Published

2022-11-29

The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas

Evaluación de desempeño de la integración débilmente acoplada con el sistema de postproceso cinemático y posicionamiento preciso en áreas arborizadas y urbanas

DOI:

https://doi.org/10.15446/esrj.v26n3.100518

Keywords:

GNSS, IMU, Loosely Coupled Integration, PPP, PPK (en)
GNSS, Unidad de medición inercial, integración débilmente acoplada, posicionamiento preciso, postproceso cinemático (es)

Downloads

Authors

In this study, the authors conducted a series of test measurements in wooded and urban areas and analyzed the results for three main objectives. The first objective is to compare the execution of the Loosely Coupled (LC) and satellite-based solutions in terms of accuracy. Compared to satellite-based solutions, the findings confirmed that the LC-based solutions enhanced accuracy by 1 cm in position and 6-7 cm in height components in the wooded area. In the urban area, LC-based solutions improved the position and height accuracies up to 6 cm and 44 cm, respectively. Also, LC-based solutions bridged the gaps and created a seamless solution in which the gaps reach almost 30% in the urban area trajectory. Secondly, the authors investigated the performance of the GPS-based and GNSS-based solutions. In the wooded area, the GNSS-based solution delivered 2 cm better accuracy in both position and height components than the GPS-based solution. In the urban area, the GNSS-based solution improved the accuracies up to 8 and 36 cm in position and height components, respectively. Also, the solution availability of the GNSS-based process is 10% better than the GPS-based solution. The third objective of this study is to test the performance of the PPP and PPK-based solutions in the two test areas. PPK-based solutions outperformed only 2 cm in position and height components compared to the PPP-based in the wooded area; however, in the urban area, the PPK-based solution improved the accuracies 4-5 dm and 1.1-1.5 meter level in position and height components, respectively. These results indicate that the PPP-based solutions offer a similar level of accuracy to the PPK-based solutions in the wooded area where the satellite visibility is high throughout the trajectory. However, the PPK-based solution provided better positioning accuracies in the urban environment with limited satellite visibility.

En este estudio los autores presentan series de mediciones de prueba en áreas arborizadas y en áreas urbanas y analizan los resultados a la luz de tres objetivos. El primero de estos objetivos es comparar las soluciones de un sistema débilmente acoplado y las satelitales en términos de precisión. Los resultados muestran que las soluciones satelitales, en comparación con las soluciones del sistema débilmente acoplado, mejoraron la precisión de posición en 1 cm y entre 6 y 7 cm en componentes de altura para la zona arborizada. En el área urbana las soluciones del sistema débilmente acoplado mejoraron la precisión de la posición hasta en 6 cm y la altura hasta en 44 cm. También el sistema débilmente acoplado abarca los vacíos de información y crea una solución constante para estos vacíos, que alcanzan hasta el 30 % en la trayectoria del área urbana. Los autores investigaron el desempeño de las soluciones de GPS y de GNSS en segunda instancia. En el área arborizada la solución GNSS presentó una mejora de 2 cm en la precisión para los componentes de posición y altura sobre la solución GPS. En el área urbana la solución GNSS mejoró la precisión de posición en 8 cm y la de altura en 36 cm. También la solución de disponibilidad del proceso GNSS es 10 % mejor que la solución GPS. El tercer objetivo de este estudio es evaluar el desempeño de las soluciones de posicionamiento preciso frente a las soluciones de postproceso cinemático en las dos áreas. Las soluciones de postproceso cinemático consiguieron mejores resultados de solo 2 cm en los componentes de posición y altura frente al posicionamiento preciso  en el área arborizada; sin embargo, las soluciones de postproceso cinemático mejoraron la precisión entre 40 y 50 cm en posición y entre 1.1 y 1.5 metros en altura en el área urbana. Estos resultados indican que las soluciones de posicionamiento preciso ofrecen un nivel de precisión similar a las postproceso cinemático en el área arborizada cuando la visibilidad del satélite es alto a través de la trayectoria. Pero las soluciones provistas por el sistema de postproceso cinemático son más precisas en el ambiente urbano con condiciones de visibilidad satelital limitada.

