基于自适应卡尔曼滤波的超宽带室内定位系统

The UWB Indoor Positioning System Based on Adaptive Kalman Filtering

超宽带(Ultra Wideband,UWB)室内定位技术以其抗干扰、抗多径传播能力强以及低功耗、低成本、高精度等特点,得到了越来越多人的关注.该文针对传统的卡尔曼滤波算法在运用于室内UWB系统定位时,由于初始参数不定以及在环境变化或系统运行偏差后定位误差增大等问题,提出了一种自适应卡尔曼滤波算法.该算法可以在定位中自动校准参数,从而提高了定位系统的可靠性和定位精度.论文设计了以DW1000射频芯片为基础的室内定位系统,并对各种定位算法进行测试.实验结果表明:融合了自适应卡尔曼滤波的定位算法,在静态定位中可以提高定位稳定性,而在动态定位中则可以提高定位精度.系统定位精度达到10cm以内,为实际应用奠定了良好的基础.

The Indoor Positioning System（IPS）based on Ultra Wide-band（UWB）has gained more and more attention due to its anti-interference,anti-multipath transmission capacity,low power consumption,low cost and high precision.When the traditional Kalman filter algorithm is applied to IPS,the positioning error will increase because of the uncertain initial parameters and the variation of environment parameters.An adaptive Kalman filtering algorithm is proposed in this paper,it can automatically calibrate the parameters in positioning process and improve the reliability and positioning accuracy of the positioning system.An IPS is designed based on DW1000 in this paper and various location algorithms are tested.The experimental results show that the positioning algorithm fused the adaptive Kalman filtering can improve the positioning stability in static positioning and enhance the positioning accuracy in dynamic positioning.The positioning accuracy reaches up to 10 cm,which lays a good foundation for practical application.