基于MUSIC算法的二次雷达应答信号分离方法

张海; 陈小龙; 张涛; 张财生

doi:10.11999/JEIT190842

基于MUSIC算法的二次雷达应答信号分离方法

doi: 10.11999/JEIT190842

张海¹,
陈小龙¹,
张涛^{1, 2, ,},
张财生¹

1.
海军航空大学烟台 264001
2.
92337部队大连 116023

基金项目: 国家自然科学基金(U1933135, 61871391, 61931021)；山东省重点研发计划(2019GSF111004)

详细信息

作者简介:
张海：男，1976年生，副教授，研究方向为雷达信号处理、雷达目标特性等

陈小龙：男，1985年生，副教授，研究方向为雷达动目标检测、海杂波抑制、雷达信号精细化处理等

张涛：男，1986年生，工程师，研究方向为ADS-B系统设计及信号处理等

张财生：男，1983年生，讲师，研究方向为雷达信号处理、ADS-B信号处理等

通讯作者:
张涛　radarads@sina.com

中图分类号: TN958.96; V19
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出版历程
- 收稿日期: 2019-11-01
- 修回日期: 2020-03-20
- 网络出版日期: 2020-04-10
- 刊出日期: 2020-12-08

Overlapping Secondary Surveillance Radar Replies Separation Algorithm Based on MUSIC

1.
Naval Aviation University, Yantai 264001, China
2.
92337 Troop, Dalian 116023, China

Funds: The National Nature Science Foundation of China (U1933135, 61871391, 61931021), The Key Research and Development Program of Shandong Province (2019GSF111004)

摘要

摘要: 为了提高在高密度信号环境下对二次监视雷达(SSR)应答信号的接收性能，该文提出一种将信源数估计和信号到达方向(DOA)估计相结合构建分离矩阵实现交叠信号分离的算法。首先根据交叠信号量测的特征值分布来确定交叠信号的个数；然后利用MUSIC算法作谱峰搜索得到各信号的DOA，并重构混合矩阵；最后通过计算混合矩阵的广义逆得到分离矩阵，并实现对交叠信号的分离。以6阵元均匀线阵为前提进行仿真分析，结果表明所提分离算法可达到90%以上的分离成功率，分离性能和独立成分分析(ICA)算法相当，优于基于投影技术分离算法(PA)，但计算量远小于ICA算法，不足ICA算法计算量1/10，更易于工程化应用。
- 交叠信号分离 /
- 阵列天线 /
- SSR应答信号 /
- MUSIC算法 /
- 混合矩阵重构
Abstract: In order to improve the reception performance of Secondary Surveillance Radar (SSR) replies in high-density signal environment, a separation algorithm is proposed, which constructs the separating matrix with estimating the source number and the Direction Of Arrival (DOA) of signal. Firstly, the number of overlapping signals is determined with the eigenvalues distribution of the measurements. Secondly, the mixing matrix with the DOA of signals, which is estimated by peak value searching in MUSIC algorithm. Finally, the separating matrix is estimated by calculating the Moore-Penrose inverse of the reconstructed mixing matrix, achieving separation of overlapping signals. Simulation is done based on uniform linear array with 6 elements. The results show that the proposed separation algorithm can achieve more than 90% success rate to separate two short Mode S replies, and the separating performance is similar to the Independent Component Analysis (ICA) algorithm and is better than Projection Algorithm (PA). The amount of calculation is less than 10 percent of ICA algorithm, thus the proposed separation algorithm is easier to engineering application.
- Overlapping signal Separation /
- Array antenna /
- Secondary Surveillance Radar (SSR) replies /
- MUSIC algorithm /
- Mixing matrix reconstruction

HTML全文

图 1 SSR应答信号四重交叠

下载: 全尺寸图片幻灯片

图 2 特征值分布及信号的空间谱

下载: 全尺寸图片幻灯片

图 3 不同测向误差下的失败率和误码率

下载: 全尺寸图片幻灯片

图 4 不同测向误差下的失败率和误码率(完全交叠)

下载: 全尺寸图片幻灯片

图 5 不同交叠程度下的不同算法的分离失败率

下载: 全尺寸图片幻灯片

图 6 不同交叠程度下的不同算法的误码率

下载: 全尺寸图片幻灯片

表 1 交叠信号个数检测正确概率(%)

