Jump-diffusion algorithm for multiple target recognition using laser radar range data
Aaron D. Lanterman · Optical Engineering · 2001
INTRODUCTION Many automatic target recognition (ATR) algorithms are intimately tied to the particular sensor they are designed for, and are not readily adapted to other kinds of sensors. Grenander's pattern theory 1--3 seeks a conceptual separation between the underlying representation of a scene, the sensors used to observe that scene, and the algorithm used to perform inference using the underlying representation and the sensor model. In this paradigm, a hypothesized scene, simulated from the characteristics of the hypothesized scene elements, is compared to the collected data by a likelihood function based on sensor statistics. The likelihood is combined with prior knowledge to form a Bayesian posterior distribution. One can explore di#erent algorithms which exploit the same underlying representation and sensor model to determine which algorithm is the most e#cient. Similarly, by employing a common representation, a particular algorithm designed for one sen