Weighted Decentralized Information Filter for Collaborative Air-Ground Target Geolocation in Large Outdoor Environments

The unmanned air-ground vehicle system has been successfully applied in civil and military domains. Collaborative vision-based target geolocation with this system can provide an enduring and accurate estimate of moving target state. Traditional decentralized information filter (DIF) treated each platform in the system identically. In fact, the observation capabilities of aerial and ground platform typically differ from each other due to different configurations and changing sensor noises. Without considering these differences, the resources of each platform cannot be fully utilized. To handle the issue, we develop a weighted DIF for geolocating of moving targets via air-ground collaboration. Specifically, it can produce a weighted factor autonomously for each platform based on the similarity of tracks from the air-ground system. Then, it is able to have more accurate global estimates than the traditional filter. Finally, simulation experiments and actual tests are conducted and the results are presented to validate the efficacy of the proposed method. Additional details can be seen in our video submission.