基于小波变换与压缩感知的脉冲星TOA估计

由四海; 王宏力; 冯磊; 何贻洋; 许强

doi:10.3788/IRLA202049.0226001

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于小波变换与压缩感知的脉冲星TOA估计

由四海, 王宏力, 冯磊, 何贻洋, 许强

文章导航 > 红外与激光工程 > 2020 > 49(2): 0226001-0226001

由四海, 王宏力, 冯磊, 何贻洋, 许强. 基于小波变换与压缩感知的脉冲星TOA估计[J]. 红外与激光工程, 2020, 49(2): 0226001-0226001. doi: 10.3788/IRLA202049.0226001

引用本文:

由四海, 王宏力, 冯磊, 何贻洋, 许强. 基于小波变换与压缩感知的脉冲星TOA估计[J]. 红外与激光工程, 2020, 49(2): 0226001-0226001. doi: 10.3788/IRLA202049.0226001

You Sihai, Wang Hongli, Feng Lei, He Yiyang, Xu Qiang. Pulsar TOA estimation based on wavelet transform and compressed sensing[J]. Infrared and Laser Engineering, 2020, 49(2): 0226001-0226001. doi: 10.3788/IRLA202049.0226001

Citation:

You Sihai, Wang Hongli, Feng Lei, He Yiyang, Xu Qiang. Pulsar TOA estimation based on wavelet transform and compressed sensing[J]. Infrared and Laser Engineering, 2020, 49(2): 0226001-0226001. doi: 10.3788/IRLA202049.0226001

基于小波变换与压缩感知的脉冲星TOA估计

doi: 10.3788/IRLA202049.0226001

1. 火箭军工程大学导弹工程学院, 陕西西安 710025;
2. 青州高新技术研究所, 山东青州 262500

基金项目:

国家自然科学基金青年科学基金（61503391）；中国博士后基金（2017M613372）

详细信息

作者简介:
由四海(1984-),男,博士生,主要从事脉冲星导航方面的研究。Email:yousihai12345@163.com

中图分类号: V448.131;V448.232;TN911.72

Pulsar TOA estimation based on wavelet transform and compressed sensing

1. College of Missile Engineering, Rocket Force Engineering University, Xi'an 710025, China;
2. Qingzhou High-tech Research Institute, Qingzhou 262500, China

摘要: 脉冲星导航是一种新型的自主式导航。为提高其精度与实时性，提出一种小波变换与压缩感知结合的脉冲星到达时间（Time of Arrival，TOA）估计的方法。该方法对标准脉冲轮廓使用小波变换构造多级冗余字典，通过信号恢复算法估计出实际脉冲星的TOA。该方法的算法复杂度低于传统的TOA估计方法，并且随着脉冲星信号周期内bin数量的增加，算法的实时性越好。该方法改变了传统的先去噪再估计TOA的思路，其可以嵌入到信号去噪的过程中，还可以和小波去噪的阈值处理并行计算。仿真结果显示文中方法耗时分别为两种传统TOA估计方法的0.87%和21.35%，并且随着数据时长的缩短，文中方法的TOA估计精度的相对优势越发明显。该方法不但可以提高TOA估计精度，而且降低了对数据时长的依赖。
- 导航 /
- TOA估计 /
- 小波变换 /
- 压缩感知 /
- 多级冗余字典
Abstract: Pulsar navigation is a new type of autonomous navigation. In order to improve its accuracy and real-time, a method of pulsar time of arrival(TOA) estimation combining wavelet transform and compressed sensing was proposed. This method constructed a multi-level redundancy dictionary using wavelet transform for the standard algorithm complexity of this method was lower than the traditional TOA estimation method, and the real-time performance of the algorithm was better as the number of bins in the pulsar signal period increases. This method changed the traditional idea of first denoising and then estimating TOA, which can be embedded in the process of signal denoising, and can be calculated in parallel with the threshold processing of wavelet denoising. The simulation results show that the time consumption of this method is 0.87% and 21.35% of that of the two traditional TOA estimation methods, respectively. And with the shortening of the data duration, the relative advantage of the TOA estimation accuracy of this method is more obvious. This method can not only improve the accuracy of TOA estimation, but also reduce the dependence on the duration of data.
- navigation /
- TOA estimation /
- wavelet transform /
- compressed sensing /
- multi-level redundancy dictionary

