干扰检测与识别技术研究与实现
摘要
随着无线通信技术的发展,通信环境日益复杂,干扰越来越多,干扰和抗干扰技术成为一个重要的研究领域。研究一个通信系统的抗干扰性能,首先要准确的测试出系统的干扰信号,然后才能够有效地采取抗干扰技术;电子对抗中对敌我双方的侦察与反侦察技术;认知无线电中对授权信号的识别,这都离不开干扰检测技术。本文主要研究了几种典型干扰(单音干扰、多音干扰和部分频带干扰)的检测识别技术,并联合SDR(Software Definition Radio,软件无线电)硬件开发平台和PC机,实现了干扰检测识别系统,分别在中频(Intermediate Frequency,IF)和射频(Radio Frequency,RF)条件下完成了典型干扰的检测识别性能测试,测试结果完全符合系统要求。
首先,本文对能量检测基本理论进行分析,给出了能量检测的性能评估方法及其优缺点,并着重分析了两种基于频域的连续均值消除(Consecutive Mean Excision ,CME)和前向连续均值消除(Forward Consecutive Mean Excision ,FCME)干扰检测算法,在此基础上提出了一种基于子带误码率统计的干扰检测算法;其次,硬件实现了一个基于模块的干扰检测系统,并对系统中时序控制,数据速率变换,频谱叠加,频谱输出等模块设计进行了详细分析,在此基础上硬件设计并实现了一种基于静默周期干扰检测链路;最后,结合设计的干扰检测与识别界面,硬件实测了干扰检测与识别系统在中频和射频下对单音干扰、多音干扰、部分带干扰的检测与识别性能,硬件实测了系统对上面三种干扰的检测灵敏度;实测干扰检测系统在高斯白噪声、高斯白噪声和变换域通信系统(Transform Domain Communication System,TDCS)信号同时存在两种情况下对单音、多音、部分带三种干扰的检测与识别性能。
硬件测试得出下面结论:中频高斯白噪声下,对于单音干扰,四个单音干扰,2.4MHz的部分带干扰( Partial-Band Interference , PBI ),当干噪比分别(Jamming-to-Noise power Ratio,JNR)大于-24.5dB,-21dB,-0.53dB时,系统检测概率大于99%;中频TDCS信号下,对于单音干扰,三个单音干扰,当干信比(Jamming-to-Signal power Ratio ,JSR)分别大于-32.2dB,-26.24dB时,系统检测概率大于99%;400MHz射频条件下,对于单音干扰,四个单音干扰,2MHz的部分带干扰,当干噪比分别大于-27.1dB,-19dB,-3.5dB时,系统检测概率逼近1;400MHz射频TDCS信号存在条件下,对于单音干扰,当JSR大于-34dB,对于2个单音干扰,当JSR大于-30dB,对于150KHMz的部分带干扰,当JSR大于-20dB,系统检测概率逼近1,优于系统要求JSR大于0dB时能够准确检测和识别出干扰的目标。
As wireless communications technology development, wireless communication environment become more and more perplexed, more and more interference in wireless communication environment, jamming and anti-jamming technology to become an important research area. Reserch the anti-interference performance of a communication system, communication system can accurately detecting the interference signal at first, and then be able to take anti-jamming technology effectively; In Electronic Warfare, Investigation and anti-reconnaissance technology to be used in both of two sides; Identification the authorized signal in cognitive radio, which are inseparable from the interference detection technology. This article mainly studied several typical interference's (Single-tone interference , multi-tone interference , Partial-band interference)detection and identification technology, and take SDR hardware platforms and PC together, to achieve the interference detection and identifying system.Respectively in the Intermediate Frequency and Radio Frequency , test several typical interference's detection and identifying performance , the test results meet system requirements.
Firstly,the article details the interference’s detecting and identifying process, while the basic method of energy detection techniques and theories were analyzed, gives its performance evaluation of energy detection and its advantages and disadvantages, and analyzing both Consecutive Mean Excision and Forward Consecutive Mean Excision detecting algorithm’s domain ideal and implementation steps.Based on the above thoughts, a statistical error rate based on sub-band interference detection algorithm is proposed. Secondly,this article study the jamming detection system based on the module design method, described the detection system timing control, data rate conversion, spectrum overlay design, spectrum output control. On this basis, designs a Jamming Detect System with silent period. Finally,Jamming Detection and Identification System’s detection and recognition performance to single tone interference, multi-tone interference, narrowband interference under the IF and RF , while simulation the system’s detection sensitivity of the above three jamming. Under both in the Gaussian white noise and Gaussian white noise and TDCS signals, analysis system’s detection and recognition performance to single tone interference, multi-tone interference, narrowband interference.
