基于相关循环谱方法的直扩信号检测与参数估计研究
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摘要
扩频通信由于具有抗干扰能力强、截获率低、良好的码分多址能力等优点,被广泛地应用于移动通信、雷达、导航和定位等领域。在通信侦察和频谱监测等非协作通信领域中,由于信噪比低和先验知识条件缺乏,以至直接序列扩频信号的检测与参数估计难于实现,使之成为当前这一领域中的重要研究课题。
由于直接序列扩频信号的带宽远大于基带信号带宽,能量分布于更宽的频带,且功率谱密度很低,以至于通常淹没在噪声中。正是由于这些特点使得直接序列扩频信号难于检测,且在伪随机序列未知的前提下,即使检测到了也难以恢复待传输的信息,导致常规处理方法在此情况下将失效。目前,对于直接序列扩频信号的检测和参数估计已有一些方法,这些方法对于单一参数具有良好的检测结果,但在低信噪比情况下性能趋于恶化。
本文主要研究了时域相关检测、延时相乘、相关累积、循环谱检测等方法,在归纳前人理论的基础上,采用了改进方法,主要研究成果如下:
1.在直扩信号检测及伪码周期的参数估计方面,分析常规时域相关检测方法的基础上,采用了时域相关二阶矩检测方法,对信号进行分段自相关运算,然后均方迭加平均相关数据。此法有效地抑制噪声,实现了在低信噪比的条件下直接序列扩频信号伪码周期的准确估计。
2.在延时相乘法的基础上,分析了在相关域上可检测出伪码的周期特性,在频域上可检测出伪码速率和载频参数的特点,并结合自适应噪声抵消器、相关累积方法和频谱校正方法,组成了时域延时相关检测系统。在低信噪比条件下,可实现对直接序列扩频信号的伪码周期、伪码速率和载频的准确估计。
3.为实现更低信噪比条件下的直接序列扩频信号检测与参数估计,在循环谱理论的基础上,分析了循环统计量抑制平稳噪声的能力,采用了基于Welch法的集平均循环谱方法,对信号分段使用频域平滑循环周期图算法后,进行迭加平均。此法可有效利用循环谱包络估计出直接序列扩频信号的伪码速率、载频参数。实验证明,以上三种改进方法在低信噪比条件下具有良好的估计效果,对于直接序列扩频信号的盲解扩具有一定的意义。
The spread spectrum communication depended on good anti-interference ability, low probability of interception and the advantages of CDMA, was widely used in mobile communication, radar, navigation, orientation and other fields. In the area of non-cooperative communication such as communication reconnaissance and spectrum monitoring, owing to low SNR and lacking of priori knowledge, direct sequence spread spectrum(DSSS) signal detection and parameters estimation were difficult to achieve those have become an important issue.
Since the bandwidth of DSSS signal was much larger than the bandwidth of baseband signal, thus energy of DSSS signal was distributed in the much wider bandwidth, power spectrum density was very low so as to submerge in the noise. These features made DSSS signal difficult to detect, or it was difficult to restore the information which was transmitted in the premise of the unknown pseudo-random(PN) sequence. This made the conventional approach invalid at low SNR. At present, there had been some methods for DSSS signal detection and parameters estimation. These methods were good for test results of single parameters. However, for DSSS signal, detection performance tended to deteriorate at low SNR.
In this dissertation, time-domain correlation detection, delay-multiply, correlation cumulation, cyclic spectrum and other methods were considered. On the base of predecessors’studies, the improved methods were presented here.
1. In the dissertation, in order to detect DSSS signal and estimate the period of PN, time-domain second-order moment detection was proposed based on time-domain correlation detection. The DSSS signal was cut up into several segments in this method, their correlation functions were obtained, and then the mean for superposition of square of correlation data was calculated. This method is able to suppress the additive white Gaussian noise so as to achieve an accurate estimation of the period of PN at low SNR.
