Abstract

In order to decrease the casualties, monitor the real-time motion and safety of the fireman in fire scene, an accurate, efficient and low-cost attitude detector is designed. To monitor the attitude angle in real time, the extend Kalman filter for attitude detector based on quaternion is presented internally. To improve the accuracy detector uses the three-axis MEMS gyroscope with range of 1200 ° / s, and sensor data is processed by using a dynamic zero-calibration method and a configurable Parks-McClellan window FIR low-pass filter. The three-axis MEMS accelerometer and compass are also used. In consideration of the compensation of the incline the affect of soft and hard magnet, and the centripetal force, automatic calibration system is designed to be adapted in different environment to guarantee the dynamic correction. At the same time, detector integrates the wireless radio frequency technology and the OpenGL representation of the real-time human motion in 3D are also given. The results of experiment show that the heading and attitude data computed from the accelerometers and magnetometers is used for compensating the drift of gyroscopes, and the dynamic accuracy is controlled within 2 degree, meanwhile, the static accuracy is no more than 0.5 degree. Through the test of principle prototype, the feasibility and stability of the attitude detector are also demonstrated.

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