DOA	4 dB	8 dB	12 dB	16 dB	20 dB
0°	93.63	95.84	97.51	98.61	99.17
15°	93.07	95.84	96.95	97.78	98.89
30°	92.80	95.29	96.40	97.23	98.61
45°	90.86	93.91	95.84	96.40	98.34
60°	85.87	91.97	95.29	95.29	98.06
75°	72.58	78.95	87.81	93.91	97.51
90°	71.75	77.84	82.55	86.70	90.03

下载: 导出CSV

参考文献(25)

张军. 空域监视技术的新进展及应用[J]. 航空学报, 2011, 32(1): 1–14.

ZHANG Jun. New development and application of airspace surveillance technology[J]. Acta Aeronautica et Astronautica Sinica, 2011, 32(1): 1–14.

PETROCHILOS N, GALATI G, and PIRACCI E. Separation of SSR signals by array processing in multilateration systems[J]. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(3): 965–982. doi: 10.1109/TAES.2009.5259177

王洪, 刘昌忠, 汪学刚. 二次雷达S模式综述[J]. 电讯技术, 2008, 48(7): 113–118. doi: 10.3969/j.issn.1001-893X.2008.07.029

WANG Hong, LIU Changzhong, and WANG Xuegang. Mode S for secondary surveillance radar (SSR): An introduction and overview[J]. Telecommunication Engineering, 2008, 48(7): 113–118. doi: 10.3969/j.issn.1001-893X.2008.07.029

PETROCHILOS N, GALATI G, MENE L, et al. Separation of multiple secondary surveillance radar sources in a real environment by a novel projection algorithm[C]. The 5th IEEE International Symposium on Signal Processing and Information Technology, Athens, Greece, 2005: 125–130.

PETROCHILOS N, GALATI G, and PIRACCI E. Projection techniques for separation of multiple secondary surveillance radar sources in a real environment[C]. The 4th IEEE Workshop on Sensor Array and Multichannel Processing, Waltham, USA, 2006: 344–348.

PETROCHILOS N, PIRACCI E G, and GALATI G. Separation of multiple secondary surveillance radar sources in a real environment for the near-far case[C]. Antennas and Propagation Society International Symposium, Honolulu, USA, 2007: 3988–3991.

CHEN Xiaolong, CHEN Baoxin, GUAN Jian, et al. Space-range-Doppler focus-based low-observable moving target detection using frequency diverse array MIMO radar[J]. IEEE Access, 2018, 6: 43892–43904. doi: 10.1109/ACCESS.2018.2863745

陈小龙, 关键, 黄勇, 等. 雷达低可观测动目标精细化处理及应用[J]. 科技导报, 2017, 35(20): 19–27.

CHEN Xiaolong, GUAN Jian, HUANG Yong, et al. Radar refined processing and its applications for low-observable moving target[J]. Science &Technology Review, 2017, 35(20): 19–27.

GALATI G, BARTOLINI S, and MENE L. Analysis of SSR signals by super resolution algorithms[C]. The 4th IEEE International Symposium on Signal Processing and Information Technology, Rome, Italy, 2004: 166–170.

王洪, 黄荣顺, 徐自励. 多点定位中A/C模式混叠信号的时域分离算法[J]. 电子科技大学学报, 2013, 42(6): 848–851. doi: 10.3969/j.issn.1001-0548.2013.06.007

WANG Hong, HUANG Rongshun, and XU Zili. Separating algorithm of A/C garbles in time domain for multilateration[J]. Journal of University of Electronic Science and Technology of China, 2013, 42(6): 848–851. doi: 10.3969/j.issn.1001-0548.2013.06.007

王洪, 刘昌忠, 汪学刚, 等. 多点定位混叠信号的盲分离[J]. 电讯技术, 2009, 49(12): 1–4. doi: 10.3969/j.issn.1001-893x.2009.12.001

WANG Hong, LIU Changzhong, WANG Xuegang, et al. Blind Separation of gables in multilateration[J]. Telecommunication Engineering, 2009, 49(12): 1–4. doi: 10.3969/j.issn.1001-893x.2009.12.001

PETROCHILOS N and VAN DER VEEN A J. Algorithms to separate overlapping secondary surveillance radar replies[C]. 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, Canada, 2004: 11–49.