2. Based on delay-multiply detection, it indicated that the period of PN showed on the correlation domain, in addition, chip rate and carrier frequency displayed on the frequency domain. This method combined the formers with adaptive noise cancellation, correlation cumulation and spectrum correction in order to compose a detection system of time-domain delay correlation. It can estimate the period of PN, chip rate and carrier frequency accurately.
3. In order to achieve DSSS signal detection and parameters estimation at lower SNR, cyclic statistics had the ability to suppress stationary noise based on cyclic spectrum theory. Improved set-average cyclic spectrum based on Welch method was proposed in this paper. DSSS signal that was divided into several sections used frequency smoothed cyclic periodogram algorithm, then the results for computing the mean were added up. This method used the envelope of cyclic spectrum to estimate the chip rate and carrier frequency, and it had high accuracy.
The simulation showed that the aboved methods can achieve high precision at the low SNR in non-cooperative communication, and had important significance for blind despreading.
由于直接序列扩频信号的带宽远大于基带信号带宽,能量分布于更宽的频带,且功率谱密度很低,以至于通常淹没在噪声中。正是由于这些特点使得直接序列扩频信号难于检测,且在伪随机序列未知的前提下,即使检测到了也难以恢复待传输的信息,导致常规处理方法在此情况下将失效。目前,对于直接序列扩频信号的检测和参数估计已有一些方法,这些方法对于单一参数具有良好的检测结果,但在低信噪比情况下性能趋于恶化。
本文主要研究了时域相关检测、延时相乘、相关累积、循环谱检测等方法,在归纳前人理论的基础上,采用了改进方法,主要研究成果如下:
1.在直扩信号检测及伪码周期的参数估计方面,分析常规时域相关检测方法的基础上,采用了时域相关二阶矩检测方法,对信号进行分段自相关运算,然后均方迭加平均相关数据。此法有效地抑制噪声,实现了在低信噪比的条件下直接序列扩频信号伪码周期的准确估计。
2.在延时相乘法的基础上,分析了在相关域上可检测出伪码的周期特性,在频域上可检测出伪码速率和载频参数的特点,并结合自适应噪声抵消器、相关累积方法和频谱校正方法,组成了时域延时相关检测系统。在低信噪比条件下,可实现对直接序列扩频信号的伪码周期、伪码速率和载频的准确估计。
3.为实现更低信噪比条件下的直接序列扩频信号检测与参数估计,在循环谱理论的基础上,分析了循环统计量抑制平稳噪声的能力,采用了基于Welch法的集平均循环谱方法,对信号分段使用频域平滑循环周期图算法后,进行迭加平均。此法可有效利用循环谱包络估计出直接序列扩频信号的伪码速率、载频参数。实验证明,以上三种改进方法在低信噪比条件下具有良好的估计效果,对于直接序列扩频信号的盲解扩具有一定的意义。
The spread spectrum communication depended on good anti-interference ability, low probability of interception and the advantages of CDMA, was widely used in mobile communication, radar, navigation, orientation and other fields. In the area of non-cooperative communication such as communication reconnaissance and spectrum monitoring, owing to low SNR and lacking of priori knowledge, direct sequence spread spectrum(DSSS) signal detection and parameters estimation were difficult to achieve those have become an important issue.
Since the bandwidth of DSSS signal was much larger than the bandwidth of baseband signal, thus energy of DSSS signal was distributed in the much wider bandwidth, power spectrum density was very low so as to submerge in the noise. These features made DSSS signal difficult to detect, or it was difficult to restore the information which was transmitted in the premise of the unknown pseudo-random(PN) sequence. This made the conventional approach invalid at low SNR. At present, there had been some methods for DSSS signal detection and parameters estimation. These methods were good for test results of single parameters. However, for DSSS signal, detection performance tended to deteriorate at low SNR.
In this dissertation, time-domain correlation detection, delay-multiply, correlation cumulation, cyclic spectrum and other methods were considered. On the base of predecessors’studies, the improved methods were presented here.
