Singular Spectrum Based Smoothing of GNSS Pseudorange Dynamics

Tahir, Muhammad; Mazher, Khurram Usman

doi:10.1109/lcomm.2016.2579624

Cited by 10 publications

(5 citation statements)

References 8 publications

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“…For ground vehicle applications, it is not feasible to use Global Positioning System (GPS) due to outage of signal in urban region, tunnels and Parking lots etc. [17,18]. Secondly, the sensors must show robust performance under all vehicle maneuvers regardless of their duration or severity.…”

Section: Introductionmentioning

confidence: 99%

A Novel Roll and Pitch Estimation Approach for a Ground Vehicle Stability Improvement Using a Low Cost IMU

Mazhar

Khan

Bhatti

et al. 2020

Sensors

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Onboard attitude estimation for a ground vehicle is persuaded by its application in active anti-roll bar design. Conventionally, the attitude estimation problem for a ground vehicle is a complex one, and computationally, its solution is very intensive. Lateral load transfer is an important parameter which should be taken in account for all roll stability control systems. This parameter is directly related to vehicle roll angle, which can be measured using devices such as dual antenna global positioning system (GPS) which is a costly technique, and this led to the current work in which we developed a simple and robust attitude estimation technique that is tested on a ground vehicle for roll mitigation. In the first phase Luenberger and Sliding mode observer is implemented using simplest roll dynamics model to measure the roll angle of a vehicle and the validation of results is carried using commercial software, CarSim® (CarSim, Ann Arbor, MI, USA). In the second phase of research, complementary and Kalman filters have been designed for attitude estimation. In the third phase, a low-cost inertial measurement unit (IMU) is mounted on a vehicle, and both the complementary filter (CF) and Kalman filter (KF) are applied independently to measure the data for both smooth and uneven terrains at four different frequencies. We compared the simulated and real-time results of roll and pitch angles obtained using the complementary and Kalman filters. Using the proposed method, the achieved root mean square error (RMSE) is less than 0.73 degree for pitch and 0.68 degree for roll, with a sample time of 2 ms. Thus, a warning signal can be generated to mitigate roll over. Hence, we claim that our proposed method can provide a low-cost solution to the roll-over problem for a road vehicle.

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Section: Introductionmentioning

confidence: 99%

A Novel Roll and Pitch Estimation Approach for a Ground Vehicle Stability Improvement Using a Low Cost IMU

Mazhar

Khan

Bhatti

et al. 2020

Sensors

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“…It has been used in many fields and applications: time‐series reconstruction [15], frequency estimation [16], time‐series forecast [17]. Many researchers have proposed SSA in the Global Navigation Satellite System (GNSS) domain for GPS time‐series analysis, inter‐annual variability, time‐varying seasonal oscillations, pseudo‐range dynamics and GPS position under different noise levels [18–22]. The simulation results demonstrate that SSA has improved accuracy and enhanced robustness against noise and propagation impairments compared to the traditional approach.…”

Section: Introductionmentioning

confidence: 99%

Implementation of storm‐time ionospheric forecasting algorithm using SSA–ANN model

Dabbakuti

Peesapati

Yarrakula

et al. 2020

IET Radar, Sonar & Navigation

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“…The global positioning system (GPS) is by far the most widely used high-precision localization method. However, it is further constrained by the non-availability of location during signal outage in dense urban areas [10,11]. Additionally, for determining sudden acceleration and braking, the GPS shows very limited success due to the insufficient update rate.…”

Section: Introductionmentioning

confidence: 99%

An Unconventional Multiple Low-Cost IMU and GPS-Integrated Kinematic Positioning and Navigation Method Based on Singer Model

Zhu

Xiao

2019

Sensors

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To release the strong dependence of the conventional inertial navigation mechanization on the a priori low-cost inertial measurement unit (IMU) error model, this research applies an unconventional multi-sensor integration strategy to integrate multiple low-cost IMUs and a global positioning system (GPS) for mass-market automotive applications. The unconventional integration strategy utilizes a basic three-dimensional (3D) kinematic trajectory model as the system model to directly estimate navigational parameters, and it allows the measurements from all of the sensors independently participating in measurement updates. However, the less complex kinematic model cannot realize smooth transitions between different motion statuses for the road vehicle with acceleration maneuvers. In this manuscript, we establish a more practical 3D kinematic trajectory model based on a “current” statistical Singer acceleration model to realize smooth transitions for the maneuvering vehicle. In addition, taking advantage of the unconventional strategy, we individually model the systematic errors of each IMU and the measurements of all sensors, in contrast to most existing approaches that adopt the common-mode errors for different sensors of the same design. A real dataset involving a GPS and multiple IMUs is processed to validate the success of the proposed algorithm model under the unconventional integration strategy.

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Singular Spectrum Based Smoothing of GNSS Pseudorange Dynamics

Cited by 10 publications

References 8 publications

A Novel Roll and Pitch Estimation Approach for a Ground Vehicle Stability Improvement Using a Low Cost IMU

A Novel Roll and Pitch Estimation Approach for a Ground Vehicle Stability Improvement Using a Low Cost IMU

Implementation of storm‐time ionospheric forecasting algorithm using SSA–ANN model

An Unconventional Multiple Low-Cost IMU and GPS-Integrated Kinematic Positioning and Navigation Method Based on Singer Model

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