This paper presents the results of up to date investigations in the field of Obstacle Tracking System for Sense and Avoid applications of Unmanned Aerial Systems. In particular it highlights the most recent trends in this field, such as the adoption of Advanced Multi Sensor Data Fusion techniques in order to increase the awareness on the information of a collision threat and the adoption of lightweight onboard system architectures that can meet the requirements for installation onboard small Unmanned Aerial Systems. As a result of the experience with flight testing for a prototypical Sense and Avoid System developed within the framework of a project of the Italian Aerospace Research Centre, some advanced solutions have been proposed to solve the above reported issues. In particular, the adoption of Particle Filtering for realizing Multi-Sensor Data Fusion has been considered in order to get reliable and accurate estimates of the collision threat, such increasing flight awareness. A customized version of the Particle Filter has been developed and tested by exploiting data acquired during flight tests. Moreover, a specific study has been carried out considering the issues for the realization of an adequate Sense and Avoid system for small Unmanned Aerial System. An integrated configuration that includes ADS-B and Electro Optical sensor has been identified as the most effective solutions standing Sense and Avoid requirements. This solution requires that a great effort is put on software both in terms of data fusion algorithms and real time image processing. The results of this study are described at the end of the paper.
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