The development of low-cost GNSS chips inspired the development of advanced positioning, navigation and timing devices. In ‘I/O of 2016’, Google announced that GNSS observations from devices running the Android version 7 operating system would be available to developers. Providing GNSS application developers the opportunity to develop advanced processing algorithms for accurate position estimation using pseudorange, Doppler and carrier phase observations. The quality of GNSS observations from Android smartphones and their accuracy in estimating position is assessed. The observed carrier-to-noise density ratio (C/N0), pseudorange noise, pseudorange rate error and phase rate error of GNSS observations are evaluated. The results demonstrate that the average (C/N0) value is approximately 10 dB-Hz lower than the representative values obtained from a geodetic-quality antenna and receiver. The station single-difference pseudorange residuals on all available signals vary from − 20 to 20 m, and the value of pseudorange rate varies within ± 10 m/s. In addition, the phase rate and Doppler reaches approximately ± 0.2 m/s. Different from the geodetic receivers, the signal noise ratio (SNR) obtained from smartphone varies more significantly, regardless of elevation angle. Therefore, the SNR-dependent weighting method is preferred during data processing. Furthermore, the results of the static data analysis show that the horizontal and vertical RMS position errors are less than 0.8 and 1.4 m, respectively, when Doppler and phase observations are incorporated into the positioning solution.

Quality assessment of GNSS observations from an Android N smartphone and positioning performance analysis using time-differenced filtering approach

On May 2018 the world’s first dual-frequency Global Navigation Satellite System (GNSS) smartphone produced by Xiaomi equipped with a Broadcom BCM47755 chip was launched. It is able to receive L1/E1/ and L5/E5 signals from GPS, Galileo, Beidou, and GLONASS (GLObal NAvigation Satellite System) satellites. The main aim of this work is to achieve the phone’s position by using multi-constellation, dual frequency pseudorange and carrier phase raw data collected from the smartphone. Furthermore, the availability of dual frequency raw data allows to assess the multipath performance of the device. The smartphone’s performance is compared with that of a geodetic receiver. The experiments were conducted in two different scenarios to test the smartphone under different multipath conditions. Smartphone measurements showed a lower C/N0 and higher multipath compared with those of the geodetic receiver. This produced negative effects on single-point positioning as showed by high root mean square error (RMS). The best positioning accuracy for single point was obtained with the E5 measurements with a DRMS (horizontal root mean square error) of 4.57 m. For E1/L1 frequency, the 2DRMS was 5.36 m. However, the Xiaomi Mi 8, thanks to the absence of the duty cycle, provided carrier phase measurements used for a static single frequency relative positioning with an achieved 2DRMS of 1.02 and 1.95 m in low and high multipath sites, respectively.

/pdf/assessment-of-dual-frequency-gnss-observations-from-a-xiaomi-ra6hhebjrw.pdf

Assessment of Dual Frequency GNSS Observations from a Xiaomi Mi 8 Android Smartphone and Positioning Performance Analysis

An iPhone 6 using the Avenza software for capturing horizontal positions was employed to understand relative positional accuracy in an urban environment, during two seasons of the year, two times of day, and two perceived WiFi usage periods. On average, time of year did not seem to influence the average error observed in horizontal positions when GPS-only (no WiFi) capability was enabled, nor when WiFi was enabled. Observations of average horizontal position error only seemed to improve with time of day (afternoon) during the leaf-off season. During each season and during each time of day, horizontal position error seemed to improve in general during perceived high WiFi usage periods (when more people were present). Overall average horizontal position accuracy of the iPhone 6 (7-13 m) is consistent with the general accuracy levels observed of recreation-grade GPS receivers in potential high multi-path environments.

/pdf/smartphone-gps-accuracy-study-in-an-urban-environment-57pa3osyoo.pdf

Smartphone GPS accuracy study in an urban environment.

Differential GPS와 응용

Quality analysis of multi-GNSS raw observations and a velocity-aided positioning approach based on smartphones

The position accuracy of Global Navigation Satellite System (GNSS) modules is one of the most significant factors in determining the feasibility of new location-based services for smartphones. Considering the structure of current smartphones, it is impossible to apply the ordinary range-domain Differential GNSS (DGNSS) method. Therefore, this paper describes and applies a DGNSS-correction projection method to a commercial smartphone. First, the local line-of-sight unit vector is calculated using the elevation and azimuth angle provided in the position-related output of Android’s LocationManager, and this is transformed to Earth-centered, Earth-fixed coordinates for use. To achieve position-domain correction for satellite systems other than GPS, such as GLONASS and BeiDou, the relevant line-of-sight unit vectors are used to construct an observation matrix suitable for multiple constellations. The results of static and dynamic tests show that the standalone GNSS accuracy is improved by about 30%–60%, thereby reducing the existing error of 3–4 m to just 1 m. The proposed algorithm enables the position error to be directly corrected via software, without the need to alter the hardware and infrastructure of the smartphone. This method of implementation and the subsequent improvement in performance are expected to be highly effective to portability and cost saving.

