44 results about "Doppler velocity log" patented technology

The invention provides a UUV (unmanned underwater vehicle) aided navigation method based on current profile. The method comprises the following steps: firstly setting up a Kalman filter model of current profile data, secondly determining the observation noise variance R and process noise variance Q in a Kalman equation according to variations of the environment and the UUV own velocity and finally setting up a UUV velocity-current profile relation database, utilizing the relation database and the current profile information measured by an ADCP (acoustic Doppler current profile) to reckon the UUV velocity at the time of DVL (Doppler velocity log) failure and further obtaining the navigation position of the UUV by deadreckoning. The method has the following beneficial effects: when the UUV performs a task under water, once the sonar data of the DVL have failure, the UUV velocity can be reckoned by using the current profile information measured by the ADCP, so that the UUV can continue performing the ocean exploration task in the complex ocean environments such as great depth, thus improving the environmental adaptation capability of the UUV.

The invention discloses a correcting method of installation errors of a doppler log of an autonomous underwater vehicle (AUV). The correcting method comprises the following steps: (1), data acquiring, namely acquiring northeast-direction location information, depth information, speed information and gesture information of the AUV on water surface; (2), filter wave estimating, namely by taking a DVL (Doppler Velocity Log) dead reckoning model with error correction, AUV three-dimensional location information and a DVL three-dimensional installation drift angle as system state vectors, the speed information measured by a DVL and the gesture information measured by a gesture sensor as system input vectors, the AUV three-dimensional location information as a measuring vector, establishing a discrete time system state equation and a measuring equation; carrying out filter wave estimating by adopting improved square capacity root Kalman filtering to obtain an estimated value of the DVL installation drift angle; and (3), error correcting, namely acquiring a DVL installation error correcting matrix according to the estimated value of the installation drift angle. The correcting method disclosed by the invention is easy to operate, does not need external equipment assistance and can effectively estimate the three-dimensional installation drift angle of the DVL, so that influences of the DVL installation errors on the AUV navigation accuracy are eliminated, and practical value is very high.

The invention discloses an alignment method of an underwater large misalignment angle based on SINS (Strapdown Inertial Navigation System) / DVL (Doppler Velocity Log) of SRQKF (Square-root Quadrature Kalman Filter). The alignment method comprises the following steps: step 1: establishing a nonlinear error model and a nonlinear filtering equation of the SINS under the large misalignment angle; step 2: constructing the SRQKF by utilizing a multivariate Gauss point and coefficient configuration method and a square-root filtering method in Gauss-Hermite quadrature; and step 3: estimating the misalignment angle by utilizing the SRQKF, and correcting a strapdown attitude matrix, thus obtaining accurate strapdown attitude matrix and attitude angle. The alignment method disclosed by the invention has the advantage that the underwater alignment accuracy and alignment speed of the carrier strapdown system are improved.

The invention discloses a dynamics-based velocity model assisted underwater intelligent navigation method. The method includes the following steps that: (1) on-board sensor information is periodicallycollected; (2) the input variables and output variables of a velocity model to be established are determined; (3) the velocity model is constructed and trained; and (4) when it is detected that a DVL(Doppler Velocity Log) malfunctions or the data of the DVL fail, navigation analysis is performed with the output velocity of the trained model used as a bottom velocity, and therefore, model-assisted navigation can be performed. According to the method of the invention, a new AUV (Autonomous Underwater Vehicle) velocity model is put forward based on the idea of dynamic models; the influence of factors such as rudder angles of rudder blades, and heading angles is considered; as long as the fault data of the DVL are not detected during an operation process, training sets can be increased at any time to train the model; after the fault data of the DVL are detected, the output velocity of the model can be adopted instead, and therefore, the problem of navigation error increase caused by thefailure or fault of the DVL can be avoided; the redundancy method of velocity sensors is provided with no hardware costs increased; the method has good system robustness and can guarantee high-precision navigation.