SDR test draw the following conclusions:IF under Gaussian white noise, for single-tone interference,four single tone interference, 2.4MHz Partial-Band interference,When Jamming-to-Noise power Ratio is respectively greater than -24dB, -21dB, -0.53dB,the system detection probability is greater than 99%;IF under TDCS,the single-tone interference,three single tone interference,When Jamming-to-Signal power Ratio is respectively greater than -32.2dB, -26.24dB, the system detection probability is greater than 99%;Under 400MHz RF, the single tone interference, four single tone interference, 2MHz Partial-Band interference,When JNR is respectively greater than -27.1dB, -19dB, -3.5dB,the System detection probability approaching 1;400MHz RF under TDCS,for the single-tone interference, when JSR is greater than -34dB, for two single tone interference, when JSR is greater than -30dB, for 150KHz Partial-Band interference, when JSR is greater than -20dB, the System detection probability approaching 1, better than the system requirements when JSR is greater than 0dB can accurately detect and identify interference.
首先,本文对能量检测基本理论进行分析,给出了能量检测的性能评估方法及其优缺点,并着重分析了两种基于频域的连续均值消除(Consecutive Mean Excision ,CME)和前向连续均值消除(Forward Consecutive Mean Excision ,FCME)干扰检测算法,在此基础上提出了一种基于子带误码率统计的干扰检测算法;其次,硬件实现了一个基于模块的干扰检测系统,并对系统中时序控制,数据速率变换,频谱叠加,频谱输出等模块设计进行了详细分析,在此基础上硬件设计并实现了一种基于静默周期干扰检测链路;最后,结合设计的干扰检测与识别界面,硬件实测了干扰检测与识别系统在中频和射频下对单音干扰、多音干扰、部分带干扰的检测与识别性能,硬件实测了系统对上面三种干扰的检测灵敏度;实测干扰检测系统在高斯白噪声、高斯白噪声和变换域通信系统(Transform Domain Communication System,TDCS)信号同时存在两种情况下对单音、多音、部分带三种干扰的检测与识别性能。
硬件测试得出下面结论:中频高斯白噪声下,对于单音干扰,四个单音干扰,2.4MHz的部分带干扰( Partial-Band Interference , PBI ),当干噪比分别(Jamming-to-Noise power Ratio,JNR)大于-24.5dB,-21dB,-0.53dB时,系统检测概率大于99%;中频TDCS信号下,对于单音干扰,三个单音干扰,当干信比(Jamming-to-Signal power Ratio ,JSR)分别大于-32.2dB,-26.24dB时,系统检测概率大于99%;400MHz射频条件下,对于单音干扰,四个单音干扰,2MHz的部分带干扰,当干噪比分别大于-27.1dB,-19dB,-3.5dB时,系统检测概率逼近1;400MHz射频TDCS信号存在条件下,对于单音干扰,当JSR大于-34dB,对于2个单音干扰,当JSR大于-30dB,对于150KHMz的部分带干扰,当JSR大于-20dB,系统检测概率逼近1,优于系统要求JSR大于0dB时能够准确检测和识别出干扰的目标。
As wireless communications technology development, wireless communication environment become more and more perplexed, more and more interference in wireless communication environment, jamming and anti-jamming technology to become an important research area. Reserch the anti-interference performance of a communication system, communication system can accurately detecting the interference signal at first, and then be able to take anti-jamming technology effectively; In Electronic Warfare, Investigation and anti-reconnaissance technology to be used in both of two sides; Identification the authorized signal in cognitive radio, which are inseparable from the interference detection technology. This article mainly studied several typical interference's (Single-tone interference , multi-tone interference , Partial-band interference)detection and identification technology, and take SDR hardware platforms and PC together, to achieve the interference detection and identifying system.Respectively in the Intermediate Frequency and Radio Frequency , test several typical interference's detection and identifying performance , the test results meet system requirements.
Firstly,the article details the interference’s detecting and identifying process, while the basic method of energy detection techniques and theories were analyzed, gives its performance evaluation of energy detection and its advantages and disadvantages, and analyzing both Consecutive Mean Excision and Forward Consecutive Mean Excision detecting algorithm’s domain ideal and implementation steps.Based on the above thoughts, a statistical error rate based on sub-band interference detection algorithm is proposed. Secondly,this article study the jamming detection system based on the module design method, described the detection system timing control, data rate conversion, spectrum overlay design, spectrum output control. On this basis, designs a Jamming Detect System with silent period. Finally,Jamming Detection and Identification System’s detection and recognition performance to single tone interference, multi-tone interference, narrowband interference under the IF and RF , while simulation the system’s detection sensitivity of the above three jamming. Under both in the Gaussian white noise and Gaussian white noise and TDCS signals, analysis system’s detection and recognition performance to single tone interference, multi-tone interference, narrowband interference.
