  This paper presents a multi-sensor architecture with an adaptive multi-sensor
management system suitable for control and navigation of autonomous maritime
vessels in hazy and poor-visibility conditions. This architecture resides in
the autonomous maritime vessels. It augments the data from on-board imaging
sensors and weather sensors with the AIS data and weather data from sensors on
other vessels and the on-shore vessel traffic surveillance system. The combined
data is analyzed using computational intelligence and data analytics to
determine suitable course of action while utilizing historically learnt
knowledge and performing live learning from the current situation. Such
framework is expected to be useful in diverse weather conditions and shall be a
useful architecture to provide autonomy to maritime vessels.
