Robust tracking of weak GPS signals in multipath and jamming environments

In this paper, we address the problem global positioning system (GPS) signals tracking in low signal-to-noise ratio (SNR) and multipath plus interference environments using a two-step approach: a block-averaging pre-processing (BAP) which converts the zero-mean interferences to colored Gaussian noise and a maximum likelihood (ML) based algorithm combined with a whitening transform. We apply the recently proposed BAP technique to improve the SNR. For code tracking with multipath mitigation, we exploit the fact that during a period with no data bit edges, the propagation delay causes only a circular shift to the C/A code block. This allows the decomposition of the averaged data vector into a constant C/A code component plus an undesired signal component. An efficient temporal whitening transform is derived from the sample covariance matrix and applied to suppress strong colored interferers, rendering the ML estimation problem of the multipath parameters tractable. A computationally efficient procedure for solving the complex ML optimization problem is considered using a finite difference maximization technique. By estimating the multipath signals and subtracting their contributions in a sequential scheme, the code synchronization is achieved. The resulting robust ML (RML) tracking procedure is more efficient in mitigating multipath and non-Gaussian interferences. The performance of the developed RML receiver is evaluated through computer simulations to show its superiority over that of narrow correlator and MEDLL approach.