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Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The initial alignment of the inertial navigation system of unmanned offshore platforms is interfered with the swaying motion induced by wave action. Departing from the traditional alignment model based on gravitational apparent motion, this paper derives the models of gravitational apparent acceleration and velocity in order to overcome the theoretical insufficiency of directly employing accelerometers to approximate gravity. Parameter identification and reconstruction of gravitational apparent motion are performed by recursive least squares algorithm (RLS) to determine the attitude of the strapdown inertial navigation system (SINS). Concurrently, a comparison is made between the calculated and reconstructed gravitational apparent motion for the separation of the platform's linear acceleration or velocity. Simulation and mooring experiment indicate that the method studied in this paper demonstrates superior convergence and accuracy compared to traditional anti-rocking coarse alignment methods. In particular, the parameter identification alignment method based on gravitational apparent velocity is capable of achieving the extreme accuracy of the inertial measurement unit (IMU). The error in separated linear motion does not diverge over time, which meets engineering requirements. This method has important implications for application scenarios such as the initialization of inertial navigation systems on unmanned platforms. • The proposed method significantly improves the accuracy and convergence of attitude angles compared with the traditional method. • The method addresses the theoretical limitations for alignment and allows the separation of linear acceleration or velocity. [ABSTRACT FROM AUTHOR]

To solve the problem of high-precision and fast initial alignment for the Strapdown Inertial Navigation System (SINS) under both dynamic and static conditions, the high-precision attitude measured by the celestial navigation system (CNS) is used as the reference information for the initial alignment. The alignment algorithm is derived in the Earth-centered inertial (ECI) frame. Compared with the alignment algorithm in the navigation frame, it is independent of position parameters and avoids the influence of the approximate error caused by the dynamic deflection angle. In addition, hull deformation is considered in attitude optimal estimation, which can realize initial the alignment of the SINS installed in various parts of the carrier. On this basis, the velocity measurement information is added to the alignment process, which further improves the accuracy and speed of the initial alignment under static conditions. The experimental results show that the algorithms proposed in this paper have better performance in alignment accuracy, speed, and stability. The attitude and velocity matching algorithm in the ECI frame can achieve alignment accuracy better than 0.6′. The attitude matching algorithm in the ECI frame has better robustness and can be used for both dynamic and static conditions, which can achieve alignment accuracy better than 1.3′. [ABSTRACT FROM AUTHOR]

To solve the problem of high-precision and fast initial alignment for the Strapdown Inertial Navigation System (SINS) under both dynamic and static conditions, the high-precision attitude measured by the celestial navigation system (CNS) is used as the reference information for the initial alignment. The alignment algorithm is derived in the Earth-centered inertial (ECI) frame. Compared with the alignment algorithm in the navigation frame, it is independent of position parameters and avoids the influence of the approximate error caused by the dynamic deflection angle. In addition, hull deformation is considered in attitude optimal estimation, which can realize initial the alignment of the SINS installed in various parts of the carrier. On this basis, the velocity measurement information is added to the alignment process, which further improves the accuracy and speed of the initial alignment under static conditions. The experimental results show that the algorithms proposed in this paper have better performance in alignment accuracy, speed, and stability. The attitude and velocity matching algorithm in the ECI frame can achieve alignment accuracy better than 0.6′. The attitude matching algorithm in the ECI frame has better robustness and can be used for both dynamic and static conditions, which can achieve alignment accuracy better than 1.3′.

Analytic alignment is a type of self-alignment for a Strapdown inertial navigation system (SINS) that is based solely on two non-collinear vectors, which are the gravity and rotational velocity vectors of the Earth at a stationary base on the ground. The attitude of the SINS with respect to the Earth can be obtained directly using the TRIAD algorithm given two vector measurements. For a traditional analytic coarse alignment, all six outputs from the inertial measurement unit (IMU) are used to compute the attitude. In this study, a novel analytic alignment method called selective alignment is presented. This method uses only three outputs of the IMU and a few properties from the remaining outputs such as the sign and the approximate value to calculate the attitude. Simulations and experimental results demonstrate the validity of this method, and the precision of yaw is improved using the selective alignment method compared to the traditional analytic coarse alignment method in the vehicle experiment. The selective alignment principle provides an accurate relationship between the outputs and the attitude of the SINS relative to the Earth for a stationary base, and it is an extension of the TRIAD algorithm. The selective alignment approach has potential uses in applications such as self-alignment, fault detection, and self-calibration.

