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

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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.

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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

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

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.