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Sparse GLONASS Signal Acquisition Based on Compressive Sensing and Multiple Measurement Vectors
Joint Authors
Song, Peng
Zhang, Shanshan
He, Guodong
Song, Maozhong
Shu, Xinwen
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-30
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
A sparse global navigation satellite system (GLONASS) signal acquisition method based on compressive sensing and multiple measurement vectors is proposed.
The nonsparse GLONASS signal can be represented sparsely on our proposed dictionary which is designed based on the signal feature.
Then, the GLONASS signal is sensed by a normalized orthogonal random matrix and acquired by the improved multiple measurement vectors acquisition algorithm.
There are 10 cycles of pseudorandom codes in a navigation message, and these 10 pseudorandom codes have the same row sparse structure.
So, the acquisition probability can be raised by row sparse features theoretically.
A large number of simulated GLONASS signal experiments show that the acquisition probability increases with the increase in the measurement vector column dimension.
Finally, the practical availability of the new method is verified by acquisition experiments with the real record GLONASS signal.
The new method can reduce the storage space and energy loss of data transmission.
We hope that the new method can be applied to field receivers that need to record and transmit navigation data for a long time.
American Psychological Association (APA)
He, Guodong& Song, Maozhong& Zhang, Shanshan& Song, Peng& Shu, Xinwen. 2020. Sparse GLONASS Signal Acquisition Based on Compressive Sensing and Multiple Measurement Vectors. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1202394
Modern Language Association (MLA)
He, Guodong…[et al.]. Sparse GLONASS Signal Acquisition Based on Compressive Sensing and Multiple Measurement Vectors. Mathematical Problems in Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1202394
American Medical Association (AMA)
He, Guodong& Song, Maozhong& Zhang, Shanshan& Song, Peng& Shu, Xinwen. Sparse GLONASS Signal Acquisition Based on Compressive Sensing and Multiple Measurement Vectors. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1202394
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202394