References

Alkan, R. M., Saka, M. H., Ozulu, M., & İlçi, V. (2017). Kinematic precise point positioning using GPS and GLONASS measurements in marine environments. Measurement: Journal of the International Measurement Confederation. https://doi.org/10.1016/j.measurement.2017.05.054 DOI: https://doi.org/10.1016/j.measurement.2017.05.054

Angrisano, A., Petovello, M., & Pugliano, G. (2012). Benefits of combined GPS/GLONASS with low-cost MEMS IMUs for vehicular urban navigation. Sensors, 12, 5134–5158. https://doi.org/10.3390/s120405134 DOI: https://doi.org/10.3390/s120405134

Atia, M. M., & Waslander, S. L. (2019). Map-aided adaptive GNSS/IMU sensor fusion scheme for robust urban navigation. Measurement: Journal of the International Measurement Confederation, 131, 615–627. https://doi.org/10.1016/j.measurement.2018.08.050 DOI: https://doi.org/10.1016/j.measurement.2018.08.050

Bakuła, M., Przestrzelski, P., & Kaźmierczak, R. (2015). Reliable Technology of Centimeter GPS/GLONASS Surveying in Forest Environments. IEEE Transactions on Geoscience and Remote Sensing, 53(2), 1029–1038. https://doi.org/10.1109/TGRS.2014.2332372 DOI: https://doi.org/10.1109/TGRS.2014.2332372

Bhatti, U. I., Ochieng, W. Y., & Feng, S. (2007). Integrity of an integrated GPS/INS system in the presence of slowly growing errors. Part I: A critical review. GPS Solutions. https://doi.org/10.1007/s10291-006-0048-2 DOI: https://doi.org/10.1007/s10291-006-0048-2

Brovelli, M. A., Minghini, M., & Zamboni, G. (2016). Public participation in GIS via mobile applications. ISPRS Journal of Photogrammetry and Remote Sensing, 114, 306–315. https://doi.org/10.1016/j.isprsjprs.2015.04.002 DOI: https://doi.org/10.1016/j.isprsjprs.2015.04.002

Chiang, K. W., Duong, T.T., Liao, J. K. (2013). The Performance Analysis of a Real-Time Integrated INS/GPS Vehicle Navigation System with Abnormal GPS Measurement Elimination. Sensors, 13, 10599–10622. DOI: https://doi.org/10.3390/s130810599

Choy, S., Zhang, S., Lahaye, F., & Héroux, P. (2013). A comparison between GPS-only and combined GPS+GLONASS Precise Point Positioning. Journal of Spatial Science, 58(2), 169–190. https://doi.org/10.1080/14498596.2013.808164 DOI: https://doi.org/10.1080/14498596.2013.808164

El-Mowafy, A. (2011). Analysis of web-based GNSS post-processing services for static and kinematic positioning using short data spans. Survey Review, 43(322), 535–549. https://doi.org/10.1179/003962611X13117748892074 DOI: https://doi.org/10.1179/003962611X13117748892074

Eling, C., Wieland, M., Hess, C., Klingbeil, L., & Kuhlmann, H. (2015). Development and evaluation of a UAV based mapping system for remote sensing and surveying applications. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 233–239. https://doi.org/10.5194/isprsarchives-XL-1-W4-233-2015 DOI: https://doi.org/10.5194/isprsarchives-XL-1-W4-233-2015

Elliott, K., & Hegarty, C. (2017). Understanding GPS/GNSS Principles and Applications. Norwood, MA: Artech House. ISBN-13, 971–978.

Erol, S., Alkan, R. M., Ozulu, M., & İlçi, V. (2020). Performance analysis of real-time and post-mission kinematic precise point positioning in marine environments. Geodesy and Geodynamics, 11(6), 401–410. https://doi.org/10.1016/j.geog.2020.09.002 DOI: https://doi.org/10.1016/j.geog.2020.09.002

Falco, G., Einicke, G. A., Malos, J. T., Dovis, F. (2012). Performance analysis of constrained loosely coupled GPS/INS integration solutions. Sensors, 12, 15983–16007. DOI: https://doi.org/10.3390/s121115983

Falco, G., Pini, M., & Marucco, G. (2017). Loose and Tight GNSS/INS Integrations: Comparison of Performance Assessed in Real Urban Scenarios. Sensors, 17(2), 255. https://doi.org/10.3390/s17020255 DOI: https://doi.org/10.3390/s17020255

Furones, A. M., Julián, A. B. A., Valero, J. L. B., & Sanmartin, M. (2012). Kinematic GNSS-PPP results from various software packages and raw data configurations. Scientific Research and Essays, 7, 419–431.

