Parameter Estimation of SAR Signal Based on SVD for the Nyquist Folding Receiver

• Main Authors: Tao Li, Qian Zhu, Zengping Chen
• Format: Article
• Language: English
• Published: MDPI AG 2018-06-01
• Series: Sensors
• Subjects: Nyquist Folding Receiver; LFM signal; parameter estimation; singular value decomposition; golden section method
• Online Access: http://www.mdpi.com/1424-8220/18/6/1768

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.