An adaptive fusion IMM algorithm for autonomous radio carrier tracking

An adaptive fusion algorithm based on interactive multiple model (IMM) is developed to track the signal with unknown signal to noise ratio (SNR) information for the technique of deep space autonomous radio receivers. The new algorithm if used to adjust the noise variances of the IMM estimator adaptively according to the SNR of the actual environment, so that it can normally track the signal with unknown SNR information and ensure that the frequency tracking accuracy is almost not affected by initial noise variances. Based on the analysis of the system convergence attribute, an adaptive adjustment strategy of model probabilities is adopted to adjust the probability of each sub module in the IMM system adaptively according to the system convergence criterion. By doing this, the new algorithm introduced here ensures the system convergence and improves the tracking accuracy. The convergence time of the adaptive fusion IMM algorithm is shorter by a half than that of Sage-Husa adaptive filter algorithm used widely.