The Research Of Beidou-Ⅱ Navigation System Location Algorithm Based On Unscented Kalman Filter

Since the80’s of last century, China began to prepare for the establishment of satellite navigation system of our own country. Until the end of2012, the Beidou Ⅱ navigation system has been able to provide navigation service for the Asia Pacific region. The construction and development of the Beidou satellite navigation system, the Beidou navigation terminal hardware and software localization algorithm, improve the Beidou satellite navigation industry chain. Play an important role in various fields of promoting China’s economic development, construction, national social service guarantee national security.It’s will improve Beidou’s application ability if we can improve the positioning accuracy, filter noise, accelerate the localization speed. In the field of positioning algorithm, the most prominent is Kalman filter based on minimum variance estimation. Kalman filter was paid much attention by the academic since it was invented, because of its excellent performance and convenient calculation way, With the increasing application of Kalman filter more widely. The extended Kalman filter (EKF) and the unscented Kalman filter (UKF) were invented which base on the Kalman filter. And UKF is always the key point of researchers because of its excellent performance, strong applicability used in nonlinear system,At first, This paper describes the whole process of the receiver calculate from receives the navigation message to calculate the user’s coordinates, Including the difference of the ephemeris data and almanac data, And Calculation the satellites’ positions in the earth of2000coordinate system by select useful parameters in the navigation message, common methods of cycle slip detection and repair, and ionospheric correction model.Then, we describes the principle and process of the UKF algorithm, According to the problems of the relationship of initial value of UKF filter and the filter’s convergence rate, use micro inertial measurement unit help UKF algorithm accelerate the speed to a stability state, calculate positions of the receiver base on the output signal of micro inertial measurement unit, Replace the receiver observation sequence, Reduce the error of single observation series, Promote the filter convergence speed.Finally, using the experimental system based on the UB240satellite signal receiving board、MinilMU module、MICRO2440embedded development board、Launchpad and intelligent car collect data, and use MATLAB process the data, prove the correctness of this method we used.After repeated experiments, proved the effective to improve the convergence speed by using the micro inertial measurement unit. and the key is to improve the accuracy of micro inertial measurement unit.