升空平台相对测量误差对定位精度的影响及定位算法

欧阳晓凤; 曾芳玲; 吕大千; 董天宝; 韩宜静

doi:10.13700/j.bh.1001-5965.2022.0240

升空平台相对测量误差对定位精度的影响及定位算法

doi: 10.13700/j.bh.1001-5965.2022.0240

1.
国防科技大学电子对抗学院，合肥 230037
2.
宇航动力学国家重点实验室，西安 710043

详细信息

通讯作者:
E-mail：zella@ustc.edu

中图分类号: TN953.7
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出版历程
- 收稿日期: 2022-04-12
- 录用日期: 2022-05-27
- 网络出版日期: 2022-06-16
- 整期出版日期: 2024-01-31

Positioning accuracy and localization algorithm with relative measurement errors in blast-off platforms

1.
College of Electronic Engineering，National University of Defense Technology，Hefei 230037，China
2.
The State Key Laboratory of Astronautic Dynamics，Xi’an 710043，China

More Information

Corresponding author: E-mail：zella@ustc.edu

摘要

摘要:
针对精准协同任务下的分布式升空平台高精度相对定位需求，基于超宽带（UWB）测距传感器研究了相对测距与定位模型，对UWB模块在非理想情况下存在的误差因素进行了推导分析，包括天线相位中心误差、测距刷新率和悬停稳定度。在此基础上对噪声成分进行了实测分析与滤波处理：通过Allan方差辨识UWB传感器噪声，并将有色噪声模型及估计参数引入到定位算法量测更新中，通过改进扩展卡尔曼滤波算法实现了分布式升空平台相对定位。仿真结果表明：在相对测量噪声服从非高斯分布情况下，所提算法相较于传统算法位置估计精度提高约23.43%。与传统算法相比，所提算法可减少测量色噪声影响，提高卫星导航拒止环境下的相对定位精度。
- 升空平台 /
- 相对定位 /
- 误差分析 /
- 超宽带传感器 /
- Allan方差
Abstract:
In response to the high-precision relative positioning requirements for precise collaborative operations involving distributed blast-off platforms, this research proposes a relative ranging and positioning model based on ultra wide band (UWB) sensors. It analyzes the error factors and noise components of UWB modules under non-ideal conditions with antenna phase center errors, ranging refresh rates, and hover stability. To improve the overall performance of ranging and positioning, the noise component in UWB measurements is identified and analyzed by Allan variance, and the colored noise model along with estimated parameters are integrated into the measurement update of the positioning algorithm. The relative positioning of distributed blast-off platforms is then obtained through improving the expanded Kalman filter. Simulation experiments show that when the UWB measurement noise follows a non-Gaussian distribution, the position estimation accuracy of the proposed algorithm is 23.43% higher than that of the traditional EKF algorithm. Compared to traditional algorithms, the proposed algorithm reduces the influence of measurement color noise, thereby increasing relative positioning accuracy in satellite navigation-denied environments.
- blast-off platform /
- relative positioning /
- error analysis /
- ultra wide band sensor /
- Allan variance

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图 1 分布式升空平台相对定位原理

Figure 1. Simplified relative motion model of distributed blast-off platform

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图 2 TW-TOF测量原理及信号波形

Figure 2. Measuring principle and signal waveform of TW-TOF

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图 3 双平台测量天线空间关系

Figure 3. Geometric relationship between two-platform measuring antennas

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图 4 位置估计误差与测距刷新率、相对速度的关系

Figure 4. Relationship of position estimation error with ranging refresh rate and relative velocity

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图 5 悬停稳定度测试场景

Figure 5. Test scenario of hovering stability

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图 6 悬停稳定度对UWB测距误差的影响

Figure 6. Effect of hovering stability on UWB ranging bias

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图 7 UWB实测数据Allan方差分析(与白噪声理论值对比)

Figure 7. Allan plots of analysis UWB measurements (compared with theoretical values under white noise)

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图 8 实测数据与模拟数据的Allan方差分析

Figure 8. Allan variance analysis of data measurements and simulation

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图 9 算法复杂度分析

Figure 9. Complexity analysis of proposed algorithm

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图 10 升空平台运动特征仿真

Figure 10. Simulation of motion characteristics of blast-off platform

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图 11 分布式升空平台定位误差分析

Figure 11. Position error analysis of distributed blast-off platforms

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表 1 基于UWB实测数据的Allan方差随机模型参数

Table 1. Parameters of Allan variance random model based on measured UWB data

距离/cm	$ {\sigma _N} $	B	W	$ \sigma_{\mu} $
2500 (LOS)	0.351	0.721	0.543	2.63
3000 (LOS)	0.812	0.564	0.471	4.10
3500 (LOS)	0.637	0.356	0.738	2.85
4000(LOS)	0.545	0.417	0.791	3.96
4500 (LOS)	0.592	0.458	0.427	2.78
5000 (LOS)	0.679	0.673	0.501	3.26
5000(NLOS)	0.609	0.232	1.569	4.76

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表 2 仿真参数设置

Table 2. Simulation parameters

参数	数值
陀螺仪测量误差/ (°)	N(0.001,0.001)
加速度计测量误差/(m·s⁻²)	N(0.001,0.003)
磁力计测量误差/(°)	N(0.02,0.05)
四元数运动模型噪声协方差	0.01
位置过程噪声协方差/m	1
角速率过程噪声协方差/(rad·s⁻¹)	10⁻⁶
线加速度过程噪声协方差/(rad·s⁻²)	10⁻⁶

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