GNSS Multipath Error Reduction in Harsh Environments

The performance of code delay and carrier phase estimation of a GNSS signal propagated in an urban or indoor environment is highly degraded by multipath when the conventional multipath mitigation techniques such as narrow correlator and double delta correlator are applied. These conventional techniques rely on the value of the delay corresponding to the peak of the autocorrelation function. In this paper, a modified iterative Projection Onto Convex Set (POCS) algorithm is discussed that estimates the Channel Impulse Response (CIR) using an adaptive threshold to remove the spurious noise peaks at each iteration. Herein, an adaptive window around the correlation peak is applied that limits the number of samples at the input of the estimation process to increase the robustness of the algorithm to noise. After estimating the CIR, the proposed algorithm estimates the LOS time of arrival from the position of its first non-zero element that passes a certain threshold. Moreover, the phase offsets are computed from the real and imaginary parts of the selected element by using an appropriate phase discriminator function. The performance of the proposed algorithm is compared with the conventional POCS and double delta correlator techniques. Simulation results indicate that the modified POCS algorithm considerably outperforms the double delta correlator technique especially when the number of paths is large (e.g. a specular channel with 7 to 10 paths). When the LOS signal does not exist, the proposed algorithm selects the first received secondary path to estimate the code delay. The performance of the proposed algorithm is tested through simulation and an actual data collection is conducted in an urban environment.