Combating Single-Frequency Jamming through a Multi-Frequency, Multi-Constellation Software Receiver: A Case Study for Maritime Navigation in the Gulf of Finland

Islam, Saiful; Bhuiyan, Mohammad Zahidul H.; Thombre, Sarang; Kaasalainen, Sanna

doi:10.3390/s22062294

Cited by 11 publications

(8 citation statements)

References 14 publications

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“…. (6) In practical computations, the optimal state estimation value can be obtained by setting ∂J L (X(k))/∂X(k) = 0 and utilizing the fixed-point iteration method, which maximally suppresses non-Gaussian outliers in the measurement vector [46].…”

Section: Mee Criterionmentioning

confidence: 99%

“…However, in narrow waterways and harbor areas, GNSS signals are subject to interference or obstruction by structures such as bridges, buildings, and harbor equipment, which do not satisfy the requirements of USV for GNSS signal robustness and accuracy [4][5][6]. Therefore, there is a need to enhance the tracking capability and robustness of GNSS receivers utilized in USVs to meet escalating navigation performance demands.…”

Section: Introductionmentioning

confidence: 99%

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Enhancing USVs navigation based on minimum error entropy of GPS vector tracking

Liu,

Chen,

et al. 2024

Meas. Sci. Technol.

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In recent years, Unmanned Surface Vehicles (USVs) have increasingly been used for river monitoring and hydrological surveys. USVs rely on global navigation satellite systems (GNSS) for navigation. However, signal blocking can cause the traditional GNSS vector tracking loop to increase the code phase and carrier frequency errors, leading to higher positioning errors that do not meet USVs’ requirements. To address this problem, we propose a vector tracking method based on the minimum error entropy (MEE) in the signal tracking module. The minimum error entropy Kalman filter (MEEKF) is adopted as the loop filter to mitigate code phase and carrier frequency errors, reduce non-Gaussian noise and random errors generated by signal blocking, and enhance the positioning accuracy and robustness of USV navigation. The measurement noise covariance of the loop filter was adjusted adaptively using the signal carrier-to-noise ratio (CNR). A field experiment was conducted using a commercial GNSS receiver as reference. The results demonstrate a 19.3% improvement in positioning accuracy compared with the traditional method in an open environment. Moreover, the proposed method maintains stable operation and achieves a 79.4% improvement in positioning accuracy during signal blocking. This novel algorithm offers a new concept for USV navigation systems to cope with signal blocking.

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Section: Mee Criterionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhancing USVs navigation based on minimum error entropy of GPS vector tracking

Liu,

Chen,

et al. 2024

Meas. Sci. Technol.

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“…GNSS SDRs also offer greater flexibility and customization as compared to traditional GNSS receivers [2,5] by allowing developers to tailor GNSS solutions to specific requirements and integrate them into a wide range of devices and systems. GNSS SDRs also serve as a valuable tool for investigation, reproduction, validation and cross-verification of GNSS signals and by providing open platforms to explore and share raw recorded GNSS in-phase/quadrature (I/Q) datasets [3,4,7,8]. These features enable GNSS SDRs to offer flexibility, adaptability, customization and interoperability for innovation and research over hardware receivers.…”

Section: Introductionmentioning

confidence: 99%

An Enhanced FGI-GSRx Software-Defined Receiver for the Execution of Long Datasets

Liaquat,

Bhuiyan,

Islam

et al. 2024

Preprint

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The Global Navigation Satellite Systems (GNSS) software-defined receivers offer greater flexibility, cost-effectiveness, customization, and integration capabilities compared to traditional hardware-based receivers, making them essential for a wide range of applications. The continuous evolution of GNSS research and the availability of new features require these software-defined receivers to upgrade continuously to facilitate the latest requirements. The Finnish Geospatial Research Institute (FGI) has been supporting the GNSS research community with its open-source implementations, such as a MATLAB-based GNSS software-defined receiver ’FGI-GSRx’ and a Python-based implementation ’FGI-OSNMA’ for utilizing Galileo’s Open Service Navigation Message Authentication (OSNMA). In this context, longer datasets are crucial for GNSS software-defined receivers to support adaptation, optimization and facilitate testing to investigate and develop future-proof receiver capabilities. In this paper we present an updated version of FGI-GSRx, namely FGI-GSRx-v2.0.0, which is also available as an open-source resource for the research community. FGI-GSRx-v2.0.0 offers improved performance as compared to its previous version, especially for the execution of long datasets. This is carried out by optimizing the receiver’s functionality and offering a newly added parallel processing feature to ensure faster capabilities to process the raw GNSS data. This paper also presents an analysis of some key design aspects of previous and current versions of FGI-GSRx for a better insight into the receiver’s functionalities. The results show that FGI-GSRx-v2.0.0 offers about 40% run time execution improvement over FGI-GSRx-v1.0.0 in case of sequential processing mode and about 59% improvement in case of parallel processing mode with 17 GNSS satellites from GPS and Galileo. In addition, an attempt is made to execute v2.0.0 with MATLAB’s own parallel computing toolbox. A detail performance comparison reveals an improvement of about 43% in execution time over v2.0.0 parallel processing mode for the same GNSS scenario.

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“…Research addressing the three aspects mentioned above will greatly promote the application of real-time high-precision GNSS positioning in the mass market and advance autonomous driving and urban digitization. This Special Issue, entitled “ Advances in GNSS Positioning and GNSS Remote Sensing” in Sensors ( , (accessed on 2 February 2024)), attracted 10 articles [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ] on new GNSS techniques for ionospheric studies, the impact of space weather on GNSS and methods for precise navigation.…”

mentioning

confidence: 99%

“…In their study, Islam et al [ 14 ] suggest the utilization of a jamming detector with multi-frequency and multi-constellation software that was able to define the GNSS receiver for Maritime Navigation in the Gulf of Finland. GPS-L5-only, Galileo-E5a-only, and Galileo-E5b-only signals and their multi-GNSS combination positioning results revealed that the Galileo-E5 and E5b signals performed better than other frequency bands in a maritime operational environment.…”

mentioning

confidence: 99%