Gao, G., & Lachapelle, G. (2008). A Novel Architecture for Ultra-Tight HSGPS-INS Integration. Journal of Global Positioning Systems, 7(1), 46–61. https://doi.org/10.5081/jgps.7.1.46 DOI: https://doi.org/10.5081/jgps.7.1.46

Godha, S., & Cannon, M. E. (2007). GPS/MEMS INS integrated system for navigation in urban areas. GPS Solutions, 11, 193–203. https://doi.org/10.1007/s10291-006-0050-8 DOI: https://doi.org/10.1007/s10291-006-0050-8

Hol, J. D. (2011). Sensor fusion and calibration of inertial sensors, vision, ultra-wideband and GPS. [Doctoral dissertation, Linköping University Electronic Press].

Ilci, V., & Toth, C. (2020). High definition 3D map creation using GNSS/IMU/LiDAR sensor integration to support autonomous vehicle navigation. Sensors, 20(3). https://doi.org/10.3390/s20030899 DOI: https://doi.org/10.3390/s20030899

Jiang, W., Li, Y., & Rizos, C. (2015). Locata-based precise point positioning for kinematic maritime applications. GPS Solutions, 19, 117–128. https://doi.org/10.1007/s10291-014-0373-9 DOI: https://doi.org/10.1007/s10291-014-0373-9

Jo, K., & Sunwoo, M. (2014). Generation of a precise roadway map for autonomous cars. IEEE Transactions on Intelligent Transportation Systems, 15(3), 925–937. https://doi.org/10.1109/TITS.2013.2291395 DOI: https://doi.org/10.1109/TITS.2013.2291395

Kuutti, S., Fallah, S., Katsaros, K., Dianati, M., Mccullough, F., & Mouzakitis, A. (2018). A Survey of the State-of-the-Art Localization Techniques and Their Potentials for Autonomous Vehicle Applications. IEEE Internet of Things Journal, 5(2), 829–846. https://doi.org/10.1109/JIOT.2018.2812300 DOI: https://doi.org/10.1109/JIOT.2018.2812300

Li, T., Zhang, H., Gao, Z., Chen, Q., & Niu, X. (2018). High-accuracy positioning in urban environments using single-frequency multi-GNSS RTK/MEMSIMU integration. Remote Sensing, 10(205), 1–21. https://doi.org/10.3390/rs10020205 DOI: https://doi.org/10.3390/rs10020205

Li, T., Zhang, H., Gao, Z., Niu, X., & El-sheimy, N. (2019). Tight Fusion of a Monocular Camera, MEMS-IMU, and Single-Frequency Multi-GNSS RTK for Precise Navigation in GNSS-Challenged Environments. Remote Sensing, 11(6), 610. https://doi.org/10.3390/rs11060610 DOI: https://doi.org/10.3390/rs11060610

Misra, P., & Enge, P. (2011). Global positioning system: Signals, Measurements, and Performance. Ganga-Jamuna Press.

Nocerino, E., Menna, F., Remondino, F., Toschi, I., & Rodríguez-Gonzálvez, P. (2017). Investigation of indoor and outdoor performance of two portable mobile mapping systems. Videometrics, Range Imaging, and Applications XIV, 1–15. https://doi.org/10.1117/12.2270761 DOI: https://doi.org/10.1117/12.2270761

Ocalan, T. (2016). Accuracy Assessment of GPS Precise Point Positioning (PPP) Technique using Different Web-Based Online Services in a Forest Environment. Sumarski List, 7-8, 357-368. https://doi.org/10.31298/sl.140.7-8.4 DOI: https://doi.org/10.31298/sl.140.7-8.4

Ocalan, T., Erdogan, B., Tunalioglu, N., & Durdag, U. M. (2016). Accuracy Investigation of PPP Method Versus Relative Positioning Using Different Satellite Ephemerides Products Near/Under Forest Environment. Earth Sciences Research Journal, 20(4), D1-D9. https://doi.org/10.15446/esrj.v20n4.59496) DOI: https://doi.org/10.15446/esrj.v20n4.59496

