Multipath Mitigation Using a Dual-Polarization Antenna�How Good Can We Get?

Abstract

As we all kwon that multipath (MP) effect is one of the error sources that degrades the pseudorange measurement quality in Global Navigation Satellite System (GNSS) receivers despite the effort by researchers and manufacturers to reduce it. Among all types of multipath, the short delay multipath is most challenging for receiver baseband signal processing techniques that reduce the multipath bias using the correlation functions within the receiver tracking loop. When the line-of-sight (LOS) and MP signals are highly correlated in the correlation domain, other characteristics of LOS and MP signals can be used to distinguish them, e.g., the difference in the angle of arrival. However, the exploitation of spatial diversity results in bulky receiver antenna and complex hardware. In the past decade, the dual-polarization antenna has become a cost efficient way to add another degree of freedom to distinguish the LOS signal from the MP signal. Lots of multipath mitigation techniques based on dual-polarization antennas have been proposed and all of them report benefits from using dual-polarization antennas to mitigate multipath. Due to the unpredictability of multipath, the signals received by a dual-polarization antenna are not always qualified to improve multipath mitigation performance. However, few studies talk about the effective condition under which the multipath mitigation based on a dual-polarization antenna can outperform that based on a single-polarization antenna. In this paper we analyze the characteristics of the signal received by a dual-polarization antenna and classify them into different cases on which we use the Maximum Likelihood Estimation (MLE) to evaluate the theoretical performance of the dual-polarization multipath mitigation. Based on the comparison of MLE using different received signal models in different multipath environments, we find the effective condition and dual-polarization antenna’s superior capability in mitigating short delay multipath. After that we modify the received signal model concerning the effective condition and derive the Cramer Rao Lower Bound (CRLB) of the TOA estimation of the LOS signal based on the simplified model. Finally the simulation of the modified ML estimator verifies our theory.