Triangle star identification algorithm is the most widely used and most mature star pattern recognition algorithms. When the number of guide star is relatively huge and the capacity of guide star catalog is relatively large, with the result that the complexity of triangle star identification algorithm increases, the time of star pattern recognition becomes longer, and even the storage space occupied by the algorithm becomes larger. So it is difficult to realize the rapid and effective star identification in star map. In order to improve the efficiency of star identification algorithm and shorten the time of star recognition, it is proposed that a star identification algorithm used on the data structure of hash map and based on the triangle algorithm. The first thing is to make the guide star catalog. Then, all the angular distance values d ijm (0 < i < j ≤ N) of the brightest N observed stars in an observed star image and their corresponding star angular distance sets are calculated, and the triangle features, namely angular distance values, are stored in the hash map. In this algorithm, each triangle feature is mapped to an integer, and the hash map of all triangle features is set to reduce the computational complexity of triangle pattern matching, decrease the number of star angular distance matching, and greatly shorten the time of star image recognition. Simulation results show that the star image recognition algorithm based on hash map has better computational complexity and efficiency of performance than traditional triangle algorithm.
For the marine integrated navigation system composed of strapdown inertial navigation system (SINS) and Doppler velocity log (DVL), when the range of DVL is insufficient, it can only output the velocity of carrier relative to ocean current. If the algorithm is not improved, it will cause great navigation and positioning error. In this paper, the Kalman filtering equation is derived by analyzing the error equation of integrated navigation system, and a SINS/DVL integrated navigation algorithm considering ocean current velocity is proposed, and the feasibility of the algorithm is verified by simulation experiments. The simulation results show that the SINS/DVL integrated navigation algorithm considering ocean current information can effectively improve the positioning accuracy when DVL works in water tracking mode.
Due to the harsh working environment and lacking of external information, after a long period of work, the performance of the local reference inertial device will deteriorate, which will cause the navigation information to fail to meet the requirements of user equipment. In this paper, a local reference dynamic calibration method based on hull deformation compensation is proposed. Firstly, eliminate the coordinate system misalignment between the main inertial navigation system (MINS) and the local reference. Furthermore, a Kalman filter is designed to calibrate the bias errors of the local reference laser gyro and accelerometer based on the high-precision navigation information of the MINS. The simulation results show that after accurate hull deformation compensation, the local reference laser gyro bias error estimation accuracy is better than 0.002°/h , accelerometer bias error estimation accuracy is better than 1μg ,which provides an effective solution for local reference marine dynamic calibration
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.