wind speed under low sea state at an elevation range from −3° to 0°, i.e., the brightness temperature decreased as the wind speed increased, which was inconsistent with the observations at the elevation angle from −10° to −5°. The variation of the LEATB difference according to the change in the over-the-horizon detection capability (OTHDC) of the shipborne microwave radar was examined to identify the reason for this phenomenon theoretically. The results showed that the LEATB difference was significantly influenced by a change in the OTHDC. Further, this study examined a remote sensing method to extract the sea surface wind speed data from experimental LEATB data under low sea state. The results demonstrated that the X-band horizontal polarization LEATBs were useful to retrieve the sea surface wind speed data at a reasonable accuracy—the root mean square error of 0.02408 m/s. Overall, this study proved the promising potential of the LEATB data for retrieving temperature profiles, humidity profiles, sea surface winds, and the OTHDC.

Machine learning based LOS/NLOS classifier and robust estimator for GNSS shadow matching

Global Navigation Satellites Systems (GNSS) is frequently used for positioning services in various applications, e.g., pedestrian and vehicular navigation. However, it is well-known that GNSS positioning performs unreliably in urban environments. GNSS shadow matching is a method of improving accuracy in the cross-street direction. Initial position and classification of observed satellite visibility between line-of-sight (LOS) and non-line-of-sight (NLOS) are essential for its performance. For the conventional LOS/NLOS classification, the classifiers are based on a single feature, extracted from raw GNSS measurements, such as signal noise ratio, pseudorange, elevation angle, etc. Especially in urban canyons, these measurements are unstable and unreliable due to the signal reflection and refraction from the surrounding buildings. Besides, the conventional least square approach for positioning is insufficient to provide accurate initialization for shadow matching in urban areas. In our study, shadow matching is improved using the initial position from robust estimator and the satellite visibility determined by support vector machine (SVM). The robust estimator has an improved positioning accuracy and the classification rate of SVM classification can reach 91.5% in urban scenarios. An important issue is related to satellites with ultra-high or low elevation angles and satellites near the building boundary that are very likely to be misclassified. By solving this problem, the SVM classification shows the potential of about 90% classification accuracy for various urban cases. With the help of these approaches, the shadow matching has a mean error of 10.27 m with 1.44 m in the cross-street direction; these performances are suitable for urban positioning.