1. In the dissertation, in order to detect DSSS signal and estimate the period of PN, time-domain second-order moment detection was proposed based on time-domain correlation detection. The DSSS signal was cut up into several segments in this method, their correlation functions were obtained, and then the mean for superposition of square of correlation data was calculated. This method is able to suppress the additive white Gaussian noise so as to achieve an accurate estimation of the period of PN at low SNR.
2. Based on delay-multiply detection, it indicated that the period of PN showed on the correlation domain, in addition, chip rate and carrier frequency displayed on the frequency domain. This method combined the formers with adaptive noise cancellation, correlation cumulation and spectrum correction in order to compose a detection system of time-domain delay correlation. It can estimate the period of PN, chip rate and carrier frequency accurately.
3. In order to achieve DSSS signal detection and parameters estimation at lower SNR, cyclic statistics had the ability to suppress stationary noise based on cyclic spectrum theory. Improved set-average cyclic spectrum based on Welch method was proposed in this paper. DSSS signal that was divided into several sections used frequency smoothed cyclic periodogram algorithm, then the results for computing the mean were added up. This method used the envelope of cyclic spectrum to estimate the chip rate and carrier frequency, and it had high accuracy.
The simulation showed that the aboved methods can achieve high precision at the low SNR in non-cooperative communication, and had important significance for blind despreading.
引文
[1]田日才.扩频通信[M].北京:清华大学出版社, 2007. 10-21.
[2]查光明,熊贤柞.扩频通信[M].西安:西安电子科技大学出版社, 1997. 30-33 48-61.
[3] W. A. Gardner. Signal Interception: A Unifying Theoretical Framework for Feature Detection[J]. IEEE Trans. on Communication. 1988, 36(8): 897-906.
[4]何世彪,谭晓衡.扩频技术及其实现[M].北京:电子工业出版社, 2007. 46-57 65-78.
[5] H. Urkowitz. Energy Detection of Unknown Deterministic Signal[J]. Proceedings of IEEE. 1967, 55(4): 523-531.
[6] A. Polydoros, J. K. Holmes. Autocorrelation Techniques for Wideband Detection of FH/DS Waveform in Random Tone Interference[A]. IEEE Military Communications Conference[C]. Washington, DC, USA, 1983: 776-780.
[7] A. Polydoros, C. L. Weber. Detection Performance Considerations for Direct-Sequence and Time-Hopping LPI Waveforms[J]. IEEE Journal on SAC. 1985, 3(5): 727-744.
[8] D. E. Reed, M. A. Wickert. Minimization of Detection of Symbol-Rate Spectral Lines by Delay and Multiply Receivers[J]. IEEE Trans. on Communication. 1988, 36(1): 118-120.
[9] J. F. Kuehls, E. Geraniotis. Presence Detection of Binary-Phase-Shift-Keyed and Direct-Sequence Spread-Spectrum Signals Using a Prefilter-Delay-and-Multiply Device[J]. IEEE Journal on SAC. 1990, 8(5): 915-933.
[10] G. Burel, G. Bouder. Blind Estimation of the Pseudo-Random Sequence of a Direct Sequence Spectrum Signal[J]. IEEE Trans. on Communication. 2000, 40(3): 967-970.
[11]董占奇,胡捍英,于宏毅.基于延时相乘-相关及谱分析的直扩信号检测与符号周期、码片时宽估计分析[J].电子与信息学报. 2008, 30(4): 840-842.
[12]石明军,徐振平,肖立民.基于延时相乘结构的直扩载波最优检测[J].清华大学学报(自然科学版). 2009, 49(7): 953-956.
[13] Minquan Lu, Xianci Xiao. Detection of DS/SS Signal Using Fourth-Order Spectrum[J]. Proceeding of ICSP’93. 1993, 39(11): 2436-2449.
[14]沈振惠.基于四阶统计2-D切片的直扩信号多参数估计[J].信号处理. 2005, 21(3): 304-306.
[15]韩高莉,田红心.基于高阶累积量的低信噪比直扩信号盲检测的实现[J].空间电子技术. 2006, 3(2): 24-28.