SDR test draw the following conclusions:IF under Gaussian white noise, for single-tone interference,four single tone interference, 2.4MHz Partial-Band interference,When Jamming-to-Noise power Ratio is respectively greater than -24dB, -21dB, -0.53dB,the system detection probability is greater than 99%;IF under TDCS,the single-tone interference,three single tone interference,When Jamming-to-Signal power Ratio is respectively greater than -32.2dB, -26.24dB, the system detection probability is greater than 99%;Under 400MHz RF, the single tone interference, four single tone interference, 2MHz Partial-Band interference,When JNR is respectively greater than -27.1dB, -19dB, -3.5dB,the System detection probability approaching 1;400MHz RF under TDCS,for the single-tone interference, when JSR is greater than -34dB, for two single tone interference, when JSR is greater than -30dB, for 150KHz Partial-Band interference, when JSR is greater than -20dB, the System detection probability approaching 1, better than the system requirements when JSR is greater than 0dB can accurately detect and identify interference.
引文
[1]陈伟.认知无线电中的频谱感知与干扰评估技术研究[D]. [硕士学位论文].成都:电子科技大学,2010.
[2]张睿.软件无线电中的信号检测技术研究[D].[博士学位论文].西安:西安电子科技大学,2001.
[3] Bin Shen, Chengshi Zhao,Longyang Huang,Zheng Zhou,Kyungsup Kwak, "Signal Contiguity Based Wideband Spectrum Sensing for Dynamic Spectrum Access Systems," [C] Communications and Information Technologies,2008.ISCIT 2008. International Symposium , vol, pp.126-130, 21-23 Oct. 2008.
[4]潘建国,翟旭平.基于能量检测的频谱感知方法[J].上海大学学报.2009,1期:54-59.
[5]隋丹,葛临东.突发信号盲存在性检测的两种算法[J].信号处理.2008,5期:863-866.
[6]赵雯雯.基于EMD的通信盲侦察技术研究:[D]. [硕士学位论文].西安:西安电子科技大学, 2008.
[7]徐启华.短波宽带侦察中的信号分选与检测[D]. [硕士学位论文].西安:西安电子科技大学, 2006.
[8]杨敏军,邱玲.一种直扩信号的检测方法[J].计算机仿真.2007,9期:322-324.
[9]薛巍,向敬成,周治中.一种直扩通信系统窄带干扰变换域抑制方法[J].信号处理.2002,4期:366-369.
[10]殷复莲,郭黎利,卢满宏.扩频测控系统常见干扰检测技术研究[J].系统工程与电子技术.2009,9期:2195-2199.
[11]彭任斌,金力军.一种自适应跳频中的干扰检测算法[J].电子科技大学学报.2006,3:464-467.
[12]樊明,魏泽鼎,郭艺. DSSS频域干扰检测方法研究[J].现代电子技术, 2007, 13期总第252期.
[13]郭丽萍. DQPSK数字卫星通信系统中FFT干扰检测方法研究[J].空间电子技术, 2002, 3期: 37-42.
[14]程郁凡,韩玮,李少谦.基于FFT的快速跳频同步信号存在性检测[J].电子科大学报,Vol.32 No.5 Oct,2003.
[15]蒋磊,王永生许华,郭建新. UWB通信系统中的窄带干扰检测算法研究[J].系统工程与电子技术.2009,5期:1035-1039.
[16] H.Urkowitz,“Energy detection of unknown deterministic signals”[J],Proc. IEEE, vol. 55, no. 4, pp.523–531, Apr.1967.
[17] V.I.Kostylev,“Energy detection of a signal with random amplitude,”[J]in Proc. IEEE ICC, Jun. 2002, pp. 1606–1610.
[18] F.F.Digham, M.Alouini, and M.K.Simon.“On the energy detection of unknown signals over fading channels”[C]. In Proc.IEEE International Conference on Communications 2003 (ICC’03), pages 3575– 3579,May 2003.
