An integrated micro attitude heading reference system(MAHRS) was researched for micro aerial vehicles (MAV) based on the MEMS gyroscopes

accelerometers

and magnetic-sensors. Due to the fact that the traditional algorithm can not keep the attitude of MUAV accurate during a long-time maneuvering

a PR adaptive attitude estimation filtering algorithm with low-cost multi-sensor for MAHRS was presented. Firstly

this algorithm modeled the acceleration and magnetic-disturbances and took them into state equation

in this way the algorithm could maintain the attitude accurate during a long-time maneuvering; Secondly

this algorithm adopted the federated filter mode to reduce the impacts between acceleration and magnetic disturbance in order to improve the precision and reliability; Thirdly

this algorithm made the estimation variance (P) and measurement variance (R) adaptive to remain steady during different maneuvering states. Compared with other different algorithms which were used for the MAHRS

the simulation results showed that this algorithm presented was more accurate and reliable than other algorithms during various maneuvering states.