Study On Integrated Navigation Algorithm Of FOG SINS/DVL

With the development of national economy and military requirement, navigation ofvehicles and ships was toward to the high-precision and high real-time direction.Because ofnot depending on any external device’s unique attributes, Strapdown Inertial NavigationSystem (SINS) was become an essential navigation equipment, especially underwaternavigation. However, the strapdown inertial navigation system meet Newton’s second law, theerror accumulated over time. In the case of a long navigation, the accuracy became lower.Integrated Navigation system of SINS/DVL could significantly overcome the abovedrawbacks. Therefore, INS/DVL integrated navigation system was researched and applicatedby a growing number, because of its high-precision navigation parameters in a longer time.In this paper, a integrated navigation system of SINS/DVL by velocity was studied, thissystem had a high precision and easy-to-implement project. In the aspect of algorithm, firstly,the basic principles and error equations was studied of SINS and DVL. Then, the form ofDVL’s velocity was simulated. Followly, calibration experiments of rate and location wasdesigned in order to get the error coefficient of the error equation, at the same time,thecorrection equation modified using the result of calibration experiment was given.Afterwards the strapdown algorithm based on the equation of solving navigation parameterswas designed, On this basis, the intergrated algorithm of SINS/DVL was designed, afterthe analization of the advantages and disadvantages of various algorithms, here Kalmanfiltering algorithm was choosed, And in the MATLAB software environment, the sampleddata of gyro and accelerometer on the same group was solved with the strapdown andcombination algorithm. Through the case of the two algorithms to obtain the navigationparameter errors compared to verify the design in this paper based on a combination ofKalman filtering algorithm is effective and feasible.After contrast of the navigation parametererrors in these two algorithms, the effectiveness and feasibility of intergrated algorithm wasproved.In the aspect of hardware design, the most important part of the system designed in thisarticle is the navigation computer, which was selected FPGA-based navigation computer. theinterface circuit of measurement components was designed according to the protocol. Then,this hardware system was packaged in a metal shell, and reserved interface cable to be usedon engineering.In the aspect of embedded operating system, system software and SOPC framework used in practical systems was designed. Then, μC/OS-II operating system was used in softwarealgorithms and introduced the steps of the system software design.Finally, the static turntable experiment and the underwater experiment of this integratednavigation system were done, and using the navigation Kalman filter algorithm designed inthis paper to process the data collected by these experiments. And the results of theseexperiments proved this algorithm could greatly improve the navigation accuracy and couldmeet the actual project requirements.