刘松, 庞育才. 基于扩展ESPRIT的随机阵列高效DoA估计算法[J]. 电子与信息学报, 2019, 41(6): 1324–1329. doi: 10.11999/JEIT180672

LIU Song and PANG Yucai. Efficient augmented ESPRIT-based direction-of-arrival estimation algorithm for random arrays[J]. Journal of Electronics &Information Technology, 2019, 41(6): 1324–1329. doi: 10.11999/JEIT180672

王洪. 1030/1090 MHz频谱的共享与干扰问题综述[J]. 电讯技术, 2013, 53(1): 105–109. doi: 10.3969/j.issn.1001-893x.2013.01.021

WANG Hong. Overview of sharing and interference at 1030/1090 MHz[J]. Telecommunication Engineering, 2013, 53(1): 105–109. doi: 10.3969/j.issn.1001-893x.2013.01.021

孙清清, 王洪, 黄忠涛, 等. 1090MHz信号同频干扰与窜扰概率探究[J]. 通信技术, 2013, 46(2): 8–11. doi: 10.3969/j.issn.1002-0802.2013.02.005

SUN Qingqing, WANG Hong, HUANG Zhongtao, et al. Exploration on 1090MHz co-channel interference and probability of garble[J]. Communications Technology, 2013, 46(2): 8–11. doi: 10.3969/j.issn.1002-0802.2013.02.005

SCHMIDT R O. Multiple emitter location and signal parameter estimation[J]. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 276–280. doi: 10.1109/TAP.1986.1143830

王旭东, 仲倩, 闫贺, 等. 一种二维信号波达方向估计的改进多重信号分类算法[J]. 电子与信息学报, 2019, 41(9): 2137–2142. doi: 10.11999/JEIT181090

WANG Xudong, ZHONG Qian, YAN He, et al. An improved MUSIC algorithm for two dimensional direction of arrival estimation[J]. Journal of Electronics &Information Technology, 2019, 41(9): 2137–2142. doi: 10.11999/JEIT181090

张蔚. 二次雷达原理[M]. 北京: 国防工业出版社, 2009: 144–146.

ZHANG Wei. Secondary Radar Principle[M]. Beijing: National Defense Industry Press, 2009: 144–146.

RTCA D. RTCA DO-260B Minimum operational performance standards for 1090 MHz extended squitter automatic dependent surveillance-broadcast (ADS-B) and traffic information services-broadcast (TIS-B)[S]. Washington, DC: RTCA, Inc., 2011.

ICAO A. 10 (Aeronautical Telecomm.) to the convention on international civil aviation[J]. Volume I, 1996: 52–60.

王永良, 陈辉, 彭应宁, 等. 空间谱估计理论与算法[M]. 北京: 清华大学出版社, 2004: 40–52.

WANG Yongliang, CHEN Hui, PENG Yingning, et al. Spatial Spectrum Estimation Theory and Algorithm[M]. Beijing: Tsinghua University Press, 2004: 40–52.

ROY R and KAILATH T. ESPRIT-estimation of signal parameters via rotational invariance techniques[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1989, 37(7): 984–995. doi: 10.1109/29.32276

王洪, 刘昌忠, 汪学刚, 等. 强干扰背景下S模式解码方法[J]. 电子与信息学报, 2009, 31(12): 2876–2880.

WANG Hong, LIU Changzhong, WANG Xuegang, et al. Mode S decoding methods in heavy jamming environment[J]. Journal of Electronics &Information Technology, 2009, 31(12): 2876–2880.

张涛, 唐小明, 金林. 基于置信度的S模式信号随机多位纠错技术[J]. 电讯技术, 2015, 55(9): 1005–1009. doi: 10.3969/j.issn.1001-893x.2015.09.010

ZHANG Tao, TANG Xiaoming, and JIN Lin. Confidence-based brute force technique with random errors for Mode S reply[J]. Telecommunication Engineering, 2015, 55(9): 1005–1009. doi: 10.3969/j.issn.1001-893x.2015.09.010

孙守宇. 盲信号处理基础及其应用[M]. 北京: 国防工业出版社, 2010: 50–95.

SUN S Y. Blind Signal Processing Foundation and It’s Applications[M]. Beijing: National Defense Industry Press, 2010: 50–95.

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