Position Accuracy Improvement by Implementing the DGNSS-CP Algorithm in Smartphones.

A differential global positioning system (DGPS) is one of the most widely used augmentation systems for a low-cost L1 (1575.42 MHz) single-frequency GPS receiver. The positioning accuracy of a low-cost GPS receiver decreases because of the spatial decorrelation between the reference station (RS) of the DGPS and the users. Hence, a network real-time kinematic (RTK) solution is used to reduce the decorrelation error in the current DGPS system. Among the various network RTK methods, the Flachen Korrektur parameter (FKP) is used to complement the current DGPS, because its concept and system configuration are simple and the size of additional data required for the network RTK is small. The FKP was originally developed for the carrier-phase measurements of high-cost GPS receivers; thus, it should be modified to be used in the DGPS of low-cost GPS receivers. We propose an FKP-DGPS algorithm as a new augmentation method for the low-cost GPS receivers by integrating the conventional DGPS correction with the modified FKP correction to mitigate the positioning error due to the spatial decorrelation. A real-time FKP-DGPS software was developed and several real-time tests were conducted. The test results show that the positioning accuracy of the DGPS was improved by a maximum of 40%.

/pdf/accuracy-improvement-of-dgps-for-low-cost-single-frequency-2ltt2wa62g.pdf

Accuracy Improvement of DGPS for Low-Cost Single-Frequency Receiver Using Modified Flächen Korrektur Parameter Correction

The Hatch filter is a code-smoothing technique using integrated carrier phase observations. It is an easy technique that non-experts can use to reduce receiver noise on the pseudorange. This paper suggests a new algorithm for the optimal Hatch filter whose smoothing window width varies adaptively depending on the regional, diurnal and seasonal ionospheric variation and satellite elevation angle. We consider both quiet and storm conditions of the ionosphere. Using the well-known quiet ionospheric model, a conservative boundary value for ionospheric storm and the receiver noise statistics function of the satellite elevation angle, this algorithm can mathematically solve the optimal averaging constant for each satellite in every epoch. From a 24 hr data process result and real-time experiment, we found that the position accuracy of the optimal Hatch filter is better and more robust than that of the traditional Hatch filter. The optimal Hatch filter algorithm and its results are expected to provide a new solution for a single-frequency DGPS receiver and a thorough understanding of the relationship between the position error and the averaging constant. Furthermore, a DGPS user who applies this algorithm to a low-cost single-frequency receiver can obtain a more accurate and robust position result than via the classical Hatch filter.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0373463308004694

Optimal Hatch Filter with an Adaptive Smoothing Window Width

Owing to the high demand for drone operation in high-elevation masked areas, it is necessary to develop a more effective method of transmitting and applying Satellite-Based Augmentation System (SBAS) messages for drones. This study proposes an onboard module including correction conversion, integrity information calculation, and fast initialization requests, which can enable the application of an online SBAS to drone operation. The proposed system not only improves the position accuracy with timely and proper protection levels in an open sky, but also reduces the initialization time from 70-100 s to 1 s, enabling a drone of short endurance to perform its mission successfully. In SBAS signal-denied cases, the position accuracy was improved by 40% and the uncorrected 13.4 m vertical error was reduced to 5.6 m by applying an SBAS message delivered online. The protection levels calculated with the accurate position regardless of the current location could denote the thrust level and availability of the navigation solution. The proposed system can practically solve the drawbacks of the current SBAS, considering the characteristics of the low-cost receivers on the market. Our proposed system is expected to be a useful and practical solution to integrate drones into the airspace in the near future.

https://www.mdpi.com/1424-8220/20/11/3047/pdf

An Online SBAS Service to Improve Drone Navigation Performance in High-Elevation Masked Areas

The range rate correction (RRC) was useful in reducing the latency error of pseudo-range correction (PRC), and the data baud rate. With selective availability (SA) removed, the temporal variations in the corrections are much smaller, so the issue has been raised as to whether the RRC term is still necessary. We provide results on PRC and RRC variation that account for seasonal, diurnal, and regional differences in the atmosphere and receiver noise statistics. We concluded that setting RRC to zero would help to reduce latency error, and supported this conclusion by static and dynamic tests using commercial receivers and the Radio Technical Commission for Marine Services (RTCM) correction message. The results will be used for defining differential correction messages in the new version 3 standard. The U.S. Coast Guard is conducting tests to address these issues based on results to date because of the potential benefits of reducing the data requirements for differential corrections and thus making available new services over the existing radio-beacon broadcast links. The results of this paper are expected to provide a thorough understanding of the factors affecting the temporal variations of the corrections, and will support the development of standards worldwide

Byungwoon Park

Papers

Position Accuracy Improvement by Implementing the DGNSS-CP Algorithm in Smartphones.

Accuracy Improvement of DGPS for Low-Cost Single-Frequency Receiver Using Modified Flächen Korrektur Parameter Correction

Optimal Hatch Filter with an Adaptive Smoothing Window Width

An Online SBAS Service to Improve Drone Navigation Performance in High-Elevation Masked Areas

RRC unnecessary for DGPS messages