Analysis of Acquisition Algorithms for the BeiDou B1I signal in Resource-Constrained Implementations

Abstract

The purpose of this thesis is to evaluate different acquisition algorithms for the BeiDou (BDS) B1I signal using a common GPS L1 C/A algorithm as reference. The selection criteria for the algorithms focuses on low resource requirements as well as implementation flexibility and potentially beneficial features. The reasoning behind this is that a resource-constrained device might not have the space for two large implementations of both the B1I and the L1 C/A acquisition algorithms if they are two separate, and not very resource efficient, implementations. Thus, a shared implementation could significantly decrease resource usage. In addition to evaluating different algorithms, the second main purpose of this thesis is to provide a detailed analysis on the features, complexity, memory requirements, and sensitivity performance of the algorithms. Five algorithms are selected to be analyzed in these aspects. The algorithms are implemented in a Python-based simulator created by the author. Monte Carlo simulations are performed with different search parameters to determine the effect on sensitivity performance of the different algorithm optimizations. Suitable algorithms for resource-constrained devices were found. A detailed description of the algorithm implementations, along with an analysis of memory requirements has been provided with the intent of presenting a feasible requirement estimates for the practical implementation of the selected acquisition algorithm in the context of resource-constrained IoT devices.