Zhizhao Liu

Cycle slip detection and repair for undifferenced GPS observations under high ionospheric activity

We develop a new approach for cycle slip detection and repair under high ionospheric activity using undifferenced dual-frequency GPS carrier phase observations. A forward and backward moving window averaging (FBMWA) algorithm and a second-order, time-difference phase ionospheric residual (STPIR) algorithm are integrated to jointly detect and repair cycle slips. The FBMWA algorithm is proposed to detect cycle slips from the widelane ambiguity of Melbourne–Wübbena linear combination observable. The FBMWA algorithm has the advantage of reducing the noise level of widelane ambiguities, even if the GPS data are observed under rapid ionospheric variations. Thus, the detection of slips of one cycle becomes possible. The STPIR algorithm can better remove the trend component of ionospheric variations compared to the normally used first-order, time-difference phase ionospheric residual method. The combination of STPIR and FBMWA algorithms can uniquely determine the cycle slips at both GPS L1 and L2 frequencies. The proposed approach has been tested using data collected under different levels of ionospheric activities with simulated cycle slips. The results indicate that this approach is effective even under active ionospheric conditions.

Analysis of BeiDou Satellite Measurements with Code Multipath and Geometry-Free Ionosphere-Free Combinations.

Using GNSS observable from some stations in the Asia-Pacific area, the carrier-to-noise ratio (CNR) and multipath combinations of BeiDou Navigation Satellite System (BDS), as well as their variations with time and/or elevation were investigated and compared with those of GPS and Galileo. Provided the same elevation, the CNR of B1 observables is the lowest among the three BDS frequencies, while B3 is the highest. The code multipath combinations of BDS inclined geosynchronous orbit (IGSO) and medium Earth orbit (MEO) satellites are remarkably correlated with elevation, and the systematic “V” shape trends could be eliminated through between-station-differencing or modeling correction. Daily periodicity was found in the geometry-free ionosphere-free (GFIF) combinations of both BDS geostationary Earth orbit (GEO) and IGSO satellites. The variation range of carrier phase GFIF combinations of GEO satellites is −2.0 to 2.0 cm. The periodicity of carrier phase GFIF combination could be significantly mitigated through between-station differencing. Carrier phase GFIF combinations of BDS GEO and IGSO satellites might also contain delays related to satellites. Cross-correlation suggests that the GFIF combinations’ time series of some GEO satellites might vary according to their relative geometries with the sun.

A study of smoothed TEC precision inferred from GPS measurements

The availability of a large amount of TEC data derived from dual frequency GPS measurements observed by GPS reference networks provides a great opportunity for ionosphere studies. In order to obtain better accuracy for the derived TEC, a data smoothing technique is usually employed to take advantage of both code pseudorange and carrier phase GPS measurements. The precision of TEC data therefore is dependent on the smoothing approach. However little work has been done to evaluate the precision of the smoothed TEC data obtained from different smoothing approaches. This investigation examines the properties of two popularly used smoothing approaches and develops the closed-form formulas for estimating the precision of the smoothed TEC data. In addition, a previously proposed approximate formula for estimating TEC precision is also evaluated against its closed-form formula developed in this paper. The TEC precisions derived from the closed-form precision estimation formulas for approaches I and II are analyzed in a numerical test. The results suggest that approach II outperforms approach I and the precision of TEC data smoothed by approach II is higher than approach I. For approach I, a numerical test is also conducted to compare the precision difference between the closed-form and approximate formulas for estimating TEC precision. The comparison indicates that TEC derived from the closed-form formula have better precisions than the approximate formula. Analysis also reminds users that extra cautions should be taken when using the approximate formula in order to avoid the precision divergence phenomenon.

