基于BSBL-BO算法的DME脉冲干扰抑制方法

doi:10.12305/j.issn.1001-506X.2021.09.35

Abstract

Abstract:

In view of the problem of the distance measure equipment (DME) signal interferes with orthogonal frequency-division multiplexing (OFDM) receiver for L-band digital aeronautical communication system 1 (L-DACS1), a DME interference suppression method based on block sparse Bayesian learning-the bound optimization (BSBL-BO) algorithm is proposed. Firstly, considering that the empty subcarriers of OFDM receiver never transmit useful signals, the compressed sensing model for DME pulse interference signal is established. Then the DME pulse interference signal is reconstructed based on the BSBL-BO algorithm.Finally, the reconstructed DME pulse interference is eliminated in the time domain. The simulation results show that this method has higher reconstruction accuracy and faster operation speed than the existing pulse interference suppression methods, which can further reduce the bit error rate of OFDM receiver and improve the trans-mission performance of forward link in L-DACS1 system significantly.

Key words: L-band digital aeronautical communication system 1 (L-DACS1), distance measure equipment (DME) interference, Bayesian compression sensing, block sparse Bayesian learning

CLC Number:

TN973.3

Dongxia LI, Qiuyu CHEN, Lei WANG, Haitao LIU. DME pulse interference suppression method based on BSBL-BO algorithm[J]. Systems Engineering and Electronics, 2021, 43(9): 2649-2656.

Figures/Tables 10

Fig.1

Fig.2

Table 1

Table 2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

References 30

1	NEJI N , LACERDA R D , AZOULAY A E , et al. Survey on the future aeronautical communication system and its development for continental communications[J]. IEEE Trans.on Vehicular Technology, 2013, 62 (1): 182- 191. doi: 10.1109/TVT.2012.2207138
2	CIEA 15 EN50002.10. L-DACS1 system definition proposal: deliverable D2[S]. Brussels: Eurocontrol Headquarters, 2009.
3	Eurocontrol. L-DACS2 system definition proposal: deliverable D2, version 1.0[R]. Brussels: Eurocontrol Headquarters, 2009.
4	JAIN R, TEMPLIN F, YIN K S. Analysis of L-band digital aeronautical communication systems: L-DACS1 and L-DACS2[C]//Proc. of the IEEE Aerospace Conference, 2011.
5	BRANDES S, EPPLE U, GLIGOREVIC S, et al. Physical layer specification of the L-band digital aeronautical communications system (L-DACS1)[C]//Proc. of the Integrated Communications, Navigation and Surveillance Conference, 2009.
6	CATHERINE J, SEBASTIAN B. A survey on DME interfe-rence mitigation techniques for L-band aeronautical communication[C]//Proc. of the 3rd International Conference on Computing and Communications Technologies, 2019.
7	BRANDES S, EPPLE U, SCHNELL M. Compensation of the impact of interference mitigation by pulse blanking in OFDM systems[C]//Proc. of the IEEE Global Telecommunications Conference, 2009.
8	EPPLE U, SCHNELL M. Adaptive threshold optimization for a blanking nonlinearity in OFDM receivers[C]//Proc. of the IEEE Global Communications Conference, 2012.
9	LIU H T , YIN Z S , JIA M , et al. SER analysis of the MRC-OFDM receiver with pulse blanking over frequency selective fading channel[J]. EURASIP Journal on Wireless Communication and Networking, 2016, 135, 1- 12.
10	刘海涛, 刘亚洲, 张学军. 联合DOA估计与主波束形成的干扰抑制方法[J]. 哈尔滨工业大学学报, 2016, 48 (11): 103- 108. doi: 10.11918/j.issn.0367-6234.2016.11.016
	LIU H T , LIU Y Z , ZHANG X J . Interference mitigation method based on joint DOA estimation and main beam forming[J]. Journal of Harbin Institute of Technology, 2016, 48 (11): 103- 108. doi: 10.11918/j.issn.0367-6234.2016.11.016
11	王磊, 李广雪, 李冬霞, 等. 基于最大输出信噪比的L-DACS1接收机盲自适应波束形成算法[J]. 系统工程与电子技术, 2018, 40 (12): 2839- 2844. doi: 10.3969/j.issn.1001-506X.2018.12.31
	WANG L , LI G X , LI D X , et al. Blind adaptive beamforming for L-DACS1 receiver based on maximum output signal-to-noise ratio[J]. Systems Engineering and Electronics, 2018, 40 (12): 2839- 2844. doi: 10.3969/j.issn.1001-506X.2018.12.31
12	刘海涛, 李广雪, 孙海霞, 等. L-DACS1系统干扰抑制与循环自适应波束形成方法[J]. 系统工程与电子技术, 2020, 42 (8): 1850- 1856.
	LIU H T , LI G X , SUN H X , et al. L-DACS1 system interference suppression and cyclic adaptive beamforming method[J]. Systems Engineering and Electronics, 2020, 42 (8): 1850- 1856.
13	SAAIFAN K A , ELSHAHED A M , HENK-EL W . Cancela-tion of distance measuring equipment interference for aeronautical communications[J]. IEEE Trans.on Aerospace and Electronic Systems, 2017, 53 (6): 3104- 3114. doi: 10.1109/TAES.2017.2728958
14	李冬霞, 王召, 刘海涛. 联合两级滤波与压缩感知的测距仪干扰抑制方法[J]. 信号处理, 2020, 36 (7): 1118- 1126.
	LI D X , WANG Z , LIU H T . DME impulse interference mitigation method based on joint two-stage filtering and compressive sensing[J]. Journal of Signal Processing, 2020, 36 (7): 1118- 1126.
15	GRANT M, BOYD S. CVX: Matlab software for disciplined convex programming[EB/OL]. [2020-09-10]. http://cvxr.com/cvx/.
16	JI S , XUE Y , CARIN L . Bayesian compressive sensing[J]. IEEE Trans.on Signal Processing, 2008, 56 (6): 2346- 2356. doi: 10.1109/TSP.2007.914345
17	XIA C Y , GAO Y X , LI L , et al. Robust signal recovery using Bayesian compressed sensing based on lomax prior[J]. Signal, Image and Video Processing, 2020, 14 (6): 1235- 1243. doi: 10.1007/s11760-020-01661-z
18	LYU F Z, ZHANG C H, TANG Z F, et al. Block-sparse signal recovery based on adaptive matching pursuit via spike and slab prior[C]//Proc. of the IEEE 11th Sensor Array and Multichannel Signal Processing Workshop, 2020.
19	KHAN M S, KIM J, LEE E H, et al. A received signal strength based localization approach for multiple target nodes via Bayesian compressive sensing[C]//Proc. of the IEEE 22nd International Multitopic Conference, 2019.
20	RUAN Y F, LI Y B. Bayesian compressed sensing in universal filtered multicarrier channel estimation[C]//Proc. of the IEEE 19th International Conference on Communication Technology, 2019.
21	ZHANG R, BAI X, ZHAO J. Multiband passive ISAR processing based on Bayesian compressive sensing[C]//Proc. of the IEEE International Conference on Signal, Information and Data Processing, 2019.
22	XIA C Y, ZHOU Z L, GUO C B, et al. Statistical modeling of ISAR imaging based on Bayesian compressive sensing of Pareto distribution family[C]//Proc. of the 5th International Confe-rence on Communication, Image and Signal Processing, 2020.
23	MASOOD M , Al-NAFFOURI T Y . Sparse reconstruction using distribution agnostic Bayesian matching pursuit[J]. IEEE Trans.on Signal Processing, 2013, 61 (21): 5298- 5309. doi: 10.1109/TSP.2013.2278814
24	ZHANG Z L , RAO B D . Extension of SBL algorithms for the recovery of block sparse signals with intra-block correlation[J]. IEEE Trans.on Signal Processing, 2013, 61 (8): 2009- 2015. doi: 10.1109/TSP.2013.2241055
25	ZHANG Z L , RAO B D . Sparse signal recovery with temporally correlated source vectors using sparse Bayesian learning[J]. IEEE Journal of Selected Topics in Signal Processing, 2011, 5 (5): 912- 926. doi: 10.1109/JSTSP.2011.2159773
26	ZHANG Z L , JUNG T P , MAKEIG S , et al. Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning[J]. IEEE Trans.on Biomedical Engineering, 2013, 60 (2): 300- 309. doi: 10.1109/TBME.2012.2226175
27	ZHANG Z L , JUNG T P , MAKEIG S , et al. Compressed sensing of EEG for wireless telemonitoring with low energy consumption and inexpensive hardware[J]. IEEE Trans.on Biomedical Engineering, 2013, 60 (1): 221- 224.
28	李冬霞, 杨玲, 张媛媛. 一种有效的宽带航空数据链脉冲干扰抑制方法[J]. 中国民航大学学报, 2015, 33 (1): 19- 23. doi: 10.3969/j.issn.1674-5590.2015.01.005
	LI D X , YANG L , ZHANG Y Y . Effective impulse interfe-rence cancellation method for broadband aeronautical data link system[J]. Journal of Civil Aviation University of China, 2015, 33 (1): 19- 23. doi: 10.3969/j.issn.1674-5590.2015.01.005
29	SCHNELL M, BRANDES S. Interference mitigation for broadband L-DACS[C]//Proc. of the IEEE/AIAA 27th Digital Avionics Systems Conference, 2008.
30	TIPPING M E . Sparse Bayesian learning and the relevance vector machine[J]. Journal of Machine Learning Research, 2001, 1 (6): 211- 244.

