Abstract
This presentation explores the impact of increasing active sonar beamwidth on the infotaxis search strategy (Vergassola, 2007) on the length of searches to find targets. Our model discretizes the search space into a one-dimensional grid. The associated state vector contains the probability that each grid cell contains the target. The search is modeled as a three-step iterative process: choosing the next sensing location (search strategy), measuring the environment, and Bayesian update of the state vector. The measurement is simplified as a Binary Hypothesis Test for the cell(s) within the sonar beam. Infotaxis search strategy is considered which maximizes the expected rate of information gain. Keith (2022) previously focused on a narrow sonar beam measuring a single grid cell. Increasing the beamwidth measures several grid cells at once, requiring a revised Bayesian update rule. The detection probability within the wider beam decreases moving away from the main response axis modeling the reduced power transmitted in off-axis directions. Simulations comparing different beamwidth infotaxis searches found that increasing the beamwidth allows infotaxis to reduce the expected number of iterations to find the target. [Funded by ONR MURI Program.]