基于临界采样多相滤波器组的宽带信号信道化

doi:10.13229/j.cnki.jdxbgxb.20220274

吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (8): 2388-2394.doi: 10.13229/j.cnki.jdxbgxb.20220274

基于临界采样多相滤波器组的宽带信号信道化

张海龙^1,^2,^3,⁴(),张萌^1,²,张亚州^1,²,王杰^1,⁴,冶鑫晨^1,⁴,王万琼¹,李嘉¹,杜旭^1,²,张婷^1,²

^1.中国科学院新疆天文台，乌鲁木齐 830011
^2.中国科学院大学天文与空间科学学院，北京 100049
^3.中国科学院射电天文重点实验室，南京 210008
^4.国家天文科学数据中心，北京 100101

收稿日期:2022-04-01 出版日期:2023-08-01 发布日期:2023-08-21
作者简介:张海龙（1980-），男，研究员级高级工程师，博士.研究方向：数据密集型研究.E-mail：zhanghailong@xao.ac.cn
基金资助:
国家重点研发计划项目(2021YFC2203502);国家自然科学基金项目(12173077);新疆维吾尔自治区天山创新团队计划项目(2022D14020);“天山英才培养”计划项目(2022TSYCCX0095);中国科学院科研仪器设备研制项目(PTYQ2022YZZD01);国家天文科学数据中心;中国科学院天文台站设备更新及重大仪器设备运行专项经费;新疆维吾尔自治区自然科学基金项目(2022D01A360)

Channelization of wideband signal based on critical sampling polyphase filter banks

Hai-long ZHANG^1,^2,^3,⁴(),Meng ZHANG^1,²,Ya-zhou ZHANG^1,²,Jie WANG^1,⁴,Xin-chen YE^1,⁴,Wan-qiong WANG¹,Jia LI¹,Xu DU^1,²,Ting ZHANG^1,²

^1.Xinjiang Astronomical Observatory，Chinese Academy of Sciences，Urumqi 830011，China
^2.School of Astronomy and Space Science，University of Chinese Academy of Sciences，Beijing 100049，China
^3.Key Laboratory of Radio Astronomy，Chinese Academy of Sciences，Nanjing 210008，China
^4.National Astronomical Data Center，Beijing 100101，China

Received:2022-04-01 Online:2023-08-01 Published:2023-08-21

摘要/Abstract

摘要：

针对通信及射电天文领域宽带信号子带划分过程中遇到的频谱泄漏及子带混叠等问题，仿真分析了Hanning窗、Hamming窗和Kaiser窗等不同窗函数对有限冲激响应（FIR）数字滤波器性能的影响。基于Hamming窗FIR数字滤波器设计实现了临界采样多相滤波器组，研究了临界采样多相滤波器组的频谱特性。利用天文观测基带数据实现了宽带信号的子带划分，分析了临界采样多相滤波器组与传统FIR数字滤波器组的滤波性能特征。利用临界采样多相滤波器组实现了宽带基带数据的多通道输出，并对子信道内频谱信息进行了分析和修正，得到了与原始信号相对应的子通道频谱。

关键词: 天文信息技术, 多相滤波器组, 有限冲激响应滤波器, 数字滤波器组, 信道划分

Abstract:

In view of spectral leakage and aliasing in the wideband signal channelization in the field of communication and radio astronomy. The effects of different window functions such as Hanning windows， Hamming windows and Kaiser windows on the performance of the finite impulse response （FIR） digital filter were simulated and analyzed. Based on the Hamming window FIR digital filter designed and implemented the critical sampling polyphase filter banks， and the spectral characteristics of the critical sampling polyphase filter banks were studied. The sub-bands division of wideband signals were realized by using the astronomical observation baseband data， and the filtering performance characteristics of the critical sampling polyphase filter banks and FIR digital filter banks were analyzed. Employed the critical sampling polyphase filter banks realized the multichannel output of wideband baseband data， and the frequency spectrum of the sub-channels was analyzed and corrected， which correspond to the original signal.

