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Aiming at the initial alignment problem of low-cost INS/GNSS in the case of moving base, this paper proposes a set of GNSS-assisted low-cost INS combined navigation initial alignment schemes, which is designed, optimized, and verified. Firstly, this paper analyses the impact of accelerometer zero bias on the accuracy of multi-vector construction and proposes an improved vector construction method, which approximates the suppression of the error caused by the accelerometer zero bias accumulating over time by vector subtraction instead of sliding window integration and also overcomes the impact of the OBA algorithm’s computational increase and memory occupation caused by the fact that the sliding window integration needs to store and integrate the data in the window. Secondly, this paper also designs an improved Kalman filter model to reconstruct the state equation and measurement equation of the system, which can more accurately estimate the zero bias of the gyroscope online and compensate for the misalignment angle of the carrier system by using the velocity and position information of the GNSS, eliminating the influence of the zero bias of the gyroscope on the accuracy of the multi-vector, and improving the accuracy of the initial alignment of the moving base and the robustness of the algorithm. Finally, the algorithm proposed in this paper and other algorithms are compared and analyzed in simulation and vehicle test experiments. The simulation experiments verify the feasibility of the initial alignment method proposed in this paper; the vehicle test experiments use vector subtraction and sliding window integration to construct the multivector, and then estimate the zero bias of the gyroscope and compensate for the misalignment angle of the carrier system by using Kalman filtering model proposed in this paper and other Kalman filtering models, respectively. The measured results show that the proposed method has better alignment accuracy and algorithm robustness than the existing Optimization-based alignment and their improvement algorithms for the moving base of low-cost INS/GNSS combined navigation.

Alignment technology plays an important role in navigation, and is used extensively throughout military and civilian applications. However, the existing in-flight alignment methods cannot be applied to the low-cost based strap-down inertial navigation system/global positioning system integrated navigation system, used in short-endurance and high-speed rotation flight bodies, since they cannot quickly obtain alignment results to meet the accuracy requirements of a flight body with special movement characteristics of short-endurance and high-speed rotation. In this paper, in order to solve this challenging problem of alignment for flight body with short-endurance and high-speed rotation, a fast in-flight alignment method based on the Lie group is proposed. First, an in-flight alignment model based on vector observations was established by using the Lie group. Second, addressing the problem that the alignment accuracy is greatly affected by the low-cost inertial sensor bias, an improved unscented Kalman filter was constructed in the Lie group on the basis of fully considering the characteristics of the system equations to estimate and feedback the correlated errors. Finally, a trajectory simulation of high-speed flight body and field semi-physical test was carried out to evaluate the proposed method. Evaluation of the system performance in comparison with existing state-of-the-art methods indicated that the proposed in-flight alignment method has better alignment accuracy and faster alignment velocity for a low-cost strap-down inertial navigation system/global positioning system integrated navigation system. [ABSTRACT FROM AUTHOR]

Alignment technology plays an important role in navigation, and is used extensively throughout military and civilian applications. However, the existing in-flight alignment methods cannot be applied to the low-cost based strap-down inertial navigation system/global positioning system integrated navigation system, used in short-endurance and high-speed rotation flight bodies, since they cannot quickly obtain alignment results to meet the accuracy requirements of a flight body with special movement characteristics of short-endurance and high-speed rotation. In this paper, in order to solve this challenging problem of alignment for flight body with short-endurance and high-speed rotation, a fast in-flight alignment method based on the Lie group is proposed. First, an in-flight alignment model based on vector observations was established by using the Lie group. Second, addressing the problem that the alignment accuracy is greatly affected by the low-cost inertial sensor bias, an improved unscented Kalman filter was constructed in the Lie group on the basis of fully considering the characteristics of the system equations to estimate and feedback the correlated errors. Finally, a trajectory simulation of high-speed flight body and field semi-physical test was carried out to evaluate the proposed method. Evaluation of the system performance in comparison with existing state-of-the-art methods indicated that the proposed in-flight alignment method has better alignment accuracy and faster alignment velocity for a low-cost strap-down inertial navigation system/global positioning system integrated navigation system.

To solve the low accuracy and poor reliability of the alignment of low-end micro-electro-mechanical systems (MEMS) inertial measurement units (IMU) in low dynamic applications such as precision agriculture, this paper proposes a velocity-based optimization-based alignment (VBOBA) method using the assistance of GNSS velocity. Essentially, the proposed VBOBA method is a kind of attitude determination algorithm based on multiple velocity vector observations. Furthermore, the global perspective of observability analysis is utilized to investigate the influence of vehicle maneuvers on the estimation of the heading angle, which reveals that the proposed VBOBA method only requires velocity vectors, while the existing acceleration-based optimization-based alignment (ABOBA) method requires acceleration changes to estimate the heading angle. The results of simulation and tractor tests show that the alignment error of the heading angle provided by the proposed VBOBA method can be reduced to 4° in 60s under low dynamic conditions with about 1 m/s for the industrial grade MEMS IMU (e.g., ADIS16460). The proposed VBOBA method can serve as an effective in-motion alignment for low-end and low dynamic applications. [ABSTRACT FROM AUTHOR]

The optimization-based alignment (OBA) methods, which are implemented by the optimal attitude estimation using vector observations—also called double-vectors—have proven to be effective at solving the in-flight alignment (IFA) problem. However, the traditional OBA methods are not applicable for the low-cost strap-down inertial navigation system (SINS) since the error of double-vectors will be accumulated over time due to the substantial drift of micro-electronic- mechanical system (MEMS) gyroscope. Moreover, the existing optimal estimation method is subject to a large computation burden, which results in a low alignment speed. To address these issues, in this article we propose a new fast IFA method based on modified double-vectors construction and the gradient descent method. To be specific, the modified construction method is implemented by reducing the integration interval and identifying the gyroscope bias during the construction procedure, which improves the accuracy of double-vectors and IFA; the gradient descent scheme is adopted to estimate the optimal attitude of alignment without complex matrix operation, which results in the improvement of alignment speed. The effect of different sizes of mini-batch on the performance of the gradient descent method is also discussed. Extensive simulations and vehicle experiments demonstrate that the proposed method has better accuracy and faster alignment speed than the related traditional methods for the low-cost SINS/global positioning system (GPS) integrated navigation system . [ABSTRACT FROM AUTHOR]

The optimization-based alignment (OBA) methods, which are implemented by the optimal attitude estimation using vector observations-also called double-vectors-have proven to be effective at solving the in-flight alignment (IFA) problem. However, the traditional OBA methods are not applicable for the low-cost strap-down inertial navigation system (SINS) since the error of double-vectors will be accumulated over time due to the substantial drift of micro-electronic- mechanical system (MEMS) gyroscope. Moreover, the existing optimal estimation method is subject to a large computation burden, which results in a low alignment speed. To address these issues, in this article we propose a new fast IFA method based on modified double-vectors construction and the gradient descent method. To be specific, the modified construction method is implemented by reducing the integration interval and identifying the gyroscope bias during the construction procedure, which improves the accuracy of double-vectors and IFA; the gradient descent scheme is adopted to estimate the optimal attitude of alignment without complex matrix operation, which results in the improvement of alignment speed. The effect of different sizes of mini-batch on the performance of the gradient descent method is also discussed. Extensive simulations and vehicle experiments demonstrate that the proposed method has better accuracy and faster alignment speed than the related traditional methods for the low-cost SINS/global positioning system (GPS) integrated navigation system., Competing Interests: The authors declare no conflict of interest.