Fully Adaptive Smart Vector tracking of Weak GPS Signals

Farhad, M. A.; Mosavi, Mohammad Reza; Abedi, Ali

doi:10.1007/s13369-020-05172-4

Cited by 9 publications

(4 citation statements)

References 23 publications

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“…According to (23), r k is the detection value that utilises the information of all components of V k , and V k represents the difference between the actual value of Z k and the predicted value, so r k can represent the cumulative errors of all received signals. Since Z k is the pseudo-range error vector converted from code phase errors, and the appearance of either the MP signal or NLOS signal result in code phase deviation, Z k can be used to indicate whether there are MP signals and NLOS signals.…”

Section: F I G U R E 1 1 Innovation Values Of Institute Of Geodesy An...mentioning

confidence: 99%

“…Although there have been a lot of studies on multipath mitigation and multipath detection, most of them focus on the conventional receiver using scalar tracking. Vector tracking which is rising in recent years has the advantages of tracking weak signals [23], bridging momentary signal outage [24], and suppressing multipath interference [25,26] etc. However, there are few studies on multipath detection for vector tracking loop (VTL) at present.…”

Section: Introductionmentioning

confidence: 99%

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Robust estimation‐based multipath detection for vector tracking loop

Zou

Kong

2023

IET Radar Sonar & Navi

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Multipath interference in cities has always been one of the main problems leading to abnormal positioning results of a global navigation satellite system. Vector tracking is superior to conventional scalar tracking in the ability of mitigating multipath interference. However, due to the special sharing structure, fault propagation which easily occurs in the vector tracking loop leads to false alarms of normal satellite signals during multipath detection. To solve this problem, a fault‐tolerant algorithm based on robust estimation is applied to suppress fault propagation. Meanwhile, in order to improve the ability of detecting multiple short delayed multipath signals, chi‐square detection is proposed to be used before applying the fault‐tolerant algorithm. By taking advantage of the characteristic that the occurrence of multipath signals will cause significant deviation of code phase errors, the mean value of code phase errors is used as the detection metric. Both simulation test and field experiment are carried out to verify the detection performance. Experimental results show that the proposed algorithm can effectively prevent fault propagation and solve the problem of false positives of normal satellite signals. As a result, not only multipath signals are detected more accurately, but also more accurate navigation solution is obtained.

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Section: F I G U R E 1 1 Innovation Values Of Institute Of Geodesy An...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust estimation‐based multipath detection for vector tracking loop

Zou

Kong

2023

IET Radar Sonar & Navi

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“…Another example is the use of a frequency lock loop (FLL) to assist the phase lock loop (PLL) in improving the carrier tracking loop's ability to track weak signals [11]. For navigation processors, researchers have proposed improved navigation filters to adaptively adjust the system noise, measurement noise, and covariance matrix of the state estimation, thus mitigating the effects of system and measurement model nonlinearities on the loop tracking performance [12,13]. To address the impact of anomalous measurements on navigation filters, some researchers have identified and eliminated anomalous measurements through detection algorithms or added measurement noise to reduce the filter gain when anomalous measurements occur [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

A robust GNSS sensors in presence of signal blockage for USV application

Liu,

Huang,

et al. 2023

Meas. Sci. Technol.

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Unmanned surface vehicle (USV) can navigate autonomously via the global navigation satellite system (GNSS). However, the traditional GNSS scalar tracking loop easily loses lock in low carrier-to-noise ratio (CNR) situations, such as signal occlusion and weak signals. Meanwhile, an increase in the carrier/code phase error leads to an increase in the measurement error of the navigation filter, which decreases the accuracy of the position estimation. To solve this problem, this paper proposes a carrier and code tracking structure based on a forward and backward Kalman filter to dynamically adjust the gain of the vector tracking loop. The carrier and code phase errors calculated by the loop discriminators were linearly transformed into pseudo-range rate and pseudo-range errors after filtering and smoothing, which were used as the measurements of the navigation filter. The signal CNR was used to adaptively adjust the measurement noise covariance matrix of the loop filters. The field tests used a commercial receiver’s navigation solution as the reference. In the stationary test, the proposed structure reduced the localization error by 44.3% compared with the traditional methods. In kinematic experiments, the proposed structure reduced the carrier and code phase errors in a harsh signal environment and improved the positioning accuracy at the source. The test results demonstrate that the proposed GNSS tracking method can provide a possible solution for the development of navigation systems for USV.

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“…In [12], a GPS receiver delivers data to an extended Kalman filter (EKF) to track the position of a car as it travels along a defined route. The EKF alone is not good at estimating the position of the vehicle when the GPS receives poor signals from the satellites.…”

Section: Introductionmentioning

confidence: 99%

GPS Data Correction Based on Fuzzy Logic for Tracking Land Vehicles

et al. 2021

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GPS sensors are widely used to know a vehicle’s location and to track its route. Although GPS sensor technology is advancing, they present systematic failures depending on the environmental conditions to which they are subjected. To tackle this problem, we propose an intelligent system based on fuzzy logic, which takes the information from the sensors and correct the vehicle’s absolute position according to its latitude and longitude. This correction is performed by two fuzzy systems, one to correct the latitude and the other to correct the longitude, which are trained using the MATLAB ANFIS tool. The positioning correction system is trained and tested with two different datasets. One of them collected with a Pmod GPS sensor and the other a public dataset, which was taken from routes in Brazil. To compare our proposal, an unscented Kalman filter (UKF) was implemented. The main finding is that the proposed fuzzy systems achieve a performance of 69.2% higher than the UKF. Furthermore, fuzzy systems are suitable to implement in an embedded system such as the Raspberry Pi 4. Another finding is that the logical operations facilitate the creation of non-linear functions because of the ‘if else’ structure. Finally, the existence justification of each fuzzy system section is easy to understand.

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Fully Adaptive Smart Vector tracking of Weak GPS Signals

Cited by 9 publications

References 23 publications

Robust estimation‐based multipath detection for vector tracking loop

Robust estimation‐based multipath detection for vector tracking loop

A robust GNSS sensors in presence of signal blockage for USV application

GPS Data Correction Based on Fuzzy Logic for Tracking Land Vehicles

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