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An Integrated Navigation System of NGIMU/ GPS Using a Fuzzy Logic Adaptive Kalman Filter

机译:使用模糊逻辑Adaptive Kalman滤波器的Ngimu / GPS集成导航系统

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The Non-gyro inertial measurement unit (NGIMU) uses only accel-erometers replacing gyroscopes to compute the motion of a moving body. In a NGIMU system, an inevitable accumulation error of navigation parameters is produced due to the existence of the dynamic noise of the accelerometer output. When designing an integrated navigation system, which is based on a proposed nine-configuration NGIMU and a single antenna Global Positioning System (GPS) by using the conventional Kalman filter (CKF), the filtering results are divergent because of the complicity of the system measurement noise. So a fuzzy logic adaptive Kalman filter (FLAKF) is applied in the design of NGIMU/GPS. The FLAKF optimizes the CKF by detecting the bias in the measurement and prevents the divergence of the CKF. A simulation case for estimating the position and the velocity is investigated by this approach. Results verify the feasibility of the FLAKF.
机译:非陀螺惯性测量单元(Ngimu)仅使用替换陀螺仪来计算移动体的运动来计算移动体的运动。在NGIMU系统中,由于加速度计输出的动态噪声存在,产生导航参数的不可避免的累积误差。在设计基于提出的九个配置Ngimu和单个天线全球定位系统(GPS)的集成导航系统时,通过使用传统的卡尔曼滤波器(CKF),由于系统测量的共同性,滤波结果是发散的噪音。因此,在Ngimu / GPS的设计中应用了模糊逻辑Adaptive Kalman滤波器(Flakf)。通过检测测量中的偏差并防止CKF的分歧来优化CKF。通过这种方法研究了估计位置和速度的模拟案例。结果验证了Flakf的可行性。

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