算法名称	运算复杂度
凸优化^[23]	O(N³)
SABMP	O(MN²)
BSBL-BO	O(MN²)

参数	取值
载波频率/GHz	1
传输带宽/MHz	0.498 05
子载波间隔/Hz	9 765.625
采样间隔/μs	1.6
发射/接收天线数	1/1
循环前缀长度/μs	17.6
有用符号长度/μs	102.4
有用子载波数	50
信道编码	卷积编码
调制方式	QPSK
信道模型	AWGN/航空移动Parking信道
DME干扰源数	1
DME载波偏移量/kHz	500
信干比/dB	-7
信道估计	理想信道估计
信道均衡	迫零均衡

[1]	Haitao LIU, Guangxue LI, Haixia SUN, Lei WANG. L-DACS1 system interference suppression and cyclic adaptive beamforming method [J]. Systems Engineering and Electronics, 2020, 42(8): 1850-1856.
[2]	ZHANG Yongshun, ZHU Weigang, JIA Xin, WANG Manxi. NBI detection and parameter estimation in DSSS communications based on BSBL [J]. Systems Engineering and Electronics, 2019, 41(4): 889-897.
[3]	WANG Lei, LI Guangxue, LI Dongxia, LIU Haitao. Blind adaptive beamforming for L-DACS1 receiver based on maximum output signal-to-noise ratio#br# [J]. Systems Engineering and Electronics, 2018, 40(12): 2839-2844.
[4]	LIU Hai-tao, LIU Ya-zhou, CHENG Wei, ZHANG Xue-jun. Interference mitigation method based on subspace projection and blind adaptive beamforming [J]. Systems Engineering and Electronics, 2015, 37(8): 1880-1886.

DME pulse interference suppression method based on BSBL-BO algorithm

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 10

References 30

Related Articles 4

Recommended Articles

Metrics

Comments