A Comprehensive Evaluation and Analysis of the Performance of Multiple Tropospheric Models in China Region

Tropospheric path delay is an important error source in range measurements of many Earth observation systems. In this paper, the accuracies of 9 zenith hydrostatic delay (ZHD) and 18 zenith wet delay (ZWD) models are assessed using benchmark values derived from 10 years (2003-2012) of radiosonde data recorded at 92 stations in the China region. Our study confirms that ZHD can be well modeled with an accuracy of several millimeters by using surface meteorological observations. ZHD derived from the European Center for Medium-Range Weather Forecasts (ECMWF) has the best agreement of 2.8 mm with the radiosonde data in the China region, while the Baby ZHD model achieves the second best with an accuracy of 6.0 mm. All of the ZWD models can only estimate the ZWD with an accuracy of a few centimeters. ECMWF can provide ZWD estimation with the best accuracy of 21.4 mm, followed by the Baby semiempirical, Hopfield, Goad and Goodman, Askne and Nordius, Saastamoinen, Callahan, and Berman 74 ZWD models whose errors are below 40 mm. We find that in the China region all of the ZWD models perform better in winter than in summer and have higher accuracy in high latitudes than low latitudes. The performances of the 18 ZWD models are further validated in a Global Positioning System (GPS) precise point positioning (PPP) computation at 6 GPS stations in China. The PPP results also confirm that ECMWF is the best model. Considering its performance and simplicity, we conclude that Saastamoinen is the optimal ZWD model for the China region.

A Fast Level Set Algorithm for Building Roof Recognition From High Spatial Resolution Panchromatic Images

Traditional level set methods usually require repeated tuning of parameters, which is quite laborious and thus limits their applications. In order to simplify the parameter setting, this letter presents a fast level set algorithm that is a further extension of the original Chan-Vese model. For computational efficiency, we start by initializing the level set function in our algorithm as a binary step function rather than the often used signed distance function. Then, we eliminate the curvature-based regularizing term that is commonly used in traditional models. Thus, we can use a relatively larger time step in the numerical scheme to expedite our model. Furthermore, to keep the evolving level curves smooth, we introduce a Gaussian kernel into our algorithm to convolve the updated level set function directly. Finally, compared with other existing popular algorithms in an experiment of recognizing building roofs from high spatial resolution panchromatic images, the proposed model is much more computationally efficient while object recognition performance is comparable to other popular models.

Global water vapor variability and trend from the latest 36 year (1979 to 2014) data of ECMWF and NCEP reanalyses, radiosonde, GPS, and microwave satellite

The variability and trend in global precipitable water vapor (PWV) from 1979 to 2014 are analyzed using the PWV data sets from the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF), reanalysis of the National Centers for Environmental Prediction (NCEP), radiosonde, Global Positioning System (GPS), and microwave satellite observations. PWV data from the ECMWF and NCEP have been evaluated by radiosonde, GPS, and microwave satellite observations, showing that ECMWF has higher accuracy than NCEP. Over the oceans, ECMWF has a much better agreement with the microwave satellite than NCEP. An upward trend in the global PWV is evident in all the five PWV data sets over three study periods: 1979–2014, 1992–2014, and 2000–2014. Positive global PWV trends, defined as percentage normalized by annual average, of 0.61 ± 0.33% decade−1, 0.57 ± 0.28% decade−1, and 0.17 ± 0.35% decade−1, have been derived from the NCEP, radiosonde, and ECMWF, respectively, for the period 1979–2014. It is found that ECMWF overestimates the PWV over the ocean prior to 1992. Thus, two more periods, 1992–2014 and 2000–2014, are studied. Increasing PWV trends are observed from all the five data sets in the two periods: 1992–2014 and 2000–2014. The linear relationship between PWV and surface temperature is positive over most oceans and the polar region. Steep positive/negative regression slopes are generally found in regions where large regional moisture flux divergence/convergence occurs.

