Mathematical Modeling of Guidance Trajectory with a Moving Destination Using Conditionally Markov Modeling (2109.02141v2)
Abstract: A trajectory of a destination-directed moving object (e.g. an aircraft from an origin airport to a destination airport) has three main components: an origin, a destination, and motion in between. We call such a trajectory that end up at the destination \textit{destination-directed trajectory (DDT)}. A class of conditionally Markov (CM) sequences (called CM$\text{L}$) has the following main components: a joint density of two endpoints and a Markov-like evolution law. A CM$\text{L}$ dynamic model can describe the evolution of a DDT but not of a guided object chasing a moving guide. The trajectory of a guided object is called a \textit{guided trajectory (GT)}. Inspired by a CM$\text{L}$ model, this paper proposes a model for a GT with a moving guide. The proposed model reduces to a CM$\text{L}$ model if the guide is not moving. We also study filtering and trajectory prediction based on the proposed model. Simulation results are presented.
Sponsor
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.