GNSS Spoofing Detection based on Correlator Outputs Stationarity Monitoring

Tao, Huiqi; Li, Hong; Chu, Fengkui; Lu, Mingquan; Liu, Peng

doi:10.33012/2017.14959

Cited by 2 publications

(3 citation statements)

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“…2 The algorithm does not eliminate the right faults. 3 The algorithm failed to detect the existence of the faults (e.i. returns an empty set).…”

Section: Performance Simulationmentioning

confidence: 99%

“…To solve the minimum-integrity-risk estimate of position, it takes lots of computation. Tao et al [3] proposed a recursive RAIM method to deal with two faults. The method is based on the fact that the conventional RAIM may successfully detect one of the two faults, and by using the conventional RAIM recursively, the other fault can be alse detected.…”

Section: Introductionmentioning

confidence: 99%

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A Two-Fault Detection and Elimination Approach to the Receiver Autonomous Integrity Monitoring

2023

Preprint

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The Receiver Autonomous Integrity Monitoring (RAIM) technique is very important for the GNSS receiver to detect faulty measurement sources before they mislead the positioning solution. Based on the parity RAIM method, a simple algorithm to detect and eliminate one fault is provided. However, there is no such a simple algorithm to detect and eliminate two faults. A general approach is traversing all possible fault cases and calculate the sum of the squares of the residual errors (SSE) of each case by solving the observation equation. However, solving the observation equation takes a lot of computation. This paper proposes a detection and elimination algorithm that can deal with no more than 2 faults, based on the least-squares-residual method. The new algorithm avoids solving the observation equation for each possible fault cases, and has very low computational complexity. Simulations are done to evaluate the performance of the algorithm, and the effect of the satellite geometry conditions on the algorithm is also discussed.

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“…2 The algorithm does not eliminate the right faults. 3 The algorithm failed to detect the existence of the faults (e.i. returns an empty set).…”

Section: Performance Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Two-Fault Detection and Elimination Approach to the Receiver Autonomous Integrity Monitoring

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Most of the anti-spoofing techniques require hardware support, such as methods based on noise level monitoring [1,2] , Signal Quality Monitoring (SQM) techniques [3][4][5] , methods based on multi-correlator [6] , methods based on multi-antenna [7,8] , methods based on Inertial Navigation System (INS) [9] , and so on. Compared to these anti-spoofing methods, anti-spoofing techniques based on Receiver Autonomous Integrity Monitoring (RAIM) [10][11][12][13][14][15][16][17] are fit for most GNSS receivers, for they do not require any change to the hardware or require additional devices like INS. Therefore, RAIM is a good choice for most general receivers.…”

Section: Introductionmentioning

confidence: 99%

A GNSS Anti-Spoofing Technique Based on the Spatial Distribution Characteristic of the Residual Vectors

Wu,

Cui,

et al. 2024

Tsinghua Sci. Technol.

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Anti-spoofing is becoming a crucial technique for applications with high navigation accuracy and reliability requirements. Anti-spoofing technique based on Receiver Autonomous Integrity Monitoring (RAIM) is a good choice for most Global Navigation Satellite System (GNSS) receivers because it does not require any change to the hardware of the receiver. However, the conventional RAIM method can only detect and mitigate a single spoofing signal. Some improved RAIM methods can deal with more spoofing signals, but the computational complexity increases dramatically when the number of satellites in view increase or need additional information. This paper proposes a new RAIM method, called the SRV-RAIM method, which has a very low computation complexity regardless of the number of satellites in view and can deal with any number of spoofing signals. The key to the new method is the spatial distribution characteristic of the Satellites' Residual Vectors (SRV). In replay or generative spoofing scenarios, the pseudorange measurements of spoofing signals are consistent, the residual vectors of real satellites and those of spoofing satellites have good separation characteristics in spatial distribution. Based on this characteristic, the SRV-RAIM method is proposed, and the simulation results show that the method can separate the real signals and the spoofing signals with an average probability of 86.55% in the case of 12 visible satellites, regardless of the number of spoofing signals. Compared to the conventional traversal-RAIM method, the performance is only reduced by 3.59%, but the computational cost is reduced by 98.3%, so most of the GNSS receivers can run the SRV-RAIM algorithm in time.

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GNSS Spoofing Detection based on Correlator Outputs Stationarity Monitoring

Cited by 2 publications

References 0 publications

A Two-Fault Detection and Elimination Approach to the Receiver Autonomous Integrity Monitoring

A Two-Fault Detection and Elimination Approach to the Receiver Autonomous Integrity Monitoring

A GNSS Anti-Spoofing Technique Based on the Spatial Distribution Characteristic of the Residual Vectors

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