Galileo signal and positioning performance analysis based on four IOV satellites

With the availability of Galileo signals from four in-orbit validation (IOV) satellites, positioning with Galileo-only observations has become possible, which allows us to assess its positioning performance. The performance of the Galileo system is evaluated in respect of carrier-to-noise density ratio (C/N 0 ), pseudorange multipath (including noise), Galileo broadcast satellite orbit and satellite clock errors, and single point positioning (SPP) accuracy in Galileo-only mode as well as in GPS/Galileo combined mode. The precision of the broadcast ephemeris data is assessed using the precise satellite orbit and clock products from the Institute of Astronomical and Physical Geodesy of the Technische Universitat Munchen (IAPG/TUM) as references. The GPS-Galileo time offset (GGTO) is estimated using datasets from different types of GNSS receivers and the results indicate that a systematic bias exists between different receiver types. Positioning solutions indicate that Galileo-only SPP can achieve a three-dimensional position accuracy of about six metres. The integration of Galileo and GPS data can improve the positioning accuracies by about 10% in the vertical components compared with GPS-only solutions.

Semiautomatic Airport Runway Extraction Using a Line-Finder-Aided Level Set Evolution

In recent years, airport runway extraction has become increasingly important for various engineering applications. Existing approaches for airport runway extraction primarily focus on locating the airport roughly, i.e., determining whether an airport is present or not, but not delineating the airport runway accurately. This study develops a novel method for semiautomatic airport runway extraction from Google earth images by integrating a long straight line finder and a region-based level set evolution (LSE). Specifically, we start by detecting the long straight lines that most likely represent airport runway boundaries in the original images. Then, based on the extracted lines, we propose a method for semiautomatic generation of initial level curves for the LSE. Furthermore, for accurate extraction of the entire airport runways, a fast region-based LSE is used to evolve the initial level curves toward the desired boundaries. Experiments validate that the proposed method is capable of semiautomatically extracting objects with complex geometrical shapes and topological structures from challenging backgrounds. Compared with other state-of-the-art approaches, the proposed method has much fewer parameters and is more computationally efficient while achieving object extraction accuracy comparable to other approaches.

The First PPP-Based GPS Water Vapor Real-Time Monitoring System in Pearl-River-Delta Region, China

The first Precipitable Water Vapor Real-Time Monitoring System (PWVRMS) based on Global Positioning System Precise Point Positioning (PPP) technique has been developed for the Pearl-River-Delta region. This PWVRMS system estimates GPS satellite clock error data in real-time while using International GNSS Service (IGS) predicted precise satellite orbit directly. Currently it processes GPS data every 10 min on a daily basis from three networks in Pearl-River-Delta region: Hong Kong SatRef GPS network, Macao MoSRef GPS network and Guangdong CORS network. Compared to traditional double-differencing technique, the advantage of using PPP technique is that (1) the PWV estimation at each station is completely independent and is not affected by data quality at other stations; (2) the computation is much faster and simpler. This PWVRMS system is evaluated using radiosonde water vapor data. The GPS PWV accuracy is about 2.20 mm though the GPS station is 4.1 km away from the radiosonde. It is expected the actual GPS PWV accuracy should be higher if the GPS station is collocated with the radiosonde station. The real-time PWV products can be widely used in weather forecasts, climate researches, and water vapor correction for remote sensing images such as SAR applications. Currently the PWVRMS supplies real-time water vapor data to several meteorological agencies in Pearl-River-Delta region including Hong Kong Observatory, Macao Meteorological and Geophysical Bureau, Shenzhen Meteorological Bureau and Guangdong Meteorological Bureau for their weather forecasting service and research.

Internet-Based Real-Time Kinematic Positioning

This article investigates the use of the Internet as the communication link between the base and rover stations for the development of an Internet-based Real-Time Kinematic (RTK) system. An Internet-based RTK system has many advantages if compared to current radio-based RTK systems. To validate the concept, a prototype system has been developed and tested in both static and kinematic modes. The results indicated that the base differential data latency is in the range of about 1 second and the RTK positioning accuracy is at the centimeterl level.