With the rise of digitalization, AI and modern data communication, engineering is increasingly challenged by the complexity of systems-of-systems, in which perception sensors have their own processing mechanism, information is merged at some centric entity, and cross-platform exchange of data is conceptualized in a holistic approach. Therefore, distributed architectures for data fusion, state estimation, and multi target tracking have been becoming increasingly important. The use of multiple sensors to perceive and compute the situational awareness picture leads to the generation of vast amounts of data, which need to be filtered, enriched, interpreted, and evaluated. This becomes infeasible without the notion of distributed algorithms.

• Chapter 1: Introduction
• Chapter 2: Stochastic motion
• Chapter 3: Bayesian state estimation and target tracking
• Chapter 4: Trajectory estimation
• Chapter 5: Track-to-track fusion with known correlations
• Chapter 6: Track-to-track fusion with unknown correlations
• Chapter 7: Distributed Kalman filter
• Chapter 8: Track-to-track association and distributed detection
• Appendix A
• Appendix B