Parameter Estimation of LFM Signal by Direct and Spline Interpolation Based on FrFT

Song, Jun; Liu, Yunfei

doi:10.1007/978-3-642-34528-9_5

Cited by 6 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, through a one‐dimensional peak search of

X ()(, l m_{f}, f_{normalsin})

l \in (}{, 0, 1, \dots, L)

, the NZ index can be estimated as

{\hat{l}}_{normalNZ} = \underset{l}{\arg} (}{, \max (][, X ()(, l m_{f}, f_{normalsin}))) .

According to the modulation parameters corresponding to

{\hat{l}}_{normalNZ}

, the LFM signal of N points can be restructured as

s_{normalLFM} ()(, n) = 0.5 (}{, s_{1} ()(, n) \exp (][, j {\overset{false^}{l}}_{normalNZ} m_{f} \sin ()(, 2 π f_{normalsin} n)) + s_{2} ()(, n)) .

Thus, the LFM/SFM hybrid modulated signal output by the dual‐channel NYFR is converted into a simple chirp signal. Then the fractional Fourier transform (FrFT) method [7] can be used to estimate the LFM parameters of

s_{normalLFM} ()(, n)

. Assuming that the best rotation angle and peak position are estimated to be

{\hat{a}}_{0}

and

{\hat{u}}_{0}

, the chirp rate and centre frequency of the original LFM signal can be estimated as

\overset{false^}{K} = - \cot {\hat{a}}_{0},

\hat{f_{c}} = \overset{...}{u}

…”

Section: Parameter Estimation Algorithmmentioning

confidence: 99%

“…Thus, the LFM/SFM hybrid modulated signal output by the dualchannel NYFR is converted into a simple chirp signal. Then the fractional Fourier transform (FrFT) method [7] can be used to estimate the LFM parameters of s LFM n ( ). Assuming that the best rotation angle and peak position are estimated to beâ 0 andû 0 , the chirp rate and centre frequency of the original LFM signal can be estimated aŝ…”

mentioning

confidence: 99%

See 1 more Smart Citation

Parameter estimation of LFM signal intercepted by improved dual‐channel Nyquist folding receiver

Zhu

Fan

et al. 2018

Electron. lett.

View full text Add to dashboard Cite

A Nyquist folding receiver (NYFR) is a novel ultra-wideband (UWB) receiver architecture, which can realise a wideband receiving with fewer components. Intercepted by the NYFR with a sinusoidal frequency modulation (SFM) local oscillator, a linear frequency modulation (LFM) signal will be converted into a LFM/SFM hybrid modulated signal. To simplify the processing of this kind of complicated signal, the authors propose improved dual-channel NYFR architecture with an efficient parameter estimation algorithm. Compared with the existing parameter estimation methods for the NYFR, the proposed architecture offers better estimation performance, higher signal type adaptability, and simpler operation.

show abstract

“…Therefore, through a one‐dimensional peak search of

X ()(, l m_{f}, f_{normalsin})

l \in (}{, 0, 1, \dots, L)

, the NZ index can be estimated as

{\hat{l}}_{normalNZ} = \underset{l}{\arg} (}{, \max (][, X ()(, l m_{f}, f_{normalsin}))) .

According to the modulation parameters corresponding to

{\hat{l}}_{normalNZ}

, the LFM signal of N points can be restructured as

s_{normalLFM} ()(, n) = 0.5 (}{, s_{1} ()(, n) \exp (][, j {\overset{false^}{l}}_{normalNZ} m_{f} \sin ()(, 2 π f_{normalsin} n)) + s_{2} ()(, n)) .

s_{normalLFM} ()(, n)

. Assuming that the best rotation angle and peak position are estimated to be

{\hat{a}}_{0}

and

{\hat{u}}_{0}

, the chirp rate and centre frequency of the original LFM signal can be estimated as

\overset{false^}{K} = - \cot {\hat{a}}_{0},

\hat{f_{c}} = \overset{...}{u}

…”

Section: Parameter Estimation Algorithmmentioning

confidence: 99%

mentioning

confidence: 99%

Parameter estimation of LFM signal intercepted by improved dual‐channel Nyquist folding receiver

Zhu

Fan

et al. 2018

Electron. lett.

View full text Add to dashboard Cite

show abstract

“…FRFT is a kind of generalized Fourier transform that better focuses LFM signals [21]. The FRFT of the signal s(t) is defined as:…”

Section: Range Imaging Based On Icpf-frftmentioning

confidence: 99%

“…If we want an accurate α k , K is usually large. The transformation and 2D search need to be coordinated [21,24], so the proposed NUFFT-based ICPF-FRFT algorithm does not need to perform any parameter search and has high anti-noise performance. These features enable the implementation of the ISAL imaging algorithm in real time.…”

Section: Range Imaging Based On Icpf-frftmentioning

confidence: 99%

An Inverse Synthetic Aperture Ladar Imaging Algorithm of Maneuvering Target Based on Integral Cubic Phase Function-Fractional Fourier Transform

Wang

et al. 2018

Electronics

View full text Add to dashboard Cite

When imaging maneuvering targets with inverse synthetic aperture ladar (ISAL), dispersion and Doppler frequency time-variation exist in the range and cross-range echo signal, respectively. To solve this problem, an ISAL imaging algorithm based on integral cubic phase function-fractional Fourier transform (ICPF-FRFT) is proposed in this paper. The accurate ISAL echo signal model is established for a space maneuvering target that quickly approximates the uniform acceleration motion. On this basis, the chirp rate of the echo signal is quickly estimated by using the ICPF algorithm, which uses the non-uniform fast Fourier transform (NUFFT) method for fast calculations. At the best rotation angle, the range compression is realized by FRFT and the range dispersion is eliminated. After motion compensation, separation imaging of strong and weak scattering points is realized by using ICPF-FRFT and CLEAN technique and the azimuth defocusing problem is solved. The