基于方位多假设的单基线干涉仪定位方法

邢怀玺; 吴华; 陈游; 张景轩

doi:10.13700/j.bh.1001-5965.2020.0074

基于方位多假设的单基线干涉仪定位方法

doi: 10.13700/j.bh.1001-5965.2020.0074

邢怀玺¹,
吴华¹,
陈游^1, ,,
张景轩²

1.
空军工程大学航空工程学院, 西安 710038
2.
合肥职业技术学院汽车工程学院, 合肥 238000

详细信息

作者简介:
邢怀玺男, 硕士研究生。主要研究方向:信息对抗理论与技术

陈游男, 博士, 讲师。主要研究方向:信息对抗理论与技术

通讯作者:
陈游, E-mail: chenyousky@163.com

中图分类号: TN971
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- 文章访问数: 406
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- PDF下载量: 33
- 被引次数: 0
出版历程
- 收稿日期: 2020-03-02
- 录用日期: 2020-06-29
- 网络出版日期: 2021-05-20

Single-baseline interferometer positioning method based on azimuth multiple hypothesis

1.
Aeronautics Engineering College, Air Force Engineering University, Xi'an 710038, China
2.
Department of Automotive Engineering, Hefei Technology College, Hefei 238000, China

More Information

Corresponding author: CHEN Y, E-mail:chenyousky@163.com

摘要

摘要:
为了解决机载单站无源定位系统中一维单基线干涉仪测量相位差信息的模糊问题，改进仅利用相位差变化率定位方法，将模糊相位差作为有效的定位参数，提出一种基于方位多假设的单基线干涉仪定位方法。利用模糊相位差和相位差变化率初始化辐射源目标的可能距离方位信息，并通过高斯-扩展卡尔曼滤波（GS-EKF）算法解算辐射源目标位置。所提方法克服了仅利用相位差变化率定位受观测平台机动影响的缺陷，有效缩短了定位时间，同时不必考虑解相位模糊，定位性能均优于仅利用相位差或相位差变化率的定位方法，在实际工程运用中可以降低设备复杂度和成本。
- 无源定位 /
- 单基线 /
- 相位差 /
- 相位差变化率 /
- 高斯-扩展卡尔曼滤波(GS-EKF)
Abstract:
In order to solve the problem of ambiguity of phase difference information measured by one-dimensional single-baseline interferometer in an airborne single-station passive positioning system, the positioning method that measures only the phase difference change rate is improved, and the fuzzy phase difference is used as an effective positioning parameter. And a single-baseline interferometer phase measurement and positioning method based on azimuth multiple hypotheses is proposed. The possible distance and azimuth information of the radiation source target is initialized using the fuzzy phase difference and the phase difference change rate, and the target location of the radiation source is solved by the Gauss-Extended Kalman Filter (GS-EKF) algorithm. This method overcomes the shortcomings of using only the phase difference change rate to locate the impact of the maneuver of the observation platform, effectively shortens the positioning time, and does not need to consider the solution of phase ambiguity. Its positioning performance is superior to the positioning method that only measures the phase difference or the phase difference change rate. In practical engineering applications, this method can reduce equipment complexity and cost.
- passive positioning /
- single baseline /
- phase difference /
- phase difference change rate /
- Gauss-Extended Kalman Filter (GS-EKF)

HTML全文

图 1 相位观测下的定位模型示意图

Figure 1. Schematic diagram of positioning model under phase observation

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图 2 模糊相位差测向及定位原理

Figure 2. Principle of direction finding and positioning based on fuzzy phase difference

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图 3 单次定位距离误差和权值更新

Figure 3. Update of distance error and weightin a single positioning

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图 4 不同初始化方位假设个数的定位性能

Figure 4. Positioning performance under different number of initial orientation assumptions

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图 5 不同观测时间下的定位结果

Figure 5. Positioning results at different observation time

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图 6 不同速度下的定位结果

Figure 6. Positioning results at different speeds

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图 7 两种方法定位性能对比

Figure 7. Comparison of positioning performance between two methods

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表 1 不同相位差误差下的定位时间(=0.5(°)/s)

Table 1. Positioning time under different phase difference measurement errors (=0.5(°)/s)

方法	定位时间/s
方法	10°	20°	30°	40°
仅测相位差	25	30	33	34
本文方法	18	18	20	21

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表 2 不同相位差变化率误差下的定位时间(σ_φ=10(°)/s)

Table 2. Positioning time under different phase difference change rate measurement errors (σ_φ=10(°)/s)

方法	定位时间/s
方法	0.3(°)/s	0.5(°)/s	1(°)/s	2(°)/s
仅测相位差变化率	20	23	—	—
本文方法	16	18	25	—

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