This paper presents a novel search-path optimization method for moving target search by an aerial vehicle, applicable to realistically sized search areas. For such missions, long endurance vehicles are needed, which are usually fixed-winged. The proposed method accounts for flight kinematics of fixed-wing and rotary-wing aerial vehicles. It additionally accounts for movements of the target, considerably increasing complexity of search-path optimization, compared to a static target. The objective is to maximize the probability to detect a conditionally deterministic moving target within a given time period. We propose a first K-step-lookahead planning method that takes flight kinematic constraints into account and in which the target and platform state space are heterogeneous. It consists of a binary integer linear program that yields a physically feasible search-path, while maximizing the probability of detection. It is based on the Max-K-Coverage problem, as it selects K waypoints while maximizing the probability that a target is within the field of view of a platform at one of these waypoints. This K-step-lookahead planning method is embedded in an iterative framework, where the probability of overlooking a target is fed back to the controller after observations are made. Simulations show the applicability and effectiveness of this method.
