Gnss Multipath Mitigation Using Low Complexity Adaptive Equalization Algorithms

The problem of GNSS multipath mitigation is pursued through developing two stochastic-gradient-based adaptive tracking algorithms. Using these techniques, instead of direct estimation of the multipath channel coefficients, the resulting distortion on the correlation function of the received GNSS signal is compensated by passing the correlation function samples through a filter whose coefficients are adaptively adjusted using a feedback signal. An optimum decision block is designed to estimate the LOS parameters from the compensated correlation sequence and produce the control error signal in the decision feedback loop of the delay estimator used to update the compensation filter coefficients. The development of the proposed algorithms in the wavelet domains is then investigated to provide a denoising mechanism and decrease the computational complexity load of the receiver. A set of simulations and real data processing results are presented to compare the performance of the proposed methods in the time and wavelet domains and to compare their performance with conventional delay estimation techniques.