Research On The Key Technology Of Vehicle Beidou Software Receiver

With the development of intelligent control and computer technology,the vehicle is becoming more and more intellectualized.And the driverless cars are gradually being applied into use form concept.As the foundation of path planning and environment perception,the navigation is important to the safe driving of driverless cars.Compared with the traditional vehicle,the driverless cars have higher requirement for the navigation’s accuracy,continuity and reliability.The software receiver is more conductive to realize the multi sensor fusion high precision navigation than hardware receiver.In order to improve the positioning accuracy of driverless cars,the baseband signal processing algorithms of vehicle Beidou software receiver are studied,and the fast acquisition algorithm and high sensitivity tracking algorithm are proposed.First,aiming at the problem that the traditional parallel code phase acquisition algorithm can not adjust the code phase search step,this paper proposes the parallel acquisition algorithm based on decomposed FFT.It divides the signals into P(P is constant)parts to do correlation and gets the correlation results with fusion algorithm.This algorithm can obtain the correlation results in the sampling points at interval of P points simultaneously.If the P value is selected appropriately,the computational load can be decreased by about 50%.Besides,the simulation results show that the PTP values of traditional algorithms and proposed algorithm are close.So the two algorithms have the same acquisition accuracy.Second,the aided acquisition algorithm is proposed based on the fast acquisition algorithm of B1 signal.This algorithm use the parallel acquisition algorithm based on decomposed FFT to capture the B1 signal first,and then narrow the search space of B2 signal according to the acquisition results of B1 signal.Finally,the Doppler frequency and code phase of B2 signal are got by the correlation operation in time-domain.Compared with the traditional aided acquisition algorithm,the computation load of this algorithm decreases about 25%.Finally,the relevance of Beidou B1/B2 signals is analyzed,and the dual-frequency coupled tracking algorithm is applied to track the two signals.This algorithm combines the output results of B1 and B2 phase discriminators first,and then inputs the combined results to the loop filter for filtering.Afterwards,the filtered results are transmitted to the carrier NCO to adjust the frequency of generated signals.Finally,the local carriers of B1 and B2 signal are obtained by the loop parameter prediction unit.Compared with the independent tracking algorithm,the tracking sensitivity of proposed algorithm is improved about 3 d B.In this paper,the proposed algorithms speed up the signal acquisition speed and improve the signal tracking sensitivity.And they are beneficial for the software receiver to be implemented on the vehicle embedded platform with limited resources.The research is referable for improving the positioning and navigation performance of driverless cars.