[19] E. J. Salt and H. H. Nguyen,“Performance prediction for energy detection of unknown signals,”[J] Vehicular Technology , IEEE Transactions on. vol. 57, no. 6, Nov. 2008, pp. 3900–3904
[20] P.Henttu and S.Aromaa,“Consecutive mean excision algorithm,”[C] in IEEE 7th International Symposium on Spread Spectrum Techniques and Applications (ISSSTA), September 2-5, Prague, Czech Republic, 2002,vol. 2, pp. 450– 454.
[21] Johanna Vartiainen, Janne J.Lehtomaki, Harri Saarnisaari, "Estimation of signal detection threshold by CME algorithms," [C]Vehicular Technology Conference, 2004. VTC 2004-Spring. 2004 IEEE 59th , vol.3, no., pp. 1654- 1658 Vol.3, 17-19 May 2004
[22] P. Henttu and S. Aromaa Conseeurive Mean Excision Algon'rhm. [C] In IEEE 7th Symposium on Spread-Specmm Techniques and Applications.pages 450-454, Pragues Czech Republic, Sept. 2-5, 2002.
[23] Huy Quang Quach, Anh Van Dinh, "Narrowband Interference Detection in UWB Systems," [C] Electrical and Computer Engineering, 2006. CCECE '06. Canadian Conference on , vol., no., pp.904-907, May 2006.
[24] Oscar V. Gonzalez, Wilfrido A..Moreno , "Narrowband interference detection in multiband UWB systems," [C] Advances in Wired and Wireless Communication, 2005 IEEE Sarnoff Symposium on , vol., no., pp.160-163, 18-19 April 2005
[25] W. Tao, W. Yong, and C. Kangsheng,“Analyzing the interference power of narrowband jamming signal on UWB system," [J]in Proc. IEEE Personal, Indoor, Mobile Radio Commun. (PIMRC), Singapore, Sep.2003, pp. 612-615.
[26] L. Zhao and A. Haimovich,“Performance of ultra-wideband communications in the presence of interference," [C] IEEE J. Select. Areas Commun., vol. 20, pp. 1684-1691, Dec. 2002.
[27] J. Romme, J. Siemons, G. Durisi.“A method for the detection of narrowbandinterferer”[J] .In Proc. IEEE, Int. workshop on Ultra Wideband Systems (IWUWBS), Oulu, June 2003.
[28] I. Bergel, E. Fishler, and H. Messer,“Narrow band interference suppression in impulse radio systems," [C] Submitted to IEEE Trans.Commun., 2004.
[29] MEDLEY M J, SAULNIER G J, DAS P K. Narrow-band interference excision in spread spectrum systems using lapped transform[C]. IEEE Transactions on Communications, 1997, 45(11): 1444-1455.
[30]吴国亮.基于变换域抗窄带干扰技术研究及FPGA设计[D]: [硕士学位论文].西安:西安电子科技大学, 2009.
[31]张巍峰.宽带干扰检测接收机设计[D]:[硕士学位论文].武汉:华中科技大学, 2006.
[32]张辰光.数字通信系统噪声干扰方法与仿真[D]: [硕士学位论文].西安:西安电子科技大学, 2007.
[33]罗华飞. MATLAB GUI设计学习手记北京:北京航空航天大学, 2009.
[2]张睿.软件无线电中的信号检测技术研究[D].[博士学位论文].西安:西安电子科技大学,2001.
[3] Bin Shen, Chengshi Zhao,Longyang Huang,Zheng Zhou,Kyungsup Kwak, "Signal Contiguity Based Wideband Spectrum Sensing for Dynamic Spectrum Access Systems," [C] Communications and Information Technologies,2008.ISCIT 2008. International Symposium , vol, pp.126-130, 21-23 Oct. 2008.
[4]潘建国,翟旭平.基于能量检测的频谱感知方法[J].上海大学学报.2009,1期:54-59.
[5]隋丹,葛临东.突发信号盲存在性检测的两种算法[J].信号处理.2008,5期:863-866.
[6]赵雯雯.基于EMD的通信盲侦察技术研究:[D]. [硕士学位论文].西安:西安电子科技大学, 2008.
[7]徐启华.短波宽带侦察中的信号分选与检测[D]. [硕士学位论文].西安:西安电子科技大学, 2006.
[8]杨敏军,邱玲.一种直扩信号的检测方法[J].计算机仿真.2007,9期:322-324.
[9]薛巍,向敬成,周治中.一种直扩通信系统窄带干扰变换域抑制方法[J].信号处理.2002,4期:366-369.
[10]殷复莲,郭黎利,卢满宏.扩频测控系统常见干扰检测技术研究[J].系统工程与电子技术.2009,9期:2195-2199.
