Estimation for Kinematic Models
Yaakov Bar‐Shalom, X.‐Rong Li, Thiagalingam T. Kirubarajan · 2002
This chapter discusses a class of widely used models derived from simple equations of motion—constant velocity and constant acceleration. The discrete-time kinematic model obtained by discretizing the continuous-time state space representation driven by white noise is presented. The state model defined directly in discrete time using a piecewise constant white random sequence as process noise is presented. Explicit filters for noiseless kinematic models are explained and explicit steady-state filters for noisy kinematic models are derived. The statistical characterization of the process noise is a key filter design parameter, which is discussed in detail. Subsequently, one important aspect of tracking system design—selection of the sampling frequency, i.e., the revisit rate—is discussed. The models are presented for a single coordinate, and some intuitive insight into filter design is presented. A problem solving section appears at the end of the chapter.