收藏切换
Multiple linear frequency modulation signal extraction in highly noisy environment using discrete prolate spheroidal sequence
收藏切换
PDF
HOU Changman, YU Biao, CHEN Yuanhang
Science & Technology Review | 2019, 37(19) : 74 - 79
Less
收藏切换
Science & Technology Review | 2019, 37(19): 74-79
Papers
Multiple linear frequency modulation signal extraction in highly noisy environment using discrete prolate spheroidal sequence
Full
HOU Changman, YU Biao, CHEN Yuanhang
Affiliations
Published: 2019-10-13 doi: 10.3981/j.issn.1000-7857.2019.19.010
Outline
收藏切换
With the continuous development of countermeasure and anti-countermeasure technology as well as the increasing application of low intercept signals, traditional signal extraction methods are no longer to satisfy user's needs for extraction of low intercept signal waveforms. In this paper, based on the discrete prolate spheroidal sequence (DPSS), the time-window function is used to analyze multiple linear frequency modulation signals. A method employing horizontal threshold decision probability to capture signal is proposed, and extraction of signal waveform is completed by adaptive binarization and improved Hough transform (HT). Simulation shows that the proposed method is better than the short-time Fourier transform algorithm in terms of noise control and can accurately extract the waveform at low SNR.
discrete prolate spheroidal sequence  /  Hough transform  /  multiple linear frequency modulation  /  short-time Fourier transform
侯长满, 余彪, 陈远航. 基于DPSS的高噪声条件下混合LFM波形提取方法设计. 科技导报, 2019 , 37 (19) : 74 -79 . DOI: 10.3981/j.issn.1000-7857.2019.19.010
HOU Changman, YU Biao, CHEN Yuanhang. Multiple linear frequency modulation signal extraction in highly noisy environment using discrete prolate spheroidal sequence[J]. Science & Technology Review, 2019 , 37 (19) : 74 -79 . DOI: 10.3981/j.issn.1000-7857.2019.19.010
Year 2019 volume 37 Issue 19
PDF
441
95
Cite this Article
BibTeX
Article Info
doi: 10.3981/j.issn.1000-7857.2019.19.010
  • Receive Date:2019-03-01
  • Online Date:2019-10-19
  • Published:2019-10-13
Article Data
Affiliations
History
  • Received:2019-03-01
  • Revised:2019-07-22
Affiliations
References
Share
https://castjournals.cast.org.cn/joweb/kjdb/EN/10.3981/j.issn.1000-7857.2019.19.010
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT