The development of a self-contained, onboard, fully autonomous trajectory guidance tool for spacecraft is presented. To be considered completely autonomous requires the capability to both identify an appropriate startup solution, and then use that solution to target a set of user-defined path and endpoint constraints. To minimize the cost of flight software development and validation, both the generation of the startup solution and the targeting algorithm are designed to be as computationally efficient as possible. This study addresses both the determination of a startup arc and the subsequent targeting process. The first part of the investigation considers the targeting algorithm. Linear targeting through differential corrections is a well-known approach for identifying feasible solutions that meet specified mission and trajectory constraints. However, to date, these methods relied on the assumption that the associated control inputs were impulsive in nature. This research focuses on the theoretical development and numerical validation of a generalized linear targeting algorithm capable of accommodating finite periods of continuous control action for a wide range of applications. Examples are presented to illustrate the general concept and to contrast the performance of this new targeting process against more classical impulsive targeting methods. The second section of the study introduces a novel approach utilizing artificial potential function methods to identify suitable startup solutions. Although common in other types of path planning, these methods have not yet been used for orbital or interplanetary trajectory design, primarily due to their inherent suboptimality. However, results show that this issue can be addressed with relative ease by the targeting algorithm. / text