[1]	Xu Q, Wang H, Feng L, et al. A novel X-ray pulsar integrated navigation method for ballistic aircraft[J]. Optik, 2018, 175(6):28-38.
[2]	Sheikh S I, Pines D J, Ray P S, et al. Spacecraft navigation using X-Ray pulsars[J]. J Guid Control Dyn, 2006, 29(1):49-63.
[3]	Chu Yonghui, Li Maodeng, Huang Xiangyu, et al. Autonomous navigation method based on landmark and pulsar measurement[J]. Infrared and Laser Engineering, 2015, 44(S):12-15. (in Chinese)
[4]	Xu Qiang, Wang Hongli, Feng Lei, et al. An improved augmented X-ray pulsar navigation algorithm based on the norm of pulsar direction error[J]. Adv Sp Res, 2018, 62(11):3187-3198.
[5]	Su Zhe, Xu Luping, Gan Wei. Pulsar profile construction algorithm based on compressed sensing[J]. Sci Sin(Phy, Mech and Astron), 2011, 41(5):681-684.
[6]	Li Shengliang, Liu Kun, Xiao Longlong. Fleet algorithm for X-ray pulsar profile construction and TOA solution based on compressed sensing[J]. Optik, 2014, 125(7):1875-1879.
[7]	Shen Lirong, Li Xiaoping, Sun Haifeng, et al. A robust compressed sensing based method for X-ray Pulsar Profile construction[J]. Optik, 2016, 127:4379-4385.
[8]	Liu Jing, Jian Chengfang, Liu Gang. Observation range-based compressive sensing and its application in TOA estimation with low-flux pulsars[J]. Optik, 2017, 148:256-267.
[9]	Kang Zhiwei, Wu Chunyan, Liu Jin, et al. Pulsar time delay estimation method based on two-level compressed sensing[J]. Acta Phys Sin, 2018, 67(9):1-8. (in Chinese)
[10]	You S, Wang H, He Y, et al. Pulsar profile construction based on double-redundant-dictionary and same-scale L1-norm compressed sensing[J]. Optik, 2018, 164:617-623.
[11]	Liu Xiuping, Wei Yuan, Han Lili, et al. X-ray pulsar signal de-noising for impulse noise using wavelet packet[J]. Aerosp Sci Technol, 2017, 64:147-153.
[12]	Donoho D L. Compressed sensing[J]. IEEE Trans Inf Theory, 2006, 52(4):1289-1306.

[1]	孙强, 戴鹭楠, 应恺宁, 倪辰荫. 二分搜索和压缩感知在激光超声内部缺陷快速检测技术的应用 . 红外与激光工程, 2022, 51(2): 20210810-1-20210810-13. doi: 10.3788/IRLA20210810
[2]	张赛文, 邓亚琦, 王冲, 冷潇泠, 张光富, 文兵, 邓杨保, 谭伟石, 田野, 李稳国. 基于多测量矢量压缩感知的超分辨荧光显微成像研究 . 红外与激光工程, 2021, 50(11): 20210484-1-20210484-8. doi: 10.3788/IRLA20210484
[3]	尹红飞, 郭亮, 周煜, 孙剑锋, 曾晓东, 唐禹, 邢孟道. 基于改进SVA和压缩感知的SAL旁瓣抑制算法 . 红外与激光工程, 2018, 47(12): 1230005-1230005(8). doi: 10.3788/IRLA201847.1230005
[4]	王忠良, 冯文田, 粘永健. 结合光谱解混与压缩感知的高光谱图像有损压缩 . 红外与激光工程, 2018, 47(S1): 189-196. doi: 10.3788/IRLA201847.S126003
[5]	杜颖财, 宋路, 万秋华, 杨守旺. 小波变换实现的光电编码器精确实时测速 . 红外与激光工程, 2017, 46(5): 517005-0517005(6). doi: 10.3788/IRLA201746.0517005
[6]	申艳, 解颐, 娄淑琴, 王鑫, 赵彤彤. 基于Contourlet变换和压缩感知的实际光子晶体光纤光 . 红外与激光工程, 2017, 46(3): 321001-0321001(7). doi: 10.3788/IRLA201746.0321001
[7]	叶松, 甘永莹, 熊伟, 张文涛, 汪杰君, 王新强. 采用小波变换的空间外差光谱仪基线校正 . 红外与激光工程, 2016, 45(11): 1117009-1117009(5). doi: 10.3788/IRLA201645.1117009
[8]	杨新锋, 张金娜, 滕书华, 崔宇. 利用压缩感知实现随机变频雷达散射中心估计 . 红外与激光工程, 2016, 45(5): 526004-0526004(6). doi: 10.3788/IRLA201645.0526004
[9]	纪强, 石文轩, 田茂, 常帅. 基于KL与小波联合变换的多光谱图像压缩 . 红外与激光工程, 2016, 45(2): 228004-0228004(7). doi: 10.3788/IRLA201645.0228004
[10]	韩申生, 龚文林, 陈明亮, 李恩荣, 薄遵望, 李望, 张惠, 高昕, 邓陈进, 梅笑东, 王成龙. 基于稀疏和冗余表象的鬼成像雷达研究进展 . 红外与激光工程, 2015, 44(9): 2547-2555.
[11]	赵爱罡, 王宏力, 杨小冈, 陆敬辉, 何星. 融合几何特征的压缩感知SIFT描述子 . 红外与激光工程, 2015, 44(3): 1085-1091.
[12]	崔珊珊, 李琦. 基于小波变换的太赫兹数字全息再现像去噪研究 . 红外与激光工程, 2015, 44(6): 1836-1840.
[13]	顾有林, 叶应流, 曹光华, 胡以华, 朱峰. EMD和小波变换在低可探测目标检测中的应用 . 红外与激光工程, 2015, 44(11): 3494-3499.
[14]	尹继豪, 孙建颖. 基于压缩感知理论的波段重构方法 . 红外与激光工程, 2014, 43(4): 1260-1264.
[15]	伊力哈木·亚尔买买提, 谢丽蓉, 孔军. 基于PCA 变换与小波变换的遥感图像融合方法 . 红外与激光工程, 2014, 43(7): 2335-2340.
[16]	关丛荣, 金伟其, 王吉晖. 小波变换在显微热图像位移估计中的应用 . 红外与激光工程, 2014, 43(8): 2780-2785.
[17]	谭歆, 冯晓毅, 王保平. 稀疏带状测量矩阵在压缩感知ISAR成像中的应用 . 红外与激光工程, 2013, 42(11): 3137-3143.
[18]	朱丰, 张群, 冯有前, 罗迎, 李开明, 梁必帅. 逆合成孔径激光雷达鸟类目标压缩感知识别方法 . 红外与激光工程, 2013, 42(1): 256-261.
[19]	陈春利, 谢红梅, 彭进业, 王志成, 王保平. 压缩感知机动目标ISAR成像新方法 . 红外与激光工程, 2013, 42(8): 2269-2274.
[20]	. 基于小波变换直方图规定的非均匀性校正算法 . 红外与激光工程, 2013, 42(12): 3481-3485.

