Parameter Estimation of SAR Signal Based on SVD for the Nyquist Folding Receiver
Open accessAbstract
The Nyquist Folding Receiver (NYFR) is a novel ultra-wideband (UWB) receiver structure that can realize wideband signal monitoring with fewer components. The NYFR induces a Nyquist zone (NZ)-dependent sinusoidal frequency modulation (SFM) by a modulated local oscillator (LOS), and the intercepted linear frequency modulated (LFM) synthetic aperture radar (SAR) signal will be converted into an LFM/SFM hybrid modulated signal. In this paper, a parameter estimation algorithm is proposed for the complicated NYFR output signal. According to the NYFR prior information, a chirp singular value ratio (CSVR) spectrum method based on singular value decomposition (SVD) is proposed to estimate the chirp rate directly before estimating the NZ index. Then, a fast search algorithm based on golden section method for the CSVR spectrum is analyzed, which can obviously reduce the computational complexity. The simulation shows that the presented algorithm can accurately estimate the parameters of the LFM/SFM hybrid modulated output signal by the NYFR.
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Cites
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“In Reference [16], a spectrum peak method was proposed for the NYFR, that is, to construct a multi-channel structure and estimate the NZ index by comparing the spectrum peak value of each channel.”
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Flagged first, then by citations
Research works printed but not linked: 1
- [25]Holmes M.P. Gray A.G. Isbell C.L. QUIC-SVD, Fast SVD using cosine trees Proceedings of the Conference on Neural Information Processing Systems Vancouver, BC, Canada 12–13 December 2008 673 680
Cited by
Sorted by citations
Liu, X., Li, T., Fan, X., & Chen, Z. (2019) · Sensors · doi:10.3390/s19061477 · Cited by 8 · see citing works
“Compared with the Gegenbauer system [5,6] and many other compress sensing (CS) based architectures [10,11] that require full signal reconstruction, the NYFR basically preserves the signal structure, and the information reconstruction can be relatively simple with conventional signal analysis methods [12].”
Self-citation
- Authors
- Li, T., Zhu, Q., & Chen, Z.
- Affiliations
- National University of Defense Technology (CN)
- Corresponding author
- Zhu, Qian
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2018-06-01
- Volume
- 18
- Issue
- 6
- Pages
- 1768
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC6021933
- OpenAlex
- W2805956748
- Cited by
- 8
- References
- 23
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 2 · 2021: 1 · 2019: 1
- FWCI
- 0.41
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Advanced SAR Imaging Techniques
- Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
- Physical Sciences › Engineering › Computational Mechanics › Sparse and Compressive Sensing Techniques
- Keywords
- parameter estimation, chirp rate estimation, singular value decomposition, sinusoidal frequency modulation, linear frequency modulation, ultra-wideband receiver, golden section search, computational complexity reduction
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