无人机侦察多目标实时定位技术研究

蔡明兵; 刘晶红; 徐芳

doi:10.3788/CO.20181105.0812

无人机侦察多目标实时定位技术研究

doi: 10.3788/CO.20181105.0812

蔡明兵^{1, 2,},
刘晶红^1, ,,
徐芳^{1, 2}

1.
中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
2.
中国科学院大学, 北京 100049

基金项目:

吉林省重大科技攻关项目 11ZDGG001

详细信息

作者简介:
蔡明兵(1990-), 男, 山东潍坊人, 硕士研究生, 主要从事导航定位方面的研究。E-mail:1617335036@qq.com

刘晶红(1967—)，女，吉林长春人，研究员，博士生导师，主要从事机载光电成像与测量技术方面的研究。E-mail：liu1577@126.com

中图分类号: V279⁺
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- 被引次数: 0
出版历程
- 收稿日期: 2017-12-26
- 修回日期: 2018-02-15
- 刊出日期: 2018-10-01

Multi-targets real-time location technology for UAV reconnaissance

CAI Ming-bing^{1, 2
,},
LIU Jing-hong^{1
, ,},
XU Fang^{1, 2}

1.
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China

Funds:

Jilin Provincial Major Scientific Research Project of China 11ZDGG001

More Information

Corresponding author: LIU Jing-hong, E-mail:liu1577@126.com

摘要

摘要: 目标定位是无人机侦察系统中至关重要一步。为增强无人机侦察目标定位的实时性、提高定位精度及侦察效率，提出一种多目标实时定位的方法，建立主次目标定位几何关系及坐标转换模型，结合已知数据信息求取各目标大地坐标，并用蒙特卡洛法分析目标定位误差。最后，基于即将组网成功"北斗二代"卫星导航系统对无人机空中定位，同时采用递归最小二乘算法滤波处理，提高了目标定位精度。研究及实验结果表明，北斗导航定位能够有效提高无人机空中定位精度，且有望达到厘米级精度，同时采用RLS滤波处理能使目标定位精度提高10 m左右。该方法能够有效增强无人机定位实时性，提高定位精度及侦察效率。
- 无人机侦察定位 /
- 多目标实时定位 /
- 北斗二代 /
- 蒙特卡洛法
Abstract: Target location is a crucial step in UAV reconnaissance system. In order to enhance the real-time performance of UAV reconnaissance target location and improve location precision, an effective multi-target real-time location method is proposed, which establishes the primary and secondary target location geometric relationship and coordinate transformation model, and combines known data to obtain each target geodetic coordinates, as well as analyzes target location error through Monte Carlo method. Finally, based on the upcoming successful establishment of the Beidou Ⅱ satellite navigation system for the aerial positioning of the UAV, and the filter processing using the Recursive Least Squares algorithm, the target location accuracy is improved. The research and experimental results show that Beidou Ⅱ navigation positioning can effectively improve the aerial positioning accuracy of the UAV, and it is expected to achieve centimeter-level accuracy. At the same time, the RLS filter processing can improve the target positioning accuracy by about 10 m. It is concluded that this method can effectively enhance the real-time positioning of UAVs, improve positioning accuracy and reconnaissance efficiency.
- UAV Reconnaissance target location /
- Multi-targets real-time location /
- Beidou II /
- Monte Carlo method

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图 1 多目标自主定位系统组成示意图

Figure 1. Sketch of multi-target self-determination system

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图 2 各坐标系的定义及其相互关系示意图

Figure 2. Schematic diagram of definition of the coordinate system and their mutual relations

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图 3 目标自主定位的坐标转换流程

Figure 3. Process of self-determination orientation coordinate conversion

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图 4 多目标定位模型

Figure 4. Model of multi-target orientation

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图 5 坐标转换流程

Figure 5. Process of coordinate conversion

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图 6 北斗MEO卫星仿真图

Figure 6. Simulation figure of BDS-MEO

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图 7 北斗仿真定位误差

Figure 7. Localization errors of BDS

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图 8 RLS滤波后的定位结果

Figure 8. Localization results after RLS filtering

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图 9 RLS滤波后的定位误差

Figure 9. Plane localization errors after RLS filtering

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图 10 RLS滤波后的高程定位误差

Figure 10. Altitude localization errors after RLS filtering

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表 1 多目标定位误差

Table 1. Error of multi-target location

目标	经度定位误差/(°)	纬度定位误差/(°)	大地高定位误差/m	平面定位误差/m
主目标	0.000 103 4	0.000 200 6	21.64	49.89
次目标1	0.000 145 6	0.000 217 2	22.47	82.82
次目标2	0.000 111 9	0.000 203 7	19.89	70.46

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表 2 RLS算法流程

Table 2. Flowchart of RLS algorithm

Algorithm RLS Filter:
Input：x_k, k=1, 2, …, t;
Initialize：A_N= I_1×1;
k=1, b_N=[ A_N^T A_N x_k];
P_N=()^-1;
X_k=P_N A_N^T b_N;
And k=2, a_N1= I_1×1
If k≤t then
P_N1= P_N- P_N a_N1^T a_N1 P_N/(1+ a_N1 P_N a_N1^T);
A_N1=[ A_N a_N1]^T;
b_N1=[ b_N b_N1]^T;
X_k= P_N1 A_N1^T b_N1;
else if
P_N= P_N1；
A_N= A_N1;
b_N= b_N1;
k=k+1, b_N1=[ x_k];
return X_k

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表 3 RLS滤波后多目标定位误差

Table 3. Errors of multi-target location after RLS filter

目标	经度定位误差/(°)	纬度定位误差/(°)	大地高定位误差/m	平面定位误差/m
主目标	0.000 093 4	0.000 191 6	9.64	23.06
次目标1	0.000 120 9	0.000 202 6	11.55	70.46
次目标2	0.000 105 3	0.000 207 1	10.63	62.94

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