The book identifies several future research directions and challenges for developing MSFF algorithms under constrained network environments with censored data. Key challenges include:
- Accurately characterizing censored measurements, as finding suitable random variables and equivalent measurement models is complex.
- Developing fusion rules that achieve optimal performance with moderate computation burden under multiple network-induced phenomena.
- Examining the performance of recursive filtering algorithms using the original Tobit measurement model, considering network-induced phenomena.
- Studying MSFF with censored measurements over sensor and complex networks, considering the challenges of topology structure and communication constraints.
- Investigating the impact of malicious attacks on MSFF frameworks and performance under constrained network environments.
- Developing data-based MSFF schemes or improving existing model-based fusion schemes for unfamiliar or unmodeled engineering systems.