[16] Zhenhui Shen, Bin Tang. Multiple Parameters Estimation Simultaneously for DS-SS/BPSK Signal Based on Fourth-Order Cumulate 2-D Slice[A]. IEEE International Conference on CommunicationsCircuits and Systems[C]. 2004, 2: 867-870.
[17] W. A. Gardner, C. M. Spooner. Detection and Source Location of Weak Cyclostationary Signals: Simplifications of the Maximum Likehood Receiver[J]. IEEE Trans. on Communication. 1993, 41(6): 905-916.
[18] W. A. Gardner, C. M. Spooner. Signal Interception: Performance Advantages of Cyclic-Feature Detectors[J]. IEEE Trans. on Communication. 1992, 40(1): 149-159.
[19] W. A. Gardner. Exploitation of Spectral Redundancy in Cyclostationary Signals[J]. IEEE Signal Processing Magazine. 1991, 8(2): 14-36.
[20]史建峰,朱良学,冯辉.基于循环谱包络的BPSK码元速率估计算法研究[J].系统工程与电子技术. 2007, 29(2): 186-189.
[21]杨敏军,邱玲.一种直扩信号的检测方法[J].计算机仿真. 2007, 24(9): 322-324.
[22] A. V. Oppenheim, R. W. Schafer. From Frequency to Quefrency: A History of the Cepstrum[J]. IEEE Signal Processing Magazine. 2004, 21(5): 95-106.
[23] R. Kemerait, D. Childers. Signal Detection and Extraction by Cepstrum Techniques Information Theory[J]. IEEE Trans. on Information Theory. 1972, 18(6): 745–759.
[24]张天骐,周正中.低信噪比长伪码直扩信号伪码周期的估计方法[J].系统工程与电子技术. 2007, 29(1): 12-16.
[25]张天骐,林孝康,周正中等.一种直扩信号基带码周期及序列的盲估计方法[J].电波科学学报. 2005, 20(3): 400-405.
[26]张天骐,周正中,郭宗祥.一种DS/SS信号PN码序列估计的神经网络方法[J].信息技术. 2001, 17(16): 534-537.
[27] G. Burel,C. Bouder. Blind Estimation of the Pseudo-Random Sequence of a Direct Sequence Spread Spectrum Signal[A]. 21st Century Military Communications Conference Proceedings[C]. Los Angeles, CA, USA, 2000, 2: 967-970.
[28] Yingxiang Li, Min Yi, Qin Yang, et al. Low SNR BPSK Signal Chip Rate Estimation Using a Wavelet Based Spectral Correlation Algorithm[J]. IEEE Trans. on Circuits and Systems. 2002, (3): 247-249.
[29] C. M. Spooner, W. A. Gardner. Exploitation of High-Order Cyclostationarity for Weak Signal Detection and Time Delay Estimation[J]. Proceedings of IEEE. 1992, 11(4): 197-201.
[30]朱近康.扩展频谱通信及其应用[M].安徽:中国科学技术大学出版社, 1993. 16-42.
[31]苟彦新.无线电抗干扰通信原理及应用[M].西安:西安电子科技大学出版社, 2005. 37-49.
[32]韦惠民.扩频通信技术及应用[M].西安:西安电子科技大学出版社, 2007. 20-23.
[33]沈丽丽,侯永宏,马兰.扩频通信导论[M].北京:电子工业出版社, 2006. 38-46.
[34] J. G. Proakis, M. Salehi, G. Bauch.现代通信系统[M].刘树棠.第二版.北京:电子工业出版社,2005. 315-319.
[35]樊昌信,曹丽娜.通信原理[M].北京:国防工业出版社, 2007. 380-383 384-389.
[36]王晓燕,方世良,朱志峰.一种基于自相关估计的水声直扩信号检测方法[J].东南大学学报(自然科学版). 2010, 40(2): 248-252.
[37]李锐,何辅云,夏玉宝.相关检测原理及其应用[J].合肥工业大学学报(自然科学版). 2008, 31(4): 573-579.
