Abstract
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.
Highlights
Ultra-wideband (UWB) receivers [1] need to achieve a high-probability reception of input signals over an extremely wide bandwidth
As the most mature signal of synthetic aperture radar (SAR), linear frequency modulated (LFM) signal has the advantage of good concealment, wide bandwidth, low peak power, and strong anti-interference, which makes it widely used in a variety of radar systems [11]
The autocorrelation method is limited to the signal type and requires a higher signal-to-noise ratio (SNR). In addition to these methods, to avoid the complicated processing of sinusoidal frequency modulation (SFM) signal, the authors of Reference [20] adopted periodic LFM signal as the modulated local oscillator (LOS), and the Nyquist zone (NZ) index was estimated via the chirp rate of the Nyquist Folding Receiver (NYFR) output signal
Summary
Ultra-wideband (UWB) receivers [1] need to achieve a high-probability reception of input signals over an extremely wide bandwidth. The chirp rate and NZ index can be estimated by the slope and the NZ-dependent SFM bandwidth This time-frequency curve algorithm is intuitive but requires a higher signal-to-noise ratio (SNR) as it does not make full use of all the sampled data. The autocorrelation method is limited to the signal type and requires a higher SNR In addition to these methods, to avoid the complicated processing of SFM signal, the authors of Reference [20] adopted periodic LFM signal as the modulated LOS, and the NZ index was estimated via the chirp rate of the NYFR output signal. In Reference [21], an improved dual-channel NYFR architecture was proposed to reduce the difficulty of NYFR output signal processing This scheme introduced an auxiliary channel to the NYFR prototype structure, which doubled the hardware size. This algorithm is suitable for the NYFR with periodic LFM LOS
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