Key words: astroinformatics, polyphase filter banks, fir filter, digital filter banks, channelization

中图分类号:

TP301.6

张海龙,张萌,张亚州,王杰,冶鑫晨,王万琼,李嘉,杜旭,张婷. 基于临界采样多相滤波器组的宽带信号信道化[J]. 吉林大学学报(工学版), 2023, 53(8): 2388-2394.

Hai-long ZHANG,Meng ZHANG,Ya-zhou ZHANG,Jie WANG,Xin-chen YE,Wan-qiong WANG,Jia LI,Xu DU,Ting ZHANG. Channelization of wideband signal based on critical sampling polyphase filter banks[J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(8): 2388-2394.

图/表 11

图1

图2

图3

图4

图5

图6

图7

图8

图9

图10

图11

参考文献 16

1	Morrison I S, Bunton J D, Straten W V, et al. Performance of oversampled polyphase filterbank inversion via fourier transform[J]. Journal of Astronomical Instrumentation, 2020, 9(1): S225117172050004X.
2	Tuthill J, Hampson G, Bunton J D, et al. Compensating for oversampling effects in polyphase channelizers: A radio astronomy application[C]∥IEEE Dsp Workshop, Salt Lake City, 2015: 255-260.
3	邵鹏, 吴志健, 周炫余. 基于反向学习的粒子群算法对线性相位低通FIR滤波器的优化[J]. 吉林大学学报: 工学版, 2015, 45(3): 907-912.
	Shao Peng, Wu Zhi-jian, Zhou Xuan-yu. Particle swarm optimization algorithm based on opposite learning for linear phase low-pass FIR filter optimization[J]. Journal of Jilin University(Engineering and Technology Edition), 2015, 45(3): 907-912.
4	Ghandour A, Mansour A, AlAsadi H, et al. Design and implementation of polyphase fast Fourier transform channelizer[C]∥International Wireless Communications and Mobile Computing, Xi'an, 2020: 613-618.
5	Proakis J G. Digital Signal Processing: Principles Algorithms and Applications[M]. Zamin Pallavaram: Pearson Education India, 2001.
6	Smith J P, Bailey J I, Tuthill J, et al. A high-throughput oversampled polyphase filter bank using vivado HLS and PYNQ on a RFSoC[J]. IEEE Open Journal of Circuits and Systems, 2021, 2: 241-252.
7	陈涛, 刘勇, 刘颜琼, 等. 基于余弦调制滤波器组的动态信道化方法[J]. 吉林大学学报: 工学版, 2013, 43(6): 1690-1695.
	Chen Tao, Liu Yong, Liu Yan-qiong, et al. Dynamic channelization using cosine modulated filter banks[J]. Journal of Jilin University(Engineering and Technology Edition), 2013, 43(6): 1690-1695.
8	赵欣, 金乘进, 朱岩, 等. 基于多相滤波的多通道数字终端设计[J]. 天文研究与技术, 2015, 12(4): 495-502.
	Zhao Xin, Jin Cheng-jin, Zhu Yan, et al. A design of a multi-channel digital backend based on a polyphase filter bank[J]. Astronomical Research and Technology, 2015, 12(4): 495-502.
9	Price D C. Spectrometers and Polyphase Filterbanks in Radio Astronomy[M]∥The WSPC Handbook of Astronomical Instrumentation: Volume 1: Radio Astronomical Instrumentation. 2021.
10	Hobbs G, Manchester R N, Dunning A, et al. An ultra-wide bandwidth (704 to 4032 MHz) receiver for the Parkes radio telescope[J]. Publications of the Astronomical Society of Australia, 2020, 37: 00656.
11	Sabath F, Mokole E L, Samaddar S N. Definition and classification of ultra-wideband signals and devices[J]. URSI Radio Ence Bulletin, 2005, 313: 12-26.
12	Taylor J D. Ultrawideband Radar: Applications and Design[M]. Boca Raton: CRC Press, 2012.
13	Federal Communications Commission. Ultra-Wideband Transmission Systems[EB/OL]. (2021-08-16).
14	Lundheim L. On Shannon and "Shannon's formula"[J]. Telektronikk, 2002, 98(1): 20-29.
15	Bulatek A. Design and modal analysis of an ultra-wideband receiver for green bank observatory[J]. Macalester Journal of Physics and Astronomy, 2020, 8(1): 3.
16	Kumar V, Bangar S, Kumar S N, et al. Design of effective window function for FIR filters[C]∥International Conference on Advances in Engineering & Technology Research, Unnao, Kanpur, 2014: 1-5.