[38]黄硕翼,石荣,陈锡明.基于码周期的延时相乘法估计扩频QPSK信号的载频[J].电子信息对抗技术. 2007, 6(22): 9-11.
[39]孙铭芳.直扩信号检测和PN码参数估计的研究[D].哈尔滨:哈尔滨工业大学硕士学位论文. 2006: 27-49.
[40]刘基南,袁亮,高梅国.一种直扩信号伪码速率的快速检测方法[J].现代防御技术. 2005, 33(1): 62-64.
[41]聂祥飞.基于LMS算法的自适应噪声抵消器研究[J].三峡学院学报. 2002, 18(2): 112-116.
[42]曹亚丽.自适应滤波器中LMS算法的应用[J].仪器仪表学报. 2005, 26(8): 452-454.
[43]田玉静,左红伟.自适应噪声抵消的应用研究[J].青岛建筑工程学院学报. 2005, 26(1): 77-80.
[44]吴正茂.自适应滤波器及其应用研究[J].南昌水专学报. 2004, 23(2): 36-45.
[45]沈福民.自适应信号处理[M].西安:西安电子科技大学出版社, 2001. 211-222.
[46]朱小芳,陈亚光.噪声对消在信号处理系统中的应用[J].现代电子技术. 2006, 29(24): 86-88.
[47]刘进明,应怀樵. FFT谱连续细化分析的傅里叶变换法[J].振动工程学报. 1995, 8(2): 162-166.
[48]丁康,江利旗.离散频谱的能量重心校正法[J].振动工程学报. 2001, 14(3): 354-358.
[49]谢明,丁康.频谱分析的校正方法[J].振动工程学报. 1994, 7 (2) : 172-179.
[50] Ming Xie, Kang Ding. Corrections for Frequency, Amplitude and Phase in Fast Fourier Transform of a Harmonic Signal[J]. Mechanical System and Signal Process. 1996, 10(2): 211-221.
[51] Jian Meng. Correlation Cumulation for Detection of DS Signal[J]. Electronic Warfare Technology. 2001, 16(2): 1-5.
[52]张邦宁,魏安全,郭道省.通信抗干扰技术[M].北京:机械工业出版社, 2006. 16-17.
[53]侯峥峰,熊辉.直扩信号的参数估计[J].计算机仿真. 2009, 26(10): 352-355.
[54]张贤达,保铮.非平稳信号分析与处理[M].北京:国防工业出版社, 1998. 325-351.
[55] W. A. Gardner. Spectral Correlation of Modulated Signals: Part I-Analog Modulation[J]. IEEE Trans. on Communication. 1987, 35(6): 584-594.
[56]陶雷,武传华.直扩信号检测和参数估计技术研究[J].船舶电子对抗. 2006, 29(1): 35-39.
[57]雷开洪,游庆山.基于循环平稳特性的直扩信号检测与参数估计[J].四川大学学报(自然科学版). 2010, 47(1): 44-47.
[58] W. A. Gardner. The Spectral Correlation Theory of Cyclostationary Time-Series[J]. SignalProcessing. 1986, 11(1): 13-36.
[59] Yan Jin, Hongbing Ji, Junhui Luo. A Cyclic-Cumulant Based Method for DS-SS Signal Detection and Parameter Estimation[J]. Acta Electronica Sinica. 2006, 34(4): 634-637.
[60] W. A. Gardner. Measurement of Spectral Correlation[J]. IEEE Trans. on ASSP. 1986, 34(5): 1111-1123.
[61]戴乐,张海波.直扩信号的循环平稳特性分析[J].系统工程与电子技术. 2004, 26(8): 1038-1052.
[62]黄知涛,周一宇,姜文利.循环平稳信号处理及其应用研究[M].长沙:国防科技大学出版社, 2007. 56-134.
[63]万建伟,王玲.信号处理仿真技术[M].北京:国防科技大学出版社, 2008. 27-55.