Otegui, J., Bahillo, A., Lopetegi, I., & Díez, L. E. (2021). Performance Evaluation of Different Grade IMUs for Diagnosis Applications in Land Vehicular Multi-Sensor Architectures. IEEE Sensors Journal, 21(3), 2658–2668. https://doi.org/10.1109/JSEN.2020.3023427 DOI: https://doi.org/10.1109/JSEN.2020.3023427

Paziewski, J., Sieradzki, R., & Baryla, R. (2018). Multi-GNSS high-rate RTK, PPP and novel direct phase observation processing method: application to precise dynamic displacement detection. Measurement Science and Technology, 29(3), 35002. https://doi.org/10.1088/1361-6501/aa9ec2 DOI: https://doi.org/10.1088/1361-6501/aa9ec2

Petovello, M. G. (2003). Real-time integration of a tactical-grade IMU and GPS for high-accuracy positioning and navigation (Unpublished doctoral thesis). University of Calgary, Calgary, AB. DOI:10.11575/PRISM/23031.

Qin, Y., Zhang, H. Y., & Wang, S. H. (2015). Principles of Kalman Filter and Integrated Navigation. Xi’an, China:Northwestern Polytechnical Univ. Press

Robustelli, U., & Pugliano, G. (2019). Characterization of dual frequency GNSS observations from Xiaomi Mi 8 smartphone in absence of duty cycle. AIP Conference Proceedings 2116, 280005. https://doi.org/https://doi.org/10.1063/1.5114288 DOI: https://doi.org/10.1063/1.5114288

Salytcheva, A. O. (2004). Medium accuracy INS/GPS integration in various GPS environments. [MS Thesis, University of Calgary, Alberta].

Shen, N., Chen, L., Liu, J., Wang, L., Tao, T., Wu, D., & Chen, R. (2019). A review of global navigation satellite system (GNSS)-based dynamic monitoring technologies for structural health monitoring. Remote Sensing, 11(9), 1001. DOI: https://doi.org/10.3390/rs11091001

Solimeno, A. (2007). Low-Cost INS/GPS Data Fusion with Extended Kalman Filter for Airborne Applications. [MS. Thesis, Universidade Técnica de Lisboa]

Specht, M., Specht, C., Dąbrowski, P., Czaplewski, K., Smolarek, L., & Lewicka, O. (2020). Road tests of the positioning accuracy of INS/GNSS systems based on MEMS technology for navigating railway vehicles. Energies, 13(17). https://doi.org/10.3390/en13174463 DOI: https://doi.org/10.3390/en13174463

Vana, S., & Bisnath, S. (2020). Enhancing Navigation in Difficult Environments with Low-Cost, Dual-Frequency GNSS PPP and MEMS IMU. In: International Association of Geodesy Symposia. Springer, Berlin, Heidelberg. https://doi.org/10.1007/1345_2020_118 DOI: https://doi.org/10.1007/1345_2020_118

Vu, A., Farrell, J. A., & Barth, M. (2013). Centimeter-accuracy smoothed vehicle trajectory estimation. IEEE Intelligent Transportation Systems Magazine, 5(4), 121–136. https://doi.org/10.1109/MITS.2013.2281009 DOI: https://doi.org/10.1109/MITS.2013.2281009

Xu, R., Ding, M., Qi, Y., Yue, S., & Liu, J. (2018). Performance Analysis of GNSS/INS Loosely Coupled Integration Systems under Spoofing Attacks. Sensors, 18(12). https://doi.org/10.3390/s18124108 DOI: https://doi.org/10.3390/s18124108

Yigit, C. O., Gikas, V., Alcay, S., & Ceylan, A. (2014). Performance evaluation of short to long term GPS, GLONASS and GPS/GLONASS postprocessed PPP. Survey Review, 46(336), 155–166. https://doi.org/10.1179/1752270613Y.0000000068 DOI: https://doi.org/10.1179/1752270613Y.0000000068

Zhang, Q., Niu, X., & Shi, C. (2020). Impact Assessment of Various IMU Error Sources on the Relative Accuracy of the GNSS/INS Systems. IEEE Sensors Journal, 20(9), 5026–5038. https://doi.org/10.1109/JSEN.2020.2966379 DOI: https://doi.org/10.1109/JSEN.2020.2966379

