利用伯努利濾波的多目標機動雷達誤差配準方法

鄧洪高; 余潤華; 紀元法; 吳孫勇; 孫希延

doi:10.11999/JEIT240013

利用伯努利濾波的多目標機動雷達誤差配準方法

doi: 10.11999/JEIT240013 cstr: 32379.14.JEIT240013

鄧洪高^{1, 4},
余潤華^{1, 2},
紀元法^{1, 2, 4},
吳孫勇^{2, 3, ,},
孫希延^{1, 2, 4, 5}

1.
桂林電子科技大學信息與通信學院桂林 541004
2.
桂林電子科技大學廣西精密導航技術與應用重點實驗室桂林 541004
3.
桂林電子科技大學數學與計算科學學院桂林 541004
4.
衛(wèi)星導航定位與位置服務國家地方聯合工程研究中心桂林 541004
5.
南寧桂電電子科技研究院有限公司南寧 530031

基金項目: 國家自然科學基金(U23A20280, 62061010, 62161007)，廣西科技廳項目(AB23026120)

詳細信息

作者簡介:
鄧洪高：男，研究員，研究方向為雷達信號處理和衛(wèi)星導航

余潤華：男，碩士生，研究方向為雷達多目標跟蹤、空間誤差配準和多源信息融合

紀元法：男，教授，研究方向為衛(wèi)星導航和信號處理

吳孫勇：男，教授，研究方向為雷達信號處理、多目標檢測與跟蹤和多源信息融合

孫希延：女，研究員，研究方向為衛(wèi)星導航和遙感

通訊作者:
吳孫勇　wusunyong121991@163.com

中圖分類號: TN959.1; V243.2
計量
- 文章訪問數: 236
- HTML全文瀏覽量: 91
- PDF下載量: 24
- 被引次數: 0
出版歷程
- 收稿日期: 2024-01-16
- 修回日期: 2024-09-05
- 網絡出版日期: 2024-09-11
- 刊出日期: 2024-10-30

Mobile Radar Registration with Multiple Targets Based on Bernoulli Filter

DENG Honggao^{1, 4},
YU Runhua^{1, 2},
JI Yuanfa^{1, 2, 4},
WU Sunyong^{2, 3
, ,},
SUN Xiyan^{1, 2, 4, 5}

1.
School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China
2.
Guangxi Key Laboratory of Precision Navigation Technology and Application, Guilin University of Electronic Science and Technology, Guilin 541004, China
3.
School of Mathematics and Computing Science, Guilin University of Electronic Science and Technology, Guilin 541004, China
4.
National & Local Joint Engineering Research Center of Satellite Navigation Positioning and Location Service, Guilin 541004, China
5.
GUET-Nanning E-Tech Research Institute Co., Ltd., Nanning 530031, China

Funds: The National Natural Science Foundation of China (U23A20280, 62061010, 62161007), Guangxi Science and Technology Department Project (AB23026120)

摘要

摘要: 傳統(tǒng)的組網雷達多目標誤差配準方法通常假設數據關聯關系已知，但在平臺機動的情況下，系統(tǒng)同時存在雷達測量偏差和平臺姿態(tài)角偏差，且雷達觀測過程中會受到雜波干擾，導致數據關聯尤為困難。針對這一問題，該文提出一種基于伯努利濾波的多目標機動雷達誤差配準方法。首先建立系統(tǒng)偏差的量測與狀態(tài)方程，然后將系統(tǒng)偏差建模成伯努利隨機有限集，利用公共坐標系下的原始量測可實現系統(tǒng)偏差在伯努利濾波框架下的遞推估計，有效避免了數據關聯問題。同時，為了充分利用多目標量測信息，提出一種修正的貪婪量測劃分方法，在每個濾波時刻挑選出系統(tǒng)偏差對應的最優(yōu)量測子集，利用量測子集中的多量測信息實現系統(tǒng)偏差的集中式融合估計，提高了系統(tǒng)偏差的估計精度和收斂速度。仿真實驗表明，所提方法能夠在數據關聯未知的多目標多雜波場景下對雷達測量偏差和平臺姿態(tài)角偏差進行有效估計，在平臺姿態(tài)角變化率較低時，所提方法具有較強的適應性。
- 誤差配準 /
- 數據關聯 /
- 伯努利濾波 /
- 集中式融合 /
- 量測劃分
Abstract: Traditional methods for multi-target bias registration in networked radar system typically assume that the data association relationship is known. However, in the case of platform maneuvering, there are simultaneously radar measurement biases and platform attitude angle biases, and the radar observation process is prone to clutter interference, resulting in difficulties in data association. To address this issue, a multi-target mobile radar bias registration method based on Bernoulli filter is proposed. Firstly, the measurement and state equations for the system biases are established, and then the system biases are modeled as a Bernoulli random finite set. The recursive estimation of the system biases under the Bernoulli filtering framework is achieved using the original measurements in a common coordinate system, effectively avoiding the data association. Additionally, to fully utilize multi-target measurement information, a modified greedy measurement partitioning method is proposed to select the optimal measurement subset corresponding to the system biases at each filtering time step, and the centralized fusion estimation of the system biases is performed using the multi-measurement information in the measurement subset, improving the estimation accuracy and convergence speed of the system biases. Simulation experiments show that the proposed method can effectively estimate radar measurement biases and platform attitude angle biases in multi-target and cluttered scenarios with unknown data association. Moreover, this method demonstrates strong adaptability when the platform attitude angle variation rate is low.
- Registration /
- Data association /
- Bernoulli filter /
- Centralized fusion /
- Measurement partition

HTML全文

圖 1 場景1中偏差估計均方根誤差圖

下載: 全尺寸圖片幻燈片

圖 2 場景2中偏差估計均方根誤差圖

下載: 全尺寸圖片幻燈片

表 1 場景3中偏差收斂步數比較

量測劃分前/后	偏差估計收斂步數
	雷達測量偏差			平臺姿態(tài)角偏差
	徑向距離	方位角	俯仰角	偏航角	縱搖角	橫搖角
前	161	330	288	362	317	305
后	18	281	194	310	260	242

下載: 導出CSV

表 2 場景3中偏差估計精度比較(%)

量測劃分前/后	偏差估計精度
	雷達測量偏差			平臺姿態(tài)角偏差
	徑向距離	方位角	俯仰角	偏航角	縱搖角	橫搖角
前	98.43	96.52	90.33	93.25	93.34	92.14
后	98.66	98.18	95.04	97.31	96.71	96.53

下載: 導出CSV

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