Strapdown Inertial Navigation Algorithm Research Articles

Hypersonic boost–glide vehicle strapdown inertial navigation system / global positioning system algorithm in a launch-centered earth-fixed frame

To suit the features of hypersonic vehicles and meet the requirement of their flight control system, we propose an integrated navigation algorithm in the launch-centered earth-fixed (LCEF) frame. First, we introduce a system mechanization for the strapdown inertial navigation algorithm in the LCEF frame and derive discrete update algorithms of strapdown inertial navigation attitude, velocity, and position in the LCEF frame. A coning effect compensation algorithm is deduced in the update algorithm of attitude, and a sculling effect compensation algorithm is deduced in the update algorithm of velocity. Then, we derive the attitude, velocity, and position error equations in the LCEF frame; we further derive a strapdown inertial navigation system (SINS) / global positioning system (GPS) integrated navigation filter state equation and measurement equation of the LCEF frame as well as introduce a simultaneous method of SINS/GPS integrated navigation. Finally, considering the typical hypersonic boost–glide vehicle as the object, the SINS/GPS algorithm is applied in a semi-physical simulation environment; verification results yield a position error less than 10 m, a velocity error less than 0.2 m/s, and an attitude error less than 0.05°.

Research on Strapdown Inertial Navigation and Laser Doppler Combination Navigating Algorithm

In the current strapdown inertial navigation system, there are errors in the calculation model set by the airborne computer and the accuracy of related equipment, and the errors accumulate over time, which will lead to lower navigation accuracy and larger speed deviation. In order to solve the above problems, a new integrated navigation algorithm is proposed in this paper, which takes strapdown inertial navigation system as the main body and calculates the velocity and attitude of the aircraft. Laser Doppler assisted velocity measurement system is used as the auxiliary navigation system to correct and eliminate the velocity error of strapdown inertial navigation system. At the same time, Kalman filter technology is used to modify the velocity data of integrated navigation system. The simulation results show that the integrated navigation algorithm can reduce the speed error and improve the navigation accuracy, which verifies the effectiveness and feasibility of the integrated navigation algorithm.

Remote length measurement system using a single point laser distance sensor and an inertial measurement unit

In this paper, we propose a remote measurement system consisting of a single point laser distance sensor and an IMU (Inertial Measurement Unit). The movement of the system is estimated using a strapdown inertial navigation algorithm. This movement information is combined with the distance sensor to obtain remote point position. The distance sensor is a time-of-flight range finder and can measure distances up to 40m. Using the estimated remote point position, length between remote points is computed. Also, a plane to plane (such as wall to wall) distance is estimated. The maximum root mean square of the error (RMSE) for the length, height, and angle are 2.93cm, 2.23cm and 0.58°, respectively.

Comparison of strapdown inertial navigation algorithm based on rotation vector and dual quaternion

For the navigation algorithm of the strapdown inertial navigation system, by comparing to the equations of the dual quaternion and quaternion, the superiority of the attitude algorithm based on dual quaternion over the ones based on rotation vector in accuracy is analyzed in the case of the rotation of navigation frame. By comparing the update algorithm of the gravitational velocity in dual quaternion solution with the compensation algorithm of the harmful acceleration in traditional velocity solution, the accuracy advantage of the gravitational velocity based on dual quaternion is addressed. In view of the idea of the attitude and velocity algorithm based on dual quaternion, an improved navigation algorithm is proposed, which is as much as the rotation vector algorithm in computational complexity. According to this method, the attitude quaternion does not require compensating as the navigation frame rotates. In order to verify the correctness of the theoretical analysis, simulations are carried out utilizing the software, and the simulation results show that the accuracy of the improved algorithm is approximately equal to the dual quaternion algorithm.