点击查看大图

计量

文章访问数: 850
HTML全文浏览量: 174
PDF下载量: 28
被引次数: 0

基于小波变换与压缩感知的脉冲星TOA估计

doi: 10.3788/IRLA202049.0226001

1. 火箭军工程大学导弹工程学院, 陕西西安 710025;

2. 青州高新技术研究所, 山东青州 262500

作者简介:
由四海(1984-),男,博士生,主要从事脉冲星导航方面的研究。Email:yousihai12345@163.com

收稿日期: 2019-10-03
修回日期: 2019-11-20
刊出日期: 2020-03-02

基金项目:

国家自然科学基金青年科学基金（61503391）；中国博士后基金（2017M613372）

中图分类号: V448.131;V448.232;TN911.72

关键词:

摘要: 脉冲星导航是一种新型的自主式导航。为提高其精度与实时性，提出一种小波变换与压缩感知结合的脉冲星到达时间（Time of Arrival，TOA）估计的方法。该方法对标准脉冲轮廓使用小波变换构造多级冗余字典，通过信号恢复算法估计出实际脉冲星的TOA。该方法的算法复杂度低于传统的TOA估计方法，并且随着脉冲星信号周期内bin数量的增加，算法的实时性越好。该方法改变了传统的先去噪再估计TOA的思路，其可以嵌入到信号去噪的过程中，还可以和小波去噪的阈值处理并行计算。仿真结果显示文中方法耗时分别为两种传统TOA估计方法的0.87%和21.35%，并且随着数据时长的缩短，文中方法的TOA估计精度的相对优势越发明显。该方法不但可以提高TOA估计精度，而且降低了对数据时长的依赖。

English Abstract

Pulsar TOA estimation based on wavelet transform and compressed sensing

1. College of Missile Engineering, Rocket Force Engineering University, Xi'an 710025, China;

2. Qingzhou High-tech Research Institute, Qingzhou 262500, China

Received Date: 2019-10-03
Rev Recd Date: 2019-11-20
Publish Date: 2020-03-02

Keywords:

Abstract: Pulsar navigation is a new type of autonomous navigation. In order to improve its accuracy and real-time, a method of pulsar time of arrival(TOA) estimation combining wavelet transform and compressed sensing was proposed. This method constructed a multi-level redundancy dictionary using wavelet transform for the standard algorithm complexity of this method was lower than the traditional TOA estimation method, and the real-time performance of the algorithm was better as the number of bins in the pulsar signal period increases. This method changed the traditional idea of first denoising and then estimating TOA, which can be embedded in the process of signal denoising, and can be calculated in parallel with the threshold processing of wavelet denoising. The simulation results show that the time consumption of this method is 0.87% and 21.35% of that of the two traditional TOA estimation methods, respectively. And with the shortening of the data duration, the relative advantage of the TOA estimation accuracy of this method is more obvious. This method can not only improve the accuracy of TOA estimation, but also reduce the dependence on the duration of data.