相关文章 15

[1]	陈小波,陈玲. 定位噪声统计特性未知的变分贝叶斯协同目标跟踪[J]. 吉林大学学报(工学版), 2023, 53(4): 1030-1039.
[2]	胡丹,孟新. 基于时变网格的对地观测卫星搜索海上船舶方法[J]. 吉林大学学报(工学版), 2022, 52(8): 1896-1903.
[3]	刘富,刘璐,侯涛,刘云. 基于优化MSR的夜间道路图像增强方法[J]. 吉林大学学报(工学版), 2021, 51(1): 323-330.
[4]	魏晓辉,孙冰怡,崔佳旭. 基于图神经网络的兴趣活动推荐算法[J]. 吉林大学学报(工学版), 2021, 51(1): 278-284.
[5]	徐谦,李颖,王刚. 基于深度学习的行人和车辆检测[J]. 吉林大学学报(工学版), 2019, 49(5): 1661-1667.
[6]	王占中, 卢月, 刘晓峰, 赵利英. 基于改进和声搜索算法的越库车辆排序[J]. 吉林大学学报(工学版), 2018, 48(3): 688-693.
[7]	王艺源, 欧阳丹彤, 张立明. 结合部件动态变化度求解最小碰集的GRASP算法[J]. 吉林大学学报(工学版), 2017, 47(3): 930-936.
[8]	黄岚, 李玉, 王贵参, 王岩. 基于点距离和密度峰值聚类的社区发现方法[J]. 吉林大学学报(工学版), 2016, 46(6): 2042-2051.
[9]	董立岩, 隋鹏, 孙鹏, 李永丽. 基于半监督学习的朴素贝叶斯分类新算法[J]. 吉林大学学报(工学版), 2016, 46(3): 884-889.
[10]	赵伟, 曲慧雁. 基于云计算Map-Reduce模型的快速碰撞检测算法[J]. 吉林大学学报(工学版), 2016, 46(2): 578-584.
[11]	张贵军, 郝小虎, 周晓根, 秦传庆. 动态步长蛋白质构象空间搜索方法[J]. 吉林大学学报(工学版), 2016, 46(2): 585-594.
[12]	李军, 倪宏, 王玲芳, 陈君. 流媒体系统中基于请求迁移的任务调度算法[J]. 吉林大学学报(工学版), 2015, 45(3): 938-945.
[13]	董宁，王宇平. 求解约束优化问题的引导多目标差分进化算法[J]. 吉林大学学报(工学版), 2015, 45(2): 569-575.
[14]	王刚, 张禹瑄, 李颖, 陈慧灵, 胡玮通, 秦磊. 一种微阵列数据降维新方法[J]. 吉林大学学报(工学版), 2014, 44(5): 1429-1434.
[15]	刘淑芬, 孟冬雪, 王晓燕. 的DBSCAN算法[J]. 吉林大学学报(工学版), 2014, 44(4): 1135-1139.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

基于临界采样多相滤波器组的宽带信号信道化

Channelization of wideband signal based on critical sampling polyphase filter banks

RICH HTML

PDF (PC)

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 16

相关文章 15

Metrics

本文评价

推荐阅读 0