[11]彭任斌,金力军.一种自适应跳频中的干扰检测算法[J].电子科技大学学报.2006,3:464-467.
[12]樊明,魏泽鼎,郭艺. DSSS频域干扰检测方法研究[J].现代电子技术, 2007, 13期总第252期.
[13]郭丽萍. DQPSK数字卫星通信系统中FFT干扰检测方法研究[J].空间电子技术, 2002, 3期: 37-42.
[14]程郁凡,韩玮,李少谦.基于FFT的快速跳频同步信号存在性检测[J].电子科大学报,Vol.32 No.5 Oct,2003.
[15]蒋磊,王永生许华,郭建新. UWB通信系统中的窄带干扰检测算法研究[J].系统工程与电子技术.2009,5期:1035-1039.
[16] H.Urkowitz,“Energy detection of unknown deterministic signals”[J],Proc. IEEE, vol. 55, no. 4, pp.523–531, Apr.1967.
[17] V.I.Kostylev,“Energy detection of a signal with random amplitude,”[J]in Proc. IEEE ICC, Jun. 2002, pp. 1606–1610.
[18] F.F.Digham, M.Alouini, and M.K.Simon.“On the energy detection of unknown signals over fading channels”[C]. In Proc.IEEE International Conference on Communications 2003 (ICC’03), pages 3575– 3579,May 2003.
[19] E. J. Salt and H. H. Nguyen,“Performance prediction for energy detection of unknown signals,”[J] Vehicular Technology , IEEE Transactions on. vol. 57, no. 6, Nov. 2008, pp. 3900–3904
[20] P.Henttu and S.Aromaa,“Consecutive mean excision algorithm,”[C] in IEEE 7th International Symposium on Spread Spectrum Techniques and Applications (ISSSTA), September 2-5, Prague, Czech Republic, 2002,vol. 2, pp. 450– 454.
[21] Johanna Vartiainen, Janne J.Lehtomaki, Harri Saarnisaari, "Estimation of signal detection threshold by CME algorithms," [C]Vehicular Technology Conference, 2004. VTC 2004-Spring. 2004 IEEE 59th , vol.3, no., pp. 1654- 1658 Vol.3, 17-19 May 2004
[22] P. Henttu and S. Aromaa Conseeurive Mean Excision Algon'rhm. [C] In IEEE 7th Symposium on Spread-Specmm Techniques and Applications.pages 450-454, Pragues Czech Republic, Sept. 2-5, 2002.
[23] Huy Quang Quach, Anh Van Dinh, "Narrowband Interference Detection in UWB Systems," [C] Electrical and Computer Engineering, 2006. CCECE '06. Canadian Conference on , vol., no., pp.904-907, May 2006.
[24] Oscar V. Gonzalez, Wilfrido A..Moreno , "Narrowband interference detection in multiband UWB systems," [C] Advances in Wired and Wireless Communication, 2005 IEEE Sarnoff Symposium on , vol., no., pp.160-163, 18-19 April 2005
[25] W. Tao, W. Yong, and C. Kangsheng,“Analyzing the interference power of narrowband jamming signal on UWB system," [J]in Proc. IEEE Personal, Indoor, Mobile Radio Commun. (PIMRC), Singapore, Sep.2003, pp. 612-615.
[26] L. Zhao and A. Haimovich,“Performance of ultra-wideband communications in the presence of interference," [C] IEEE J. Select. Areas Commun., vol. 20, pp. 1684-1691, Dec. 2002.
[27] J. Romme, J. Siemons, G. Durisi.“A method for the detection of narrowbandinterferer”[J] .In Proc. IEEE, Int. workshop on Ultra Wideband Systems (IWUWBS), Oulu, June 2003.
[28] I. Bergel, E. Fishler, and H. Messer,“Narrow band interference suppression in impulse radio systems," [C] Submitted to IEEE Trans.Commun., 2004.
[29] MEDLEY M J, SAULNIER G J, DAS P K. Narrow-band interference excision in spread spectrum systems using lapped transform[C]. IEEE Transactions on Communications, 1997, 45(11): 1444-1455.
[30]吴国亮.基于变换域抗窄带干扰技术研究及FPGA设计[D]: [硕士学位论文].西安:西安电子科技大学, 2009.
[31]张巍峰.宽带干扰检测接收机设计[D]:[硕士学位论文].武汉:华中科技大学, 2006.
[32]张辰光.数字通信系统噪声干扰方法与仿真[D]: [硕士学位论文].西安:西安电子科技大学, 2007.
[33]罗华飞. MATLAB GUI设计学习手记北京:北京航空航天大学, 2009.