[64] Chunlin Huang, Zheng Liu. Chip Width Carrier Frequency and Amplitude Estimation of DS Signal Based on Cyclic Spectrum Amplitude[J]. Acta Electronica Sinica. 2002, 30(9): 1353-1356.
[65]陈四根,杨莘元. QPSK信号谱相关性质研究[J].哈尔滨工程大学学报. 2003, 24(2): 208-211.
[66]赵培聪,高翔,刘重阳.基于改进谱相关算法的信号抗噪性能分析[J].现代雷达. 2010, 32(1): 66-69.
[67]汪赵华,陈昊,郭立.基于频域平滑循环周期图法的直接序列扩频信号的参数估计[J].中国科学技术大学学报. 2010, 40(5): 466-473.
[2]查光明,熊贤柞.扩频通信[M].西安:西安电子科技大学出版社, 1997. 30-33 48-61.
[3] W. A. Gardner. Signal Interception: A Unifying Theoretical Framework for Feature Detection[J]. IEEE Trans. on Communication. 1988, 36(8): 897-906.
[4]何世彪,谭晓衡.扩频技术及其实现[M].北京:电子工业出版社, 2007. 46-57 65-78.
[5] H. Urkowitz. Energy Detection of Unknown Deterministic Signal[J]. Proceedings of IEEE. 1967, 55(4): 523-531.
[6] A. Polydoros, J. K. Holmes. Autocorrelation Techniques for Wideband Detection of FH/DS Waveform in Random Tone Interference[A]. IEEE Military Communications Conference[C]. Washington, DC, USA, 1983: 776-780.
[7] A. Polydoros, C. L. Weber. Detection Performance Considerations for Direct-Sequence and Time-Hopping LPI Waveforms[J]. IEEE Journal on SAC. 1985, 3(5): 727-744.
[8] D. E. Reed, M. A. Wickert. Minimization of Detection of Symbol-Rate Spectral Lines by Delay and Multiply Receivers[J]. IEEE Trans. on Communication. 1988, 36(1): 118-120.
[9] J. F. Kuehls, E. Geraniotis. Presence Detection of Binary-Phase-Shift-Keyed and Direct-Sequence Spread-Spectrum Signals Using a Prefilter-Delay-and-Multiply Device[J]. IEEE Journal on SAC. 1990, 8(5): 915-933.
[10] G. Burel, G. Bouder. Blind Estimation of the Pseudo-Random Sequence of a Direct Sequence Spectrum Signal[J]. IEEE Trans. on Communication. 2000, 40(3): 967-970.
[11]董占奇,胡捍英,于宏毅.基于延时相乘-相关及谱分析的直扩信号检测与符号周期、码片时宽估计分析[J].电子与信息学报. 2008, 30(4): 840-842.
[12]石明军,徐振平,肖立民.基于延时相乘结构的直扩载波最优检测[J].清华大学学报(自然科学版). 2009, 49(7): 953-956.
[13] Minquan Lu, Xianci Xiao. Detection of DS/SS Signal Using Fourth-Order Spectrum[J]. Proceeding of ICSP’93. 1993, 39(11): 2436-2449.
[14]沈振惠.基于四阶统计2-D切片的直扩信号多参数估计[J].信号处理. 2005, 21(3): 304-306.
[15]韩高莉,田红心.基于高阶累积量的低信噪比直扩信号盲检测的实现[J].空间电子技术. 2006, 3(2): 24-28.
[16] Zhenhui Shen, Bin Tang. Multiple Parameters Estimation Simultaneously for DS-SS/BPSK Signal Based on Fourth-Order Cumulate 2-D Slice[A]. IEEE International Conference on CommunicationsCircuits and Systems[C]. 2004, 2: 867-870.
[17] W. A. Gardner, C. M. Spooner. Detection and Source Location of Weak Cyclostationary Signals: Simplifications of the Maximum Likehood Receiver[J]. IEEE Trans. on Communication. 1993, 41(6): 905-916.
[18] W. A. Gardner, C. M. Spooner. Signal Interception: Performance Advantages of Cyclic-Feature Detectors[J]. IEEE Trans. on Communication. 1992, 40(1): 149-159.
