| The Bei Dou(BD)receiver is used as the user terminal in the navigation system and the location information is obtained through processing the received satellite signals.The acquisition and tracking,as the part of signal processing,can directly affect the performance of the receiver.Their main tasks are to get the carrier frequency and the code phase and remove them from the received signal to demodulate accurate navigation information.In general,the signal-to-noise(SNR)of the intermediate frequency(IF)signal through the RF front end is low,so this paper will research the acquisition and tracking algorithms about the weak BD signal.The coherent,incoherent and differential coherent integration algorithms are usually introduced to capture weak signal instead of traditional time-domain serial and frequency-domain parallel acquisition algorithms.It is known that the coherent and the differential coherent integration can obviously improve the SNR gain compared with the incoherent integration algorithm.However,the integration time is limited by the navigation data transition.In this paper,a differential coherent integration based on data-transition estimation and a coherent integration based on data-transition elimination algorithms are proposed.The first one estimates the position of the data block that has data transition by differential coherent operation and then removes it while the latter supplies with zero after the local code in order to eliminate data transition in cycle correlation perspective.It can be seen that both can capture the weak signal in the case of data transition and the latter is as low as-38dB and has the higher acquisition probability than the former through simulation.When the coarse carrier frequency and code phase are captured,the further tracking is needed which is achieved by tracking loop based on phase locked loop(PLL).In the same way,the traditional tracking loop is easy to cause lock-lose when dealing with the weak signal.So the Kalman filter is used instead of the loop filter to estimate the state vector in the BD signal but it is diverged due to the influence of the fixed state model in the dynamic changing loop.In this paper,an adaptive Kalman algorithm is proposed to solve this problem which can estimate the noise variance in real time by the innovation sequence,and the adaptive fading factor is introduced to increase the filtering gain of Kalman,thus improving the weight of the measurement vector to correct the estimation of the state vector and restraining the divergence.It is proved that the Kalman filter algorithm can track the weak signal.while the adaptive Kalman filter proposed in this paper can track as low as-35dB BD signal compared to the traditional one,that is to say it has better performance. |
