復(fù)雜多徑信號下基于空域變換的米波雷達(dá)穩(wěn)健測高算法

陳根華; 陳伯孝

doi:10.11999/JEIT190554

復(fù)雜多徑信號下基于空域變換的米波雷達(dá)穩(wěn)健測高算法

doi: 10.11999/JEIT190554 cstr: 32379.14.JEIT190554

陳根華^1, ,,
陳伯孝²

1.
南昌工程學(xué)院信息工程學(xué)院南昌 310099
2.
西安電子科技大學(xué)雷達(dá)信號處理國家重點實驗室西安 710071

基金項目: 國家自然科學(xué)基金(61401187)，江西省教育廳科學(xué)技術(shù)研究項目(GJJ170990)

詳細(xì)信息

作者簡介:
陳根華：男，1980年生，副教授，博士，研究方向為陣列雷達(dá)信號處理

陳伯孝：男，1966年生，教授，博士生導(dǎo)師，研究方向為新體制雷達(dá)系統(tǒng)設(shè)計及其實現(xiàn)、雷達(dá)信號處理、目標(biāo)精確制導(dǎo)與跟蹤等

通訊作者:
陳根華　cghnit@126.com

中圖分類號: TN958
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- 文章訪問數(shù): 3779
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- PDF下載量: 83
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2019-07-24
- 修回日期: 2020-02-24
- 網(wǎng)絡(luò)出版日期: 2020-03-21
- 刊出日期: 2020-06-04

Robust Altitude Estimation Based on Spatial Sign Transform in the Presence of Diffuse Multipath for Very High Frequency Radar

Genhua CHEN^{1
, ,},
Baixiao CHEN²

1.
School of Information Engineering, Nanchang Institute of Technology, Nanchang 310099, China
2.
National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds: The National Natural Science Foundation of China(61401187), The Science Research of Jiangxi Provincial Department of Education(GJJ170990)

摘要

摘要:
針對米波(VHF)雷達(dá)的復(fù)雜多徑信號中散射分量的非高斯性嚴(yán)重影響測高的穩(wěn)定性，該文提出了穩(wěn)健的空域符號變換最大似然測高算法。該算法先對多維陣列快拍矢量進(jìn)行空域符號變換處理，以抑制散射分量野值點對陣列協(xié)方差矩陣及其測高算法的影響，再計算符號協(xié)方差矩陣(SCM)，然后根據(jù)符號協(xié)方差矩陣的映射等效性和特征空間不變性，將符號協(xié)方差矩陣應(yīng)用到最大似然(SCM-ML)測高算法中，實現(xiàn)了穩(wěn)健的米波雷達(dá)低角測高。該算法有效抑制了多徑信號中散射分量和波束打地形成的強雜波的非高斯性，提高了米波雷達(dá)低角測高的穩(wěn)健性。仿真結(jié)果和實測數(shù)據(jù)驗證了算法的穩(wěn)健性與有效性。
- 米波雷達(dá) /
- 空域符號變換 /
- 散射分量 /
- 非高斯性 /
- 測高
Abstract:
A robust spatial sign transform-based maximum likelihood method for low-elevation target altitude measurement is proposed in the presence of the non-Gaussian diffuse multipath component for Very High Frequency (VHF) radar. The spatial sign transform is implemented to the antenna array snapshots, reducing the influence of the outliers on array covariance matrix and the low elevation estimation algorithms, followed by computing the spatial Sign Covariance Matrix(SCM). Then the application of SCM to the Maximum Likelihood method(SCM-ML) is presented on the basis of the affine equivalence and preservation of the eigenstructure for robust low elevation estimation and height finding of VHF radar. The proposed method effectively solves the non-Gaussian property of the diffuse multipath component and improves the robustness of low elevation estimation. Simulation result and real data demonstrate the robustness and validation of the SCM-ML method.
- Very High Frequency (VHF) radar /
- Spatial sign transform /
- Diffuse component /
- Non-Gaussian /
- Altitude estimation

HTML全文

圖 1 復(fù)雜環(huán)境下米波雷達(dá)低角目標(biāo)測高示意圖

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圖 2 空域符號變換示意圖

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圖 3 某相控陣米波雷達(dá)低角目標(biāo)回波序列

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圖 4 符號變換后SCM特征值分布

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圖 5 SCM-ML測高算法精度

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圖 6 SCM-ML測高算法低角估計分布

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圖 7 SCM-ML穩(wěn)健性能分析及測高算法分辨性能

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