基于Ransac算法的捷變頻聯(lián)合正交頻分復(fù)用雷達(dá)高速多目標(biāo)參數(shù)估計(jì)

全英匯; 高霞; 沙明輝; 方文; 李亞超; 邢孟道

doi:10.11999/JEIT200529

基于Ransac算法的捷變頻聯(lián)合正交頻分復(fù)用雷達(dá)高速多目標(biāo)參數(shù)估計(jì)

doi: 10.11999/JEIT200529 cstr: 32379.14.JEIT200529

1.
西安電子科技大學(xué)電子工程學(xué)院西安 710071
2.
北京無線電測(cè)量研究所北京 100854
3.
西安電子科技大學(xué)雷達(dá)信號(hào)處理國家重點(diǎn)實(shí)驗(yàn)室西安 710071

基金項(xiàng)目: 國家自然科學(xué)基金(61303035, 61772397)，中央高?；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金，西安電子科技大學(xué)研究生創(chuàng)新基金

詳細(xì)信息

作者簡介:
全英匯：男，1981年生，博士，教授，研究方向?yàn)槔走_(dá)信號(hào)處理、主動(dòng)波形對(duì)抗

高霞：女，1996年生，碩士生，研究方向?yàn)槔走_(dá)信號(hào)處理

沙明輝：男，1986年生，博士生，研究方向?yàn)槔走_(dá)抗干擾和信號(hào)處理

方文：男，1996年生，碩士生，研究方向?yàn)槔走_(dá)信號(hào)處理

李亞超：男，1981年生，博士，教授，研究方向?yàn)槔走_(dá)成像和實(shí)時(shí)信號(hào)處理

邢孟道：男，1975年生，博士，教授，研究方向?yàn)镾AR/ISAR成像、動(dòng)目標(biāo)檢測(cè)等

通訊作者:
高霞　2636897970@qq.com

中圖分類號(hào): TN957.51
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出版歷程
- 收稿日期: 2020-06-29
- 修回日期: 2020-12-06
- 網(wǎng)絡(luò)出版日期: 2020-12-15
- 刊出日期: 2021-07-10

High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Ransac Algorithm

1.
School of Electronic Engineering, Xidian University, Xi’an 710071, China
2.
Beijing Institute of Radio Measurement, Beijing 100854, China
3.
National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds: The National Natural Science Foundation of China (61303035, 61772397), The Foundation Research Funds for Central University, The Innovation Fund of Xidian University

摘要

摘要: 在現(xiàn)代雷達(dá)電子戰(zhàn)場(chǎng)中，目標(biāo)檢測(cè)與其參數(shù)估計(jì)有著非常重要的意義。因此，該文提出了一種基于隨機(jī)抽樣一致算法(Ransac)的捷變頻聯(lián)合正交頻分復(fù)用(FA-OFDM)雷達(dá)高速多目標(biāo)參數(shù)估計(jì)的方法。首先，在傳統(tǒng)捷變頻雷達(dá)的每個(gè)脈沖內(nèi)同時(shí)發(fā)射多個(gè)頻率隨機(jī)跳變的窄帶OFDM子載波。將單個(gè)脈沖內(nèi)所有子載波的回波信號(hào)進(jìn)行脈沖壓縮后，采用迭代自適應(yīng)譜估計(jì)(IAA)算法合成目標(biāo)的高分辨距離。然后，分別對(duì)各個(gè)脈沖的回波進(jìn)行脈沖壓縮和迭代自適應(yīng)譜估計(jì)，得到不同脈沖時(shí)刻的高分辨距離，構(gòu)成觀測(cè)數(shù)據(jù)集。再根據(jù)Ransac算法估計(jì)信號(hào)參數(shù)模型的步驟，擬合多條時(shí)間-距離直線，進(jìn)而對(duì)高速運(yùn)動(dòng)的多個(gè)目標(biāo)同時(shí)進(jìn)行參數(shù)估計(jì)。最后，分別分析了信噪比(SNR)對(duì)檢測(cè)概率以及目標(biāo)自身速度對(duì)其相對(duì)估計(jì)誤差的影響。仿真實(shí)驗(yàn)驗(yàn)證了所提算法的有效性。
- 參數(shù)估計(jì) /
- 高速多目標(biāo) /
- 捷變頻聯(lián)合正交頻分復(fù)用雷達(dá) /
- 迭代自適應(yīng)譜估計(jì)算法 /
- 隨機(jī)抽樣一致算法
Abstract: In modern radar electronic battlefield, target detection and parameter estimation have great significance. Therefore, a high-speed multi-target parameter estimation method for Frequency Agile-Orthogonal Frequency Division Multiplexing (FA-OFDM) radar based on Random sampling consensus (Ransac) algorithm is proposed in this paper. Firstly, multiple narrowband OFDM subcarriers with random frequency hopping are simultaneously transmitted in each pulse of conventional frequency agile radar. The echo signals of all subcarriers in a single pulse are compressed, and then the high-resolution range of the target is synthesized by Iterative Adaptive Approach (IAA) algorithm. Furthermore, the echoes of each pulse are compressed and iterative adaptive spectrum estimated, and the high-resolution distance of different pulse time is obtained to form the observation data set. Then, according to the steps of the Ransac algorithm to estimate the signal parameter model, multiple time-distance lines are fitted, and then parameters of multiple high-speed moving targets are estimated at the same time. Finally, the influence of the Signal-to-Noise Ratio (SNR) on detection probability and the target velocity on relative error of estimation are analyzed, respectively. Simulations are provided to verify the effectiveness of the proposal.

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圖 1 FA-OFDM雷達(dá)發(fā)射信號(hào)示意圖

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圖 2 3個(gè)相鄰目標(biāo)仿真結(jié)果圖

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圖 3 基于Ransac算法的高速多目標(biāo)參數(shù)估計(jì)方法的流程圖

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圖 4 信噪比為–12 dB時(shí)的仿真結(jié)果

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圖 5 信噪比為–28 dB時(shí)的仿真結(jié)果

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圖 6 信噪比對(duì)檢測(cè)概率的影響

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圖 7 目標(biāo)速度對(duì)估計(jì)誤差的影響

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圖 8 輸出SNR對(duì)RMSE的影響

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表 1 仿真參數(shù)

參數(shù)	數(shù)值	參數(shù)	數(shù)值
脈沖寬度	4 μs	脈沖重復(fù)頻率	25 kHz
信號(hào)帶寬	24 MHz	采樣頻率	48 MHz
子載波個(gè)數(shù)	64	中心載頻	14 GHz
跳頻總數(shù)	128	跳頻帶寬	20 MHz
脈沖總數(shù)	64	輸入信噪比	–12 dB / –28 dB
目標(biāo)距離	[3994, 4001, 4006] m	目標(biāo)速度	[600, 1220, 5800] m/s

下載: 導(dǎo)出CSV

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