Application of Singer Tracking Model in Adaptive GPS Signal Tracking Algorithm

In the GPS signal tracking of cascade deeply coupled GPS/SINS system, the model of baseband pre-filter has strong nonlinearity while the correlator outputs, I/Q signals, is taken as observation directly. To reduce the complexity of deeply coupled GPS/SINS, the phase discriminator outputs are selected as the baseband pre-filter measurements. The major disadvantage of this filter model is not precise enough to obtain high-accuracy estimation under the condition of High Dynamic. In this case, the Singer model based adaptive GPS signal tracking algorithm is proposed. The Singer target tracking model is employed to improve the precision of state equation. And the Sage-Husa adaptive filtering is adopted to improve filter accuracy via estimating and adjusting the model noise online. The simulation results show that the proposed method has strong capability to track GPS signals stably even in the high dynamic case. Compared with the traditional method, the filter above inhibits the fluctuation of tracking signal error effectively with less computation. It should be a promised method for signal tracking application.