Search

Android smartphone has gained attention in precise positioning applications since it can collect raw observable GNSS (Global Navigation Satellite System) data. Some studies have reported that the positioning accuracy may reach the sub-decimeter level. However, these studies mostly rely on a flagship Android smartphone that is made with better internal hardware, while the use of a non-flagship Android smartphone is not reported for this field. In this study, therefore, we explore non-flagship Android smartphones for positioning applications. We assessed the observable data quality and positioning performance of two non-flagship Android GNSS smartphones of a Samsung M21 and a Redmi Note 7. The data quality assessment includes satellite tracking and carrier-to-noise density ratio analysis. Also, the positioning performance was assessed for Single Point Positioning (SPP) and relative positioning methods in static and open-sky conditions. In addition, the residual properties of GNSS measurements were also evaluated. The results were further compared to the high-grade GNSS device. We found that the observable pseudorange and carrier phase measurements from Android smartphones were about 70 % and 36 % of what high-grade GNSS obtained. Furthermore, within a span of 1 h of observations, a considerable amount of cycle slips, amounting to as many as 518 instances, were noted in the observations from Android GNSS devices. While for the carrier-to-noise density ratio in Android smartphones, it was estimated to be about 15 dB-Hz lower than in high-grade GNSS devices. The spread of the residuals for pseudorange and carrier phase from Android smartphones was estimated to be about ±15 and ±6 m, respectively. The 3D positioning error for SPP was estimated to be about 4.7 m, with a position spread reaching tens of meters. At the same time, the 3D positioning error was calculated to be 4.6 m with the estimated standard error at the centimeter level when using the relative positioning method. To improve the positioning performance, applying a C/N0 mask to the observations become the best solution. The 3D positioning error for the relative positioning method reduces to 2.7 m when applying a C/N0 mask of 30 dB-Hz. The observable data quality of non-flagship Android GNSS devices possibly causes relatively poor performance of positioning applications. [ABSTRACT FROM AUTHOR]

As the modernized Global Navigation Satellite System (GNSS) method, Real Time Kinematic (RTK) ensures high accuracy of position (within several centimeters). This method uses Ultra High Frequency (UHF) radio to transmit the correction data, however, due to gain and power issues, Networked Transport of RTCM via Internet Protocol (RTCM) is used to transmit the correction data for a longer baseline. This Research aims to investigate the performance of short to long-range single baseline RTK GNSS (Up to 80 KM) by applying modified LAMBDA method to resolve the ambiguity in carrier phase. The RTK solution then compared with the differential GNSS network solution. The results indicate that the differences are within RTK accuracy up to 80 km are several centimeter for horizontal solution and three times higher for vertical solution.

Bandung-Jakarta, Indonesia highway have high density vehicles pass even often jammed. High activity of vehicles cause repeated vibrations and occur continuously. In case, the highway that divides the hills. The passing vehicles give rise repeatedly vibration and indicated disturbance of hillside slope stability. Vehicles vibration depend on speed, weight, number of vehicles and road construction materials. A method in question is counting a vehicle volume and determine the volume pattern of the vehicle. The magnitude of vibration is function of the object distance from the sources. The magnitude of the vibration effect is very dependent on the geological structure of hills formation. Hilly slope stability indicates experiencing interference if the object or material slope changes position or displacement. GPS observation give position changes and its displacement. The effect of Toll road vibration to slope stability is known by GPS and Vibration simultaneous measurement. Data acquisition used six unit GPS receivers and six unit vibration sensor which is installed on the hillside beside the highway. Integrated data processing techniques using Empirical Mode Decomposition (EMD). Integrated GPS-Vibration data are implemented to find actual displacement which are caused by highway vibration.

This paper assesses the agreement between observed heights of sea level from Global Navigation Satellite System (GNSS) and a global model of Mean Sea Surface (MSS). The assessment of the agreement is carried out according to the direct comparison between the height of MSS model and the geodetic height of actual sea level. Here, MSS is generated according to Gravity Recovery And Climate Experiment (GRACE) Gravity Model (GGM) and Mean Dynamic Ocean Topography (MDOT). The tracking of geodetic heights of actual sea level are done by Wide Area Differential (WA D) and Real Time Precise Point Positioning (RTPPP) Global Navigation Satellite System (GNSS) along an approximately 180 Nm SW-NE transect of away-return ship track in the west of the Java Sea, Indonesia. It is found that the overall agreement between geodetic height of sea level and MSS observed by WA DGNSS is 7.5 cm (away tracking), while those observed by RTPPP GNSS is 39.5 cm (away tracking) and 36.0 cm (return tracking). This work recommends selection of the best-fit tide model and careful examination on the dynamics of antenna offset due to vessel attitude.

In Indonesia, Global Navigation Satellite System (GNSS) has become one of the important tool in survey mapping, especially for cadastral purposes like land registration by using Real Time Kinematic (RTK) GNSS positioning method. The conventional RTK GNSS positioning method ensure high accuracy GNSS position solution (within several centimeters) for baseline less than 20 kilometers. The problems of resolving high accuracy position for a greater distance (more than 50 kilometers) becomes greater challenge. In longer baseline, atmospheric delays is a critical factor that influenced the positioning accuracy. In order to reduce the error, a modified LAMBDA ambiguity resolution, atmospheric correction and modified kalman filter were used in this research. Thus, this research aims to investigate the accuracy of estimated position and area in respect with short baseline RTK and differential GNSS position solution by using NAVCOM SF-3040. The results indicate that the long-range single baseline RTK accuracy vary from several centimeters to decimeters due to unresolved biases.

Land subsidence is not a new phenomenon for Semarang the capital city of Central Java Province with recent population of about 1.5 million. Some report said the subsidence in Semarang probably is occurring for more than 100 years. Geodetic surveys such as GPS Surveys can detect land subsidence accurately. Land subsidence in Semarang exhibits spatial and temporal variations with the typical average rates of about 3 to 10 cm/year until recently it seem the acceleration existed in some region of the city. This acceleration will increase the risk of negative consequences from the land subsidence. This paper present and discuss the acceleration of land subsidence in Semarang as detected from GPS Surveys. The surveys have been conducted in 2008, 2009, 2010, 2012, 2016 and 2017. From 2008 to 2012 the subsidence generally follow linier rates while from 2012 to 2017 seem they are accelerating. The northern eastern region of Semarang along the coastal area still exhibits relatively higher rates of subsidence along with acceleration in rates compare to others region. Ground water exploitation is suspected to be the causes of that land subsidence phenomenon in Semarang city

Land subsidence is not a new phenomenon for Jakarta and Semarang areas. According to some publications, the value of Jakarta’s subsidence may reach 2-4 meter in certain place. Meanwhile, more than 2 meter of subsidence is taking place in northern part of Semarang. Some techniques are being used to derive land subsidence information in these areas such as repeated leveling measurements, GPS surveys, and InSAR measurements. The impact of land subsidence in Jakarta and Semarang could be seen in several ways, such as sea inundation (“Rob” in Javanese), problem on infrastructures, the wider expansion of flooding areas, etc. Cracking on housing, street, “sinking” on the bridges and dyke, problems on drainage are examples of infrastructures problems due to the land subsidence. Huge costs have already been spent to fixing those infrastructures problems both in Jakarta and Semarang. Since mostly liniear pattern of land subsidence are recognized in both area today and probably in the next years to come, in this case the impact especially on infrastructures are probably will getting worse. Insight look the subsidence impact to the infrastuctures in Jakarta and Semarang area would raisen the concern, and become key for adaptation and mitigation.