Design and Performance Evaluation of an Adaptive Hybrid Coherent and Non-coherent GNSS Vector Tracking Loop

Wu, Mouyan; Ding, Jicheng; Zhao, Lin; Kang, Yingyao; Luo, Zhibin

doi:10.33012/2017.14971

Cited by 3 publications

(9 citation statements)

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“…The institute of geodesy and geophysics (IGG) III function of the adaptive factor

is obtained by [ 28 , 29 ]:

where

is the standardized predicted residual of measurement:

; and

is the standard deviation of measurement noise.

can reflect the measurement accuracy to some extent.…”

Section: Design Of the Grid Sins/dvl Integrated Navigation Algoritmentioning

confidence: 99%

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A Novel Grid SINS/DVL Integrated Navigation Algorithm for Marine Application

Kang

Zhao

Cheng

et al. 2018

Sensors

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Integrated navigation algorithms under the grid frame have been proposed based on the Kalman filter (KF) to solve the problem of navigation in some special regions. However, in the existing study of grid strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) integrated navigation algorithms, the Earth models of the filter dynamic model and the SINS mechanization are not unified. Besides, traditional integrated systems with the KF based correction scheme are susceptible to measurement errors, which would decrease the accuracy and robustness of the system. In this paper, an adaptive robust Kalman filter (ARKF) based hybrid-correction grid SINS/DVL integrated navigation algorithm is designed with the unified reference ellipsoid Earth model to improve the navigation accuracy in middle-high latitude regions for marine application. Firstly, to unify the Earth models, the mechanization of grid SINS is introduced and the error equations are derived based on the same reference ellipsoid Earth model. Then, a more accurate grid SINS/DVL filter model is designed according to the new error equations. Finally, a hybrid-correction scheme based on the ARKF is proposed to resist the effect of measurement errors. Simulation and experiment results show that, compared with the traditional algorithms, the proposed navigation algorithm can effectively improve the navigation performance in middle-high latitude regions by the unified Earth models and the ARKF based hybrid-correction scheme.

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“…The institute of geodesy and geophysics (IGG) III function of the adaptive factor

is obtained by [ 28 , 29 ]:

where

is the standardized predicted residual of measurement:

; and

is the standard deviation of measurement noise.

can reflect the measurement accuracy to some extent.…”

Section: Design Of the Grid Sins/dvl Integrated Navigation Algoritmentioning

confidence: 99%

“…The equivalent covariance of the measurement noise is related to the DVL measurement, and the equivalent covariance

can be obtained by [ 28 , 29 ]:

…”

Section: Design Of the Grid Sins/dvl Integrated Navigation Algoritmentioning

confidence: 99%

A Novel Grid SINS/DVL Integrated Navigation Algorithm for Marine Application

Kang

Zhao

Cheng

et al. 2018

Sensors

Self Cite

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“…Thus, a Jacobian matrix is constructed to accomplish the correction in EKF. Detailed discussion of Jacobian matrix construction for coherent pre-filter is provided in a great deal of literature, and will not be shown here [ 13 , 17 , 19 , 20 ]. The observation noise variance of coherent pre-filter can be calculated as Equation (5), as long as the C / N 0 estimation is available.…”

Section: Tracking Error Estimationmentioning

confidence: 99%

“…The coherent pre-filter and non-coherent pre-filter have complementary characteristics, which can be used to design a hybrid pre-filter structure [ 18 ]. An adaptive hybrid coherent/non-coherent GNSS vector tracking loop has been proposed to adaptively switch the pre-filter type that is working in tracking channel according to the signal strength [ 19 ]. The coherent pre-filter works in strong signal condition, while the non-coherent pre-filter works in weak signal condition.…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers

Luo

Ding

Zhao

et al. 2017

Sensors

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Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration—which are the basis of tracking error estimation—are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (−0.25 cycle, 0.25 cycle) to (−0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz ∪ (26, 50) dB-Hz.

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“…Wu et al combined the advantages of coherent and incoherent structures and proposed an adaptive hybrid coherent and incoherent GNSS VTL. This tracking loop was capable of achieving accurate and robust tracking performance in GNSS-challenged environments [24,25]. Luo et al conducted an extensive analysis of both coherent and non-coherent integrations and proposed an enhanced design for the non-coherent pre-filter.…”

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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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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Design and Performance Evaluation of an Adaptive Hybrid Coherent and Non-coherent GNSS Vector Tracking Loop

Cited by 3 publications

References 0 publications

A Novel Grid SINS/DVL Integrated Navigation Algorithm for Marine Application

A Novel Grid SINS/DVL Integrated Navigation Algorithm for Marine Application

An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers

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

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