The technology of hydrodynamic modeling and marine craft motion control systems has progressed greatly in recent years. This timely survey includes the latest tools for analysis and design of advanced guidance, navigation and control systems and presents new material on underwater vehicles and surface vessels. Each section presents numerous case studies and applications, providing a practical understanding of how model-based motion control systems are designed.

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Handbook of Marine Craft Hydrodynamics and Motion Control: Fossen/Handbook of Marine Craft Hydrodynamics and Motion Control

Optimization approach to adapt Kalman filters for the real-time application of accelerometer and gyroscope signals' filtering

The integrated strapdown inertial navigation system/global position system (SINS/GPS) is a widely used procedure for position, velocity and attitude determination. There are two options for the state estimation procedure by a filtering system model and the integration filter, namely direct navigation mode that estimates the navigation parameters and indirect navigation mode that estimates the error of navigation parameters with a feedback calculation process. To a certain extent, they both have their own advantages. However, determining which one of the two navigation modes will be more celebrated than the other under different conditions is a beneficial but thus far less seriously treated issue. In this study, two navigation modes are systematically studied in terms of the filtering system model, filtering algorithm and application issues. The simulation test and car-mounted experiments for low-precision and high-precision SINS are carried out to compare the performance of two navigation modes under diff...

http://journals.sagepub.com/doi/pdf/10.1177/0142331214568236

Comparison of direct navigation mode and indirect navigation mode for integrated SINS/GPS:

The known methods used for strapdown inertial navigation system (SINS)/celestial navigation system (CNS) integration are classified based on two categories of measurement in this paper. One category is called the “attitude observation method,” in which the measurement is derived by the difference between the optimal attitude information of the star sensor and the SINS. The other category is called the “star vector observation method,” in which the measurement is derived by the difference between the original star vector information of the star sensor. The attitude angle observation equation of the first category is generally obtained by using the relationship between the attitude angle errors and the Phi-angle (or tilt errors), and the attitude matrix observation equation is obtained by using the relationship between the attitude matrix and the Psi-angle (or platform errors). However, the interrelationship between these two observation equations has not been developed in previous studies. A simpler attitude angle observation method based on the Psi-angle instead of the Phi-angle is proposed to reveal the interrelationship between these two methods. This proposed method is basically the principle behind the SINS/CNS integration and depicts the physical meaning clearly. In addition, the internal relationships of the second category and the interrelationship of these two categories are also analyzed to show their equivalence to each other. Numerical simulations verify the correctness of the analysis. Experimental studies indicate that the integration accuracy of the two categories is also exactly equivalent.

Classification of Methods in the SINS/CNS Integration Navigation System

Proceeding from actual needs of AINS initial alignment technology, this paper is specific to rigidity carrier ship, and it deduces the model equations of Airborne Inertial Navigation System's velocity and acceleration (ecificforce) with the effect of arm-lever vector. It employs the method that establishes large initial misalignment angle transfer alignment model of AINS, which is other than traditional velocity and attitude matching algorithm. Basing on nonlinear deterministic particle filtering, it simulates the performance of the model with experimental data, and comparatively studies inhering lever-arm vector error's influence on AINS misalignment attitude angle estimation error and its alignment accuracy. With different initial lever-arm vectors it researches its effects on misalignment attitude angle's estimation error and the accuracy of transfer alignment. The simulation results verify the model's validity and its superior alignment accuracy in transfer alignment of AINS. It is of great theory and application value in design of AINS.

The Impact of Arm-Lever Effect Error Based Large Initial Misalignment Transfer Alignment Technology Study

Almost all aircraft are equipped with the Inertial Navigation Systems. The autonomous Inertial Systems are capable of calculating the navigational parameters of aircraft: position, velocity, and attitude, without external sources of information. In the paper the equations and algorithms of strapdown navigation system are derived and analysed. The research is focused on the calculation methods of the aircraft attitude.

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Strapdown inertial navigation system. Part 1 – Navigation equations

Almost all new aircraft are equipped with the Inertial Navigation System (INS). The accuracy in calculations of velocity, position and attitude of aircraft depends on measurement Instruments, initial alignment errors, and navigation computer errors and can be improved by analysing and solving of differential equation of error. Solution of the equations allows one to correct output signals from the navigation system. In this work, three error models for the Strapdown Inertial Navigation System (SDINS) are derived – one into computed co-ordinate system in matrix notation and two models in a local-level co-ordinate system, in matrix and in quaternion notations, respectively. Some simplifications to be introduced into error equations are proposed.

/pdf/strapdown-inertial-navigation-system-part-2-error-models-1x45ei4y4g.pdf

Albert Ortyl

Papers

Strapdown inertial navigation system. Part 1 – Navigation equations

Strapdown inertial navigation system. Part-2 – Error models