Simplified Design of Dual Quaternion Strapdown Inertial Navigation Integration Algorithms

Dual quaternion navigation algorithm gain higher accuracy than traditional strapdown inertial navigation algorithm at the cost of real-time performance. In order to reduce tremendous computation amount of the former, a simplified design scheme for navigation integration algorithms is presented in this paper. First, based on update principle and computation rules of dual quaternion we separate rotational and translational increment information from dual quaternion increment, and deduce exact solutions defined by the spiral vector for thrust velocity increment, gravitational velocity increment and displacement increment. Then, considering characteristics of a strapdown inertial navigation system, implementation schemes of simplified integration algorithms for dual quaternion differential equations in three frames, including thrust velocity coordinates, gravitational velocity coordinates and position coordinates, are designed separately. Under the premise of ensuring the accuracy advantage of the original dual quaternion inertial navigation algorithm, the proposed simplified algorithm significantly improve the computational efficiency. This will lay favorable foundation for engineering realization of the dual quaternion strapdown inertial navigation algorithm.

Comparison of numerical integration methods in strapdown inertial navigation algorithm

The numerical mathematical theory provides a few ways of numerical integration with different errors. It is necessary to make use of the most exact method with respect to the computing power for a majority of microprocessors, because errors are integrated within them due to the algorithm. In our contribution, trapezoidal rule and Romberg’s method of numerical integration are compared in the velocity calculation algorithm of the strapdown inertial navigation. The sample frequency of acceleration and angular velocity measurement was 816.6599 Hz. Inertial navigation velocity was compared with precise incremental encoder data. Trapezoidal method velocity error in this example was 1.23 × 10<sup>–3</sup> m/s in the fifteenth-second measurement. Romberg’s method velocity error was 0.16 × 10<sup>–3 </sup>m/s for the same input data. The numerical mathematical theory provides a few ways of numerical integration with different errors. It is necessary to make use of the most exact method with respect to the computing power for a majority of microprocessors, because errors are integrated within them due to the algorithm. In our contribution, trapezoidal rule and Romberg’s method of numerical integration are compared in the velocity calculation algorithm of the strapdown inertial navigation. The sample frequency of acceleration and angular velocity measurement was 816.6599 Hz. Inertial navigation velocity was compared with precise incremental encoder data. Trapezoidal method velocity error in this example was 1.23 × 10<sup>–3</sup> m/s in the fifteenth-second measurement. Romberg’s method velocity error was 0.16 × 10<sup>–3 </sup>m/s for the same input data.

정밀 스트랩다운 관성항법을 위한 혼합 이체쿼터니언 알고리즘

Dual quaternion is efficient methodology to express rotation and translation of the vehicle`s movements in the unified frame work. Recently, a strapdown inertial navigation algorithm based on dual quaternion was introduced. By comparing and analyzing the classical and dual-quaternion algorithms, this paper proposes a new strapdown inertial navigation algorithm that maintains the accuracy benefit of the dual-quaternion algorithm with considerable computational reduction. Simulation results show the efficiency of the proposed hybrid strapdown navigation algorithm. ᠊缀Ѐ㘰〻਀呥捨湯汯杹

Erratum To Savage, P.G., "Strapdown Inertial Navigation Algorithm Design Part 2: Velocity and Position Algorithms", JGCD, Vol. 21, No. 2, 1998, pp. 208-221

Erratum To Savage, P.G., "Strapdown Inertial Navigation Algorithm Design Part 2: Velocity and Position Algorithms", JGCD, Vol. 21, No. 2, 1998, pp. 208-221

Instrumentation and Data Processing for Identification of Nonlinear Ship Hydrodynamics

This paper describes a portable instrumentation package used to collect ship motion data. The package includes a six degree of freedom inertial sensor set, a LORAN-C radio position fix receiver, and interfaces with shipboard rudder angle, propeller rate, and Doppler sonar speed sensors. A processor in the package implements a strapdown inertial navigation algorithm for data compression and consistency testing. The data collected are of sufficient quality for the system identification of the hydrodynamic coefficients of the subject vessel's maneuvering mathematical model. The package has to date been employed once in proof-of-concept trials conducted by the Kings Pointer, a 1000 ton ocean going tug. The resulting data allow the identification of a nonlinear dynamic model of this vessel.