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炮位侦校雷达联合定位算法研究

闫海 张炜轩 韩文俊 王晓东 周垂红

现代雷达2026,Vol.48Issue(1):34-40,7.
现代雷达2026,Vol.48Issue(1):34-40,7.DOI:10.16592/j.cnki.1004-7859.20231019002

炮位侦校雷达联合定位算法研究

A Joint Locating Algorithm for Artillery Locating&Calibration Radar

闫海 1张炜轩 1韩文俊 1王晓东 1周垂红1

作者信息

  • 1. 南京电子技术研究所,江苏 南京 210039
  • 折叠

摘要

Abstract

The increased measurement noise,resulting from strong clutter and fluctuations in the radar cross section(RCS)of the target,adversely affects the accuracy of target angle measurement.In the traditional method,the observation data of individual tar-get is filtered and then used for ballistic extrapolation.However,when significant measurement errors exist,the filtering process converges slowly and estimation errors become unacceptable,making it difficult to meet the high-precision positioning requirements of artillery locating&calibration radars.To address this problem,a filtering algorithm based on multi-trajectory joint measurement(MTLF)is proposed in this paper.The MTLF algorithm replaces single-shot measurement results with fused measurement results from multiple projectiles in the filtering equation,which can reduce filtering posterior estimation errors and improve the consistency of extrapolation.To validate the effectiveness of the algorithm,multiple sets of data for projectiles under various shooting conditions are generated using a simulator.A comparative analysis is performed between the proposed method and the traditional method in terms of measurement error,filtering error,and positioning accuracy.Results show that compared with traditional method,the pro-posed method effectively suppresses measurement errors,improves filtering accuracy,and reduces the circular error probable(CEP)of the artillery group,demonstrating strong practical value.

关键词

炮位侦校雷达/低信噪比/量测误差/滤波/联合定位

Key words

artillery locating&calibration radars/low signal-to-noise ratio/measurement error/filtering/joint locating method

分类

信息技术与安全科学

引用本文复制引用

闫海,张炜轩,韩文俊,王晓东,周垂红..炮位侦校雷达联合定位算法研究[J].现代雷达,2026,48(1):34-40,7.

现代雷达

1004-7859

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