Parameter estimation of LFM signals intercepted by a composite local oscillation SNYFR

Li, Tao; Fan, Xiaolei; Zhu, Quing; Chen, Zengping

doi:10.1109/ispacs.2017.8266510

Cited by 7 publications

(10 citation statements)

References 8 publications

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“…The simulation parameters are listed in Table 2. We compared the proposed method with the spectrum peak search method [21], the autocorrelation method [22] and the QMFB method [23] described in Section 1. The probability of a correct NZ determination is shown in Figure 12, and the NRMSE of the chirp rate is illustrated in Figure 13.…”

Section: Simulations and Discussionmentioning

confidence: 99%

“…However, the algorithm is more applicable to narrowband signals, and the performance will deteriorate along with the increase of signal bandwidth. In Reference [22], a new synchronous Nyquist folding receiver (SNYFR) structure based on composite sinusoidal frequency modulation (SFM) LO is proposed, and a parameter estimation algorithm based on instantaneous autocorrelation is presented. Effective detection of multi-component LFM signals and accurate parameters estimation are achieved when the SNR is larger than −8 dB.…”

Section: Introductionmentioning

confidence: 99%

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Nyquist Zone Index and Chirp Rate Estimation of LFM Signal Intercepted by Nyquist Folding Receiver Based on Random Sample Consensus and Fractional Fourier Transform

Liu

Li²,

Fan

et al. 2019

Sensors

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The Nyquist folding receiver (NYFR) can achieve a high-probability interception of an ultra-wideband (UWB) signal with fewer devices, while the output of the NYFR is converted into a hybrid modulated signal of the local oscillator (LO) and the received signal, which requires the matching parameter estimation methods. The linear frequency modulation (LFM) signal is a typical low probability of intercept (LPI) radar signal. In this paper, an estimation method of both the Nyquist Zone (NZ) index and the chirp rate for the LFM signal intercepted by NYFR was proposed. First, according to the time-frequency characteristics of the LFM signal, the accurate NZ and the rough chirp rate was estimated based on least squares (LS) and random sample consensus (RANSAC). Then, the information of the LO was removed from the hybrid modulated signal by the known NZ, and the precise chirp rate was obtained by using the fractional Fourier transform (FrFT). Moreover, a fast search method of FrFT optimal order was presented, which could obviously reduce the computational complexity. The simulation demonstrated that the proposed method could precisely estimate the parameters of the hybrid modulated output signal of the NYFR.

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Section: Simulations and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nyquist Zone Index and Chirp Rate Estimation of LFM Signal Intercepted by Nyquist Folding Receiver Based on Random Sample Consensus and Fractional Fourier Transform

Liu

Li²,

Fan

et al. 2019

Sensors

Self Cite

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“…For the SFM part, only the NZ modulation index

is unknown. Unlike the existing algorithms [ 16 , 18 ] that treat the LFM/SFM hybrid modulated signal as a simple modulation signal and regard the other modulation as a redundant part, we make full use of the its modulation characteristics, and estimate chirp rate directly using the LOS periodic information.…”

Section: Parameter Estimation Based On Svdmentioning

confidence: 99%

“…We compared the proposed CSVR method with the spectrum peak method [ 16 ], the autocorrelation method [ 18 ], and the time-frequency curve method described in Section 1 . Figure 8 illustrates the normalized root mean square error (NRMSE) of chirp rate estimation.…”

Section: Numerical Experimentsmentioning

confidence: 99%

“…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. Based on the periodicity of SFM, the authors of Reference [ 18 ] looked at the use of autocorrelation to process LFM/SFM hybrid modulated signal. The study found that if the interval is exactly the SFM period, a sinusoidal signal with a chirp rate-dependent carrier frequency can be obtained by autocorrelation.…”

Section: Introductionmentioning

confidence: 99%

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

Zhu

Chen

2018

Sensors

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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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Parameter Estimation of LFM Signal Intercepted by Synchronous Nyquist Folding Receiver Based on Instantaneous Autocorrelation

Liu,

Bai,

Peng

2023

2023 5th International Conference on Electronic Engineering and Informatics (EEI)

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Parameter estimation of LFM signals intercepted by a composite local oscillation SNYFR

Cited by 7 publications

References 8 publications

Nyquist Zone Index and Chirp Rate Estimation of LFM Signal Intercepted by Nyquist Folding Receiver Based on Random Sample Consensus and Fractional Fourier Transform

Nyquist Zone Index and Chirp Rate Estimation of LFM Signal Intercepted by Nyquist Folding Receiver Based on Random Sample Consensus and Fractional Fourier Transform

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

Parameter Estimation of LFM Signal Intercepted by Synchronous Nyquist Folding Receiver Based on Instantaneous Autocorrelation

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