Research On Integrated Navigation Technology For Land Vehicle Use Based On MIMU/UDVL

The needs and requirements of modern vehicles for high-reliability and high-precision navigation system have been increasingly growing.Single navigation system can hardly meet such demand, so integrated navigation becomes the main development direction of vehicle navigation.The integrated navigation based on MIMU (Micro-Inertial Measurement Unit)/UDVL (Ultrasonic Doppler Velocity Log) can really realize low-cost,high-precision navigation as a more ideal vehicle navigation system in the future.The main research contents of this article are as follows:Firstly, the thesis has a detailed analysis on the principle and error model of SINS(Strap-down Inertial Navigation System) based on MIMU and UDVL, accounting for thenecessity of combining the SINS and UDVL.Secondly, the initial coarse alignment is completed. The initial attitude angles obtainedfrom the initial coarse alignment are used to calculate the optimal estimation for attitude errorangles by quaternion update method and Kalman filtering, in order to carry out the finealignment. The simulation analysis of several UDVL frequency measurement algorithms isgiven; the simulation results are applied to confirm the practical frequency measurementalgorithms. Based on MIMU/UDVL tight combination mode, the state equation andmeasurement equation of the integrated navigation system is established, and UnscentedKalman Filter of high precision is designed to do the data fusion for integrated system.Thirdly, the paper completes Udvl’s hardware design based on DSP, including ultrasonictransducer, receiver and transmitter system, and DSP peripheral circuits. In CCS developmentenvironment, the thesis also completes Udvl’s software design, including SPWM wavebelonging to ultrasonic transmitter system, AD sampling, and frequency measurementalgorithm.Lastly, the initial alignment algorithm of MIMU/UDVL integrated system is simulated toshow that this algorithm can successfully finish the alignment task and provide accuratealignment conditions for MIMU/UDVL.The Kalman filtering, extended Kalman filtering andunscented Kalman filtering are separately applied in MIMU/UDVL.From their simulationresults, it can be seen that compared with a single navigation system,MIMU/UDVL integratedsystem has a greatly improved navigation accuracy, and UKF is the best filtering algorithm tocomplete MIMU/UDVL data fusion.