基于強散射點在線估計的距離擴展目標檢測方法

郭鵬程; 劉崢; 羅丁利; 李儉樸

doi:10.11999/JEIT190417

基于強散射點在線估計的距離擴展目標檢測方法

doi: 10.11999/JEIT190417 cstr: 32379.14.JEIT190417

郭鵬程^{1, 2},
劉崢^1, ,,
羅丁利²,
李儉樸¹

1.
西安電子科技大學(xué)雷達信號處理國家重點實驗室西安 710071
2.
西安電子工程研究所西安 710100

詳細信息

作者簡介:
郭鵬程：男，1983年生，高級工程師，博士生，研究方向為雷達目標檢測與識別

劉崢：男，1964年生，教授，研究方向為雷達信號處理的理論與系統(tǒng)設(shè)計、雷達精確制導(dǎo)技術(shù)、多傳感器融合等

羅丁利：男，1974年生，研究員，研究方向為雷達信號處理、目標分類識別技術(shù)

李儉樸：男，1994年生，碩士生，研究方向為雷達目標檢測

通訊作者:
劉崢　lz@xidian.edu.cn

中圖分類號: TN957.51
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出版歷程
- 收稿日期: 2019-06-06
- 修回日期: 2019-09-07
- 網(wǎng)絡(luò)出版日期: 2019-09-19
- 刊出日期: 2020-06-04

Range Spread Target Detection Based on OnlineEstimation of Strong Scattering Points

Pengcheng GUO^{1, 2},
Zheng LIU^{1
, ,},
Dingli LUO²,
Jianpu LI¹

1.
National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
2.
Xi'an Electronic Engineering Research Institute, Xi’an 710100, China

摘要

摘要:
傳統(tǒng)的距離擴展目標檢測一般在散射點密度或散射點數(shù)量先驗條件下完成，在目標散射點信息完全未知時檢測性能會大幅降低。針對這個問題，該文提出一種基于強散射點在線估計的距離擴展目標檢測方法(OESS-RSTD)，該方法利用機器學(xué)習(xí)中的無監(jiān)督聚類算法在線估計強散射點數(shù)量以及首次檢測門限，然后再結(jié)合虛警率，確定2次檢測門限，最后通過兩次門限檢測完成目標有無的判決。該文分別利用仿真數(shù)據(jù)和實測數(shù)據(jù)進行了試驗驗證，并和其他算法進行了試驗對比，通過虛警概率一定時的信噪比(SNR)-檢測概率曲線驗證了該文所提方法相對于傳統(tǒng)算法有更高的穩(wěn)健性，且該方法不需要目標散射點的任何先驗信息。
- 高分辨雷達 /
- 擴展目標檢測 /
- 聚類 /
- 強散射點估計
Abstract:
The traditional range-extended target detection is usually completed under the condition of scattering point density or scattering point number priori. The detection performance is greatly reduced when the scattering point information of the target is completely unknown. To solve this problem, a Range Spread Target Detection method based on Online Estimation of Strong Scattering(OESS-RSTD) points is proposed. Firstly, the unsupervised clustering algorithm in machine learning is used to estimate the number of strong scattering points and the first detection threshold adaptively. Then, the second detection threshold is determined according to false alarm rate. Finally, the existence of the target is determined through two detection thresholds. The simulation data and the measured data are used to verify and compare with other algorithms. By comparing the Signal-to-Noise Ratio (SNR) -detection probability curves of various methods with a given false alarm probability, it is verified that the proposed method has higher robustness than the traditional algorithm, and the method does not need any priori information of target scattering points.
- High resolution radar /
- Extended target detection /
- Clustering /
- Strong scattering point estimation

HTML全文

圖 1 檢測器各區(qū)域的示意圖

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圖 2 非先驗依賴的擴展目標檢測流程圖

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圖 3 卡車典型姿態(tài)的高分辨距離像

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圖 4 基于4種仿真模型的檢測性能對比

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圖 5 基于實測數(shù)據(jù)的檢測性能對比結(jié)果

下載: 全尺寸圖片幻燈片

表 1 4種典型散射點模型

編號	散射點分布特點	名稱
模型1	1個強散射點，占全部能量	單散射點
模型2	10個散射點，一個強散射點占50%能量，其他散射點占各占5.556%能量	稀疏多散射點
模型3	32個散射點，兩個強散射點各占25%，其他散射點占各占1.66%能量	密集非均勻多散射點
模型4	32個散射點，均勻分布，各占3.125%能量	密集均勻散射點

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