GNSS/IMU/LiDAR fusion positioning research
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摘要: 为提升低成本卫星接收机和惯性测量单元(inertial measurement unit，IMU)条件下传统组合导航定位的抗干扰性和定位精度，本文通过融合GNSS、IMU、激光雷达(laser radar，LiDAR)来提高定位的鲁棒性及定位精度. 在高楼遮挡等复杂环境下由于卫星信号丢失导致卫星定位结果降低，可通过IMU与GNSS的融合提升导航定位的鲁棒性及其精度. 如果卫星信号缺失时间过长，低成本条件下的IMU/GNSS组合定位精度仍不理想，本文提出利用LiDAR里程计输出的位置信息与传统组合导航通过扩展卡尔曼滤波(extended Kalman filter，EKF)进行融合定位. 实验得出：在无遮挡的环境下融合定位标准差(standard deviation，STD)精度较之卫星定位提升53.7%，均方根误差(root mean square error，RMSE)精度提升56%，较之GNSS/IMU组合定位STD精度提升37.9%，RMSE精度提升38.6%. 在有遮挡的环境下融合定位STD精度较之卫星定位提升59.4%，RMSE精度提升71.3%，较之GNSS/IMU组合定位STD精度提升26.3%，RMSE精度提升33.7%.
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关键词:
- 定位 /
- GNSS /
- 惯性测量单元(IMU) /
- 激光雷达(LiDAR) /
- 扩展卡尔曼滤波(EKF)
Abstract: To improve the anti-interference and positioning accuracy of conventional integrated navigation and positioning under the conditions of low-cost satellite receivers and IMU, this paper proposes to fuse GNSS, inertial measurement unit (IMU), and laser radar (LiDAR) to enhance the robustness and accuracy of positioning. In complex environments such as high-rise buildings, where satellite signals are lost, the robustness and accuracy of navigation and positioning can be improved by fusing IMU and GNSS. However, if the satellite signal loss time is too long, the IMU/GNSS integrated positioning accuracy under low-cost conditions is still not ideal. This paper proposes to use the position information output by the LiDAR odometer and the conventional integrated navigation to perform fusion positioning through extended Kalman filter (EKF). The experiments show that in the unobstructed environment, the fusion positioning standard deviation (STD) accuracy is 53.7% higher than the satellite positioning, the root mean square error (RMSE) accuracy is 56% higher, the fusion positioning STD accuracy is 37.9% higher than the GNSS/IMU integrated positioning, and the RMSE accuracy is 38.6% higher. In the obstructed environment, the fusion positioning STD accuracy is 59.4% higher than the satellite positioning, the RMSE accuracy is 71.3% higher, the fusion positioning STD accuracy is 26.3% higher than the GNSS/IMU integrated positioning, and the RMSE accuracy is 33.7% higher.-
Key words:
- position /
- GNSS /
- inertial measurement unit (IMU) /
- laser radar (LiDAR) /
- extended Kalman filter (EKF)
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表 1 产品参数及其数据
产品 参数 技术数据 IMU 量程 $ \left(A\right)\pm 2~\pm 16\;\mathrm{g} $ $ \left(G\right)\pm 125~\pm 2000\;\mathrm{d}\mathrm{p}\mathrm{s} $ 零偏 $ \left(A\right)\pm 20\;\mathrm{m}\mathrm{g} $ $ \left(G\right)\pm 0.5\;\mathrm{d}\mathrm{p}\mathrm{s} $ 灵敏度误差 $ \left(A\right)\pm 0.4 \text{%} $ $ \left(G\right)\pm 0.4 \text{%} $ 噪声密度 $ \left(A\right)\pm 160\; \text{µ} \mathrm{g}\surd \mathrm{H}\mathrm{z} $ $ \left(G\right)\pm 0.008\;\mathrm{d}\mathrm{p}\mathrm{s}/\surd \mathrm{H}\mathrm{z} $ 卫星接收机 E向定位精度(SPP) 4.904 6 m N向定位精度(SPP) 6.003 3 m U向定位精度(SPP) 12.939 0 m LiDAR 定位精度 2.833 3 m 
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表 2 导航定位坐标解算STD及其精度提升
环境 实验次序 卫星定位/m GNSS/IMU
组合定位/mGNSS/IMU/LiDAR
融合定位/m精度提升
(卫星定位)/%精度提升
(组合定位)/%无遮挡 第一次 4.345 1 3.624 7 1.982 2 54.4 45.3 第二次 4.209 3 4.236 6 2.932 5 30.3 30.8 第三次 4.479 7 2.525 0 1.710 8 61.8 32.2 第四次 5.176 8 3.181 9 1.806 8 65.1 43.2 平均值 4.552 7 3.392 1 2.108 1 53.7 37.9 有遮挡 第五次 8.276 1 3.606 9 2.643 7 68.1 26.7 第六次 6.775 4 3.420 4 2.766 8 59.2 19.1 第七次 3.788 4 3.345 8 2.237 9 40.9 33.1 平均值 6.280 0 3.457 7 2.549 5 59.4 26.3
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表 3 导航定位坐标解算RMSE及其精度提升
环境 实验次序 卫星定位/m GNSS/IMU
组合定位/mGNSS/IMU/LiDAR
融合定位/m精度提升
(卫星定位)/%精度提升
(组合定位)/%无遮挡 第一次 9.163 4 4.783 8 2.522 7 72.5 47.3 第二次 6.638 4 5.086 9 3.968 8 40.2 22.0 第三次 7.198 0 6.704 7 4.262 5 40.8 36.4 第四次 6.264 2 4.405 5 2.123 0 66.1 51.8 平均值 7.316 0 5.245 2 3.219 3 56.0 38.6 有遮挡 第五次 14.526 1 4.456 3 2.680 1 81.5 39.9 第六次 12.223 1 6.028 3 4.789 0 60.8 20.6 第七次 14.390 7 7.330 5 4.341 1 69.8 40.8 平均值 13.713 3 5.938 4 3.936 7 71.3 33.7
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