Zhao, L., Qiu, H., & Feng, Y. (2016). Analysis of a robust Kalman filter in loosely coupled GPS/INS navigation system. Measurement: Journal of the International Measurement Confederation, 80, 138–147. https://doi.org/10.1016/j.measurement.2015.11.008 DOI: https://doi.org/10.1016/j.measurement.2015.11.008

Zhao, S., Chen, Y., & Farrell, J. A. (2016). High-Precision Vehicle Navigation in Urban Environments Using an MEM’s IMU and Single-Frequency GPS Receiver. IEEE Transactions on Intelligent Transportation Systems, 17(10), 2854–2867. https://doi.org/10.1109/TITS.2016.2529000 DOI: https://doi.org/10.1109/TITS.2016.2529000

How to Cite

APA

Gurturk, M. and Ilci, V. (2022). The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas. Earth Sciences Research Journal, 26(3), 211–220. https://doi.org/10.15446/esrj.v26n3.100518

ACM

[1]
Gurturk, M. and Ilci, V. 2022. The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas. Earth Sciences Research Journal. 26, 3 (Nov. 2022), 211–220. DOI:https://doi.org/10.15446/esrj.v26n3.100518.

ACS

(1)
Gurturk, M.; Ilci, V. The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas. Earth sci. res. j. 2022, 26, 211-220.

ABNT

GURTURK, M.; ILCI, V. The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas. Earth Sciences Research Journal, [S. l.], v. 26, n. 3, p. 211–220, 2022. DOI: 10.15446/esrj.v26n3.100518. Disponível em: https://revistas.unal.edu.co/index.php/esrj/article/view/100518. Acesso em: 7 mar. 2025.

Chicago

Gurturk, Mert, and Veli Ilci. 2022. “The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas”. Earth Sciences Research Journal 26 (3):211-20. https://doi.org/10.15446/esrj.v26n3.100518.

Harvard

Gurturk, M. and Ilci, V. (2022) “The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas”, Earth Sciences Research Journal, 26(3), pp. 211–220. doi: 10.15446/esrj.v26n3.100518.

IEEE

[1]
M. Gurturk and V. Ilci, “The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas”, Earth sci. res. j., vol. 26, no. 3, pp. 211–220, Nov. 2022.

MLA

Gurturk, M., and V. Ilci. “The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas”. Earth Sciences Research Journal, vol. 26, no. 3, Nov. 2022, pp. 211-20, doi:10.15446/esrj.v26n3.100518.

Turabian

Gurturk, Mert, and Veli Ilci. “The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas”. Earth Sciences Research Journal 26, no. 3 (November 29, 2022): 211–220. Accessed March 7, 2025. https://revistas.unal.edu.co/index.php/esrj/article/view/100518.

Vancouver

1.
Gurturk M, Ilci V. The performance evaluation of PPK and PPP-based Loosely Coupled integration in wooded and urban areas. Earth sci. res. j. [Internet]. 2022 Nov. 29 [cited 2025 Mar. 7];26(3):211-20. Available from: https://revistas.unal.edu.co/index.php/esrj/article/view/100518

Download Citation

CrossRef Cited-by

CrossRef citations2

1. Simla Özbayrak, Veli İlçi. (2024). Visual-SLAM Based 3-Dimensional Modelling of Indoor Environment. International Journal of Engineering and Geosciences, https://doi.org/10.26833/ijeg.1459216.

2. Aleyna Başaran, Veli İlçi. (2025). Accuracy Evaluation of LiDAR-SLAM Based 2-Dimensional Modelling for Indoor Environment: A Case Study. International Journal of Engineering and Geosciences, 10(1), p.74. https://doi.org/10.26833/ijeg.1519533.

Dimensions

PlumX

Plum Print visual indicator of research metrics
  • Citations
  • Scopus - Citation Indexes: 2
  • Captures
  • Mendeley - Readers: 7
  • Mendeley - Readers: 2
  • Mentions
  • News: 1
-
see details

Article abstract page views

219

Downloads

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Earth Sciences Research Journal holds a Creative Commons Attribution license. 

You are free to:

Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.