A Superresolution Multipath Estimation Algorithm for DSSS Systems

Abstract

In direct sequence spread spectrum systems, the multipath interference is known to be one of the most important factors in degrading the measurement accuracy. To resolve this problem, we propose a superresolution multipath estimation method based on waveform replacement and adaptive-filtering. In this method, the continuous pseudorandom noise code autocorrelation waveform of the matched filtering output is first replaced by a designed triangular pulse waveform. Subsequently, a reiterative minimum mean-square error adaptive filtering approach is applied to realize superresolution estimation of multipath parameters. The proposed method can achieve accurate multipath estimation even in complex multipath scenarios containing short-delay multipaths and make a good balance between the computational complexity and the estimation performance of multipath parameters. Simulation results verify the effectiveness of the proposed method.