[19] W. A. Gardner. Exploitation of Spectral Redundancy in Cyclostationary Signals[J]. IEEE Signal Processing Magazine. 1991, 8(2): 14-36.
[20]史建峰,朱良学,冯辉.基于循环谱包络的BPSK码元速率估计算法研究[J].系统工程与电子技术. 2007, 29(2): 186-189.
[21]杨敏军,邱玲.一种直扩信号的检测方法[J].计算机仿真. 2007, 24(9): 322-324.
[22] A. V. Oppenheim, R. W. Schafer. From Frequency to Quefrency: A History of the Cepstrum[J]. IEEE Signal Processing Magazine. 2004, 21(5): 95-106.
[23] R. Kemerait, D. Childers. Signal Detection and Extraction by Cepstrum Techniques Information Theory[J]. IEEE Trans. on Information Theory. 1972, 18(6): 745–759.
[24]张天骐,周正中.低信噪比长伪码直扩信号伪码周期的估计方法[J].系统工程与电子技术. 2007, 29(1): 12-16.
[25]张天骐,林孝康,周正中等.一种直扩信号基带码周期及序列的盲估计方法[J].电波科学学报. 2005, 20(3): 400-405.
[26]张天骐,周正中,郭宗祥.一种DS/SS信号PN码序列估计的神经网络方法[J].信息技术. 2001, 17(16): 534-537.
[27] G. Burel,C. Bouder. Blind Estimation of the Pseudo-Random Sequence of a Direct Sequence Spread Spectrum Signal[A]. 21st Century Military Communications Conference Proceedings[C]. Los Angeles, CA, USA, 2000, 2: 967-970.
[28] Yingxiang Li, Min Yi, Qin Yang, et al. Low SNR BPSK Signal Chip Rate Estimation Using a Wavelet Based Spectral Correlation Algorithm[J]. IEEE Trans. on Circuits and Systems. 2002, (3): 247-249.
[29] C. M. Spooner, W. A. Gardner. Exploitation of High-Order Cyclostationarity for Weak Signal Detection and Time Delay Estimation[J]. Proceedings of IEEE. 1992, 11(4): 197-201.
[30]朱近康.扩展频谱通信及其应用[M].安徽:中国科学技术大学出版社, 1993. 16-42.
[31]苟彦新.无线电抗干扰通信原理及应用[M].西安:西安电子科技大学出版社, 2005. 37-49.
[32]韦惠民.扩频通信技术及应用[M].西安:西安电子科技大学出版社, 2007. 20-23.
[33]沈丽丽,侯永宏,马兰.扩频通信导论[M].北京:电子工业出版社, 2006. 38-46.
[34] J. G. Proakis, M. Salehi, G. Bauch.现代通信系统[M].刘树棠.第二版.北京:电子工业出版社,2005. 315-319.
[35]樊昌信,曹丽娜.通信原理[M].北京:国防工业出版社, 2007. 380-383 384-389.
[36]王晓燕,方世良,朱志峰.一种基于自相关估计的水声直扩信号检测方法[J].东南大学学报(自然科学版). 2010, 40(2): 248-252.
[37]李锐,何辅云,夏玉宝.相关检测原理及其应用[J].合肥工业大学学报(自然科学版). 2008, 31(4): 573-579.
[38]黄硕翼,石荣,陈锡明.基于码周期的延时相乘法估计扩频QPSK信号的载频[J].电子信息对抗技术. 2007, 6(22): 9-11.
[39]孙铭芳.直扩信号检测和PN码参数估计的研究[D].哈尔滨:哈尔滨工业大学硕士学位论文. 2006: 27-49.
[40]刘基南,袁亮,高梅国.一种直扩信号伪码速率的快速检测方法[J].现代防御技术. 2005, 33(1): 62-64.
[41]聂祥飞.基于LMS算法的自适应噪声抵消器研究[J].三峡学院学报. 2002, 18(2): 112-116.
