Design of a Novel PN Code Based on Genetic Algorithm for Rapid GNSS Signal Acquisition

Abstract

Although long pseudo-noise (PN) codes offer highly accurate positioning performance in global navigation satellite systems, their plenty of code phases essentially require a long code phase acquisition time. By splitting the PN code into multiple blocks and stacking the blocks, the folding scans multiple code phases simultaneously, thus reducing the acquisition time significantly. However, the stacking of the split blocks distorts the correlation property of the PN code, thus limiting the use of more folding for faster acquisition. Using the genetic algorithm (GA), in this paper, we design a PN code that is robust to the distortion effect caused by the folding. We first set several randomly generated binary codes as the initial genes, then evaluate the genes by simulating the mean acquisition times (MATs) of the genes. Subsequently, the GA operations including the selection, crossover, and mutation are repeatedly performed to obtain a more evolved gene. In numerical results, it is confirmed that the proposed PN code provides the reductions of 8.3% and 8.0% from the MAT and the normalized mean acquisition error (NMAE) of the conventional PN codes, respectively.