PN code acquisition using signed-rank-based non-parametric detector in a multiplicative noise model

Abstract

Multiplicative noise is known to be useful in modelling an environment that is difficult to describe with an additive noise model. In this article, signed-rank-based non-parametric detectors are used for pseudonoise (PN) code acquisition in multiplicative noise. First, a locally optimum (LO) detector based on the signs and ranks of observations is derived, and then the locally suboptimum rank (LSR) detector is proposed by using approximate score functions. The finite sample-size performance of the LSR detector is considered. Numerical results show that the LSR detector asymptotically has almost the same performance as the LO detector for multiplicative noise.