[42]曹亚丽.自适应滤波器中LMS算法的应用[J].仪器仪表学报. 2005, 26(8): 452-454.
[43]田玉静,左红伟.自适应噪声抵消的应用研究[J].青岛建筑工程学院学报. 2005, 26(1): 77-80.
[44]吴正茂.自适应滤波器及其应用研究[J].南昌水专学报. 2004, 23(2): 36-45.
[45]沈福民.自适应信号处理[M].西安:西安电子科技大学出版社, 2001. 211-222.
[46]朱小芳,陈亚光.噪声对消在信号处理系统中的应用[J].现代电子技术. 2006, 29(24): 86-88.
[47]刘进明,应怀樵. FFT谱连续细化分析的傅里叶变换法[J].振动工程学报. 1995, 8(2): 162-166.
[48]丁康,江利旗.离散频谱的能量重心校正法[J].振动工程学报. 2001, 14(3): 354-358.
[49]谢明,丁康.频谱分析的校正方法[J].振动工程学报. 1994, 7 (2) : 172-179.
[50] Ming Xie, Kang Ding. Corrections for Frequency, Amplitude and Phase in Fast Fourier Transform of a Harmonic Signal[J]. Mechanical System and Signal Process. 1996, 10(2): 211-221.
[51] Jian Meng. Correlation Cumulation for Detection of DS Signal[J]. Electronic Warfare Technology. 2001, 16(2): 1-5.
[52]张邦宁,魏安全,郭道省.通信抗干扰技术[M].北京:机械工业出版社, 2006. 16-17.
[53]侯峥峰,熊辉.直扩信号的参数估计[J].计算机仿真. 2009, 26(10): 352-355.
[54]张贤达,保铮.非平稳信号分析与处理[M].北京:国防工业出版社, 1998. 325-351.
[55] W. A. Gardner. Spectral Correlation of Modulated Signals: Part I-Analog Modulation[J]. IEEE Trans. on Communication. 1987, 35(6): 584-594.
[56]陶雷,武传华.直扩信号检测和参数估计技术研究[J].船舶电子对抗. 2006, 29(1): 35-39.
[57]雷开洪,游庆山.基于循环平稳特性的直扩信号检测与参数估计[J].四川大学学报(自然科学版). 2010, 47(1): 44-47.
[58] W. A. Gardner. The Spectral Correlation Theory of Cyclostationary Time-Series[J]. SignalProcessing. 1986, 11(1): 13-36.
[59] Yan Jin, Hongbing Ji, Junhui Luo. A Cyclic-Cumulant Based Method for DS-SS Signal Detection and Parameter Estimation[J]. Acta Electronica Sinica. 2006, 34(4): 634-637.
[60] W. A. Gardner. Measurement of Spectral Correlation[J]. IEEE Trans. on ASSP. 1986, 34(5): 1111-1123.
[61]戴乐,张海波.直扩信号的循环平稳特性分析[J].系统工程与电子技术. 2004, 26(8): 1038-1052.
[62]黄知涛,周一宇,姜文利.循环平稳信号处理及其应用研究[M].长沙:国防科技大学出版社, 2007. 56-134.
[63]万建伟,王玲.信号处理仿真技术[M].北京:国防科技大学出版社, 2008. 27-55.
[64] Chunlin Huang, Zheng Liu. Chip Width Carrier Frequency and Amplitude Estimation of DS Signal Based on Cyclic Spectrum Amplitude[J]. Acta Electronica Sinica. 2002, 30(9): 1353-1356.
[65]陈四根,杨莘元. QPSK信号谱相关性质研究[J].哈尔滨工程大学学报. 2003, 24(2): 208-211.
[66]赵培聪,高翔,刘重阳.基于改进谱相关算法的信号抗噪性能分析[J].现代雷达. 2010, 32(1): 66-69.
[67]汪赵华,陈昊,郭立.基于频域平滑循环周期图法的直接序列扩频信号的参数估计[J].中国科学技术大学学报. 2010, 40(5): 466-473.