Copyright of Piezoelectrics & Acoustooptics is the property of Piezoelectric & Acoustooptic and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Piezoelectrics & Acoustooptics is the property of Piezoelectric & Acoustooptic and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to achieve high precision of initial alignment and inertial sensor calibration, this paper proposes a high accuracy multiplex two-position alignment method based on SINS (Strapdown Inertial Navigation System) with the aid of star sensor. Firstly, the Mars rover's approximate initial position is determined by the lander's landing position, and its initial attitude is obtained with the time and the output of star sensor. Based on that, a two-position alignment method aided by star sensor's precise attitude information is used to improve accuracy of initial alignment and inertial sensor calibration. It can take full advantages of both inertial navigation and celestial navigation. Finally, we deduce the relationships between estimation errors of accelerometer bias, estimation errors of misalignment angles and position errors. The rover's higher accuracy initial alignment is achieved by using the deduced relationships and the estimates of accelerometer bias to correct the rover's initial position and attitude. The simulation results demonstrate that the presented method can meet the high accuracy requirements of the rover's initial alignment and inertial sensor calibration. [ABSTRACT FROM AUTHOR]

In this paper, a conventional Strapdown Inertial Navigation System (SINS) alignment method on a disturbed base is analysed. A novel method with an attitude tracking idea is proposed for the rocking base alignment. It is considered in this method that the alignment algorithm should track the rocking base attitude real changes in the alignment process, but not excessively restrain disturbance. According to this idea, a rapid alignment algorithm is devised for the rocking base. In the algorithm, coarse alignment is carried out within 30 s in the inertial frame with alignment precision less than 2°, which meets Kalman filter linearization conditions well. Then a Kalman filter with ten state vectors and four measurement vectors is applied for the fine alignment to improve the capability of the algorithm in tracking the vehicle attitude. A turntable rotation experiment is carried out to validate the capability of the fine algorithm in tracing the large magnitude change during alignment. It is shown that the repeated alignment precision is about 0·04° by the alignment experiment on a rocking vehicle, with alignment time of 180 s. The Laser Strapdown Inertial Navigation System (LINS) ground navigation experiment suggests that the algorithm proposed by this paper can be satisfied without the need of high precision SINS alignment. [ABSTRACT FROM AUTHOR]

Highlights: [•] A new fast compass alignment method based on repeated navigation solution is designed in detail. [•] In this method, alignment time is reduced without reducing alignment accuracy. [•] The reason why repeated navigation solution can be used for SINS compass alignment is given. [•] Two repeated navigation solution algorithms are compared, and forward–forward loop is chosen. [•] Simulation and test results indicate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a method for the initial alignment of strap-down inertial navigation system on stationary base. In the coarse alignment, Magnetism compass and accelerometer are used to get the initial pose angles. In the precise alignment, radial basis function network (RBF network), in which radial function chosen by averaging method and weights adjusted by an improved H∞ robust filter, is applied to correct the pose angles to ensure the robustness and real-time computing. Simulation results show that comparing with ordinary H ∞ filter learning algorithm and extended Kalman filter, this method is efficient and rapid for initial alignment. [Copyright &y& Elsevier]

Abstract: Strapdown inertial navigation system (SINS) is presently used in several applications related to aerospace system and marine navigation. The accurate initial attitude is essential to ensure the precise determination of the position and attitude of the moving platform, which is usually calculated using initial alignment. When the vehicle is moored, the SINS inevitably experience disturbing motion. The method of ground coarse alignment, which is based on the assumption that SINS is on a stationary carrier with limited vibration, therefore cannot be used to perform the SINS mooring alignment. In this paper, a novel method processing the gyro and accelerometer measurements with infinite impulse response (IIR) digital low-pass filter to remove the high frequency noise is investigated for marine mooring alignment. Its algorithmic principle is described in details. The results obtained from both simulation and mooring experiment show that the attitude determined by this novel method can meet the accurate alignment. [ABSTRACT FROM AUTHOR]

There are many filtering methods that can be used for the initial alignment of an integrated inertial navigation system. This paper discussed the use of GPS, but focused on two kinds of filters for the initial alignment of an integrated strapdown inertial navigation system (SINS). One method is based on the Kalman filter (KF), and the other is based on the robust filter. Simulation results showed that the filter provides a quick transient response and a little more accurate estimate than KF, given substantial process noise or unknown noise statistics. So the robust filter is an effective and useful method for initial alignment of SINS. This research should make the use of SINS more popular, and is also a step for further research. [ABSTRACT FROM AUTHOR]