A cooperative navigation architecture for the search and recognition of targets using aerial and ground vehicles is proposed in this paper. The architecture allows to manage aerial and ground vehicles to autonomously perform different tasks in an independent or cooperative way. For our application, two main tasks are conceived; aerial monitoring of a surface to search for targets, and target ground recognition. In the target aerial detection task, the aerial drone tracks autonomously a trajectory, computed to cover all the surface to monitoring, to search for targets using vision algorithms. Once one of them is detected its relative position is sent to the cooperative architecture. After the aerial drone has covered the entire area, the architecture computes and assigns to each ground vehicle the closest target found. Then, each ground vehicle navigates autonomously avoiding obstacles (if presents) to its assigned target. For verifying the success of the mission, the aerial vehicle flies following the dynamic center of mass of the ground vehicles. Real-time experiments are carried out to validate the proposed architecture. Main results, depicted in some graphs, corroborate the good performance in closed loop.