Double-vector attitude determination algorithm improving coarse alignment accuracy of strapdown inertial navigation system for sea cucumber fishing device

Abstract: Autonomous navigation is one of the key technologies for an intelligent agricultural equipment, which has been widely used in modern agricultural production. Sea cucumber production and consumption are very large in China. At present, the sea cucumber harvest mainly relies on trawl or artificial fishing, which will cause a potential hazard to the health of divers and the marine ecology. Therefore, in order to overcome the shortcomings of traditional sea cucumber fishing methods, it is necessary to develop a sea cucumber fishing device with autonomous navigation and positioning functions. Strapdown inertial navigation system (SINS) is suitable for the navigation of the autonomous sea cucumber fishing device because of its autonomy, passivity and complete navigation parameters. For the SINS, initial alignment must be completed before starting a navigation mission. The purpose of the initial alignment is to determine the initial position of the carrier coordinate system relative to the navigation coordinate system, that is, to determine the initial value of the attitude matrix. Initial alignment is one of the key technologies of SINS, which is divided into coarse alignment and fine alignment, and the coarse alignment accuracy will directly determine the performance of the initial alignment. Therefore, it is of practical value to study a coarse alignment scheme with simple algorithm and high alignment precision. The traditional analytical coarse alignment algorithm directly utilizes the earth gravity vector and the earth rotation angular velocity vector to estimate the initial attitude matrix. In view of the problem that the horizontal alignment accuracy of SINS is affected by the measurement errors of gyroscope and accelerometer in the traditional analytical coarse alignment algorithm, a novel coarse alignment algorithm based on double-vector attitude determination is proposed. In general, the measurement error of the accelerometer is much smaller than that of the gyroscope, so the earth gravity vector in the proposed algorithm is chosen as the main reference vector. Then, 3 unit orthogonal vectors are constructed based on the earth gravity vector and the earth rotation angular velocity vector, and the resulting attitude matrix is a unit orthogonal matrix. The theoretical analysis shows that horizontal misalignment angles of SINS are only related to the accelerometer level measurement errors in the case of using the proposed algorithm, however, using the conventional algorithm, the horizontal misalignment angles are related to the accelerometer measurement errors and the gyroscope drift error. Therefore, the coarse alignment accuracy of SINS using the aforementioned algorithm is significantly improved. Based on the same measured data from an inertial measurement unit, the simulation experiment was carried out for 30 times using the conventional coarse alignment algorithm and the proposed algorithm, respectively. Simulation curves demonstrated that the variation of the horizontal attitude angles using the algorithm proposed was smoother. To further verify the effectiveness of the algorithm, the attitude angles calculated from the measured values of the inertial measurement unit were compared with the measured value of a high-precision three-dimensional electronic compass, and the experimental results showed that the horizontal error angles of the aforementioned coarse alignment algorithm did not exceed 1° and the azimuth error angle did not exceed 3°. The results can meet the accuracy requirement of coarse alignment and will provide an effective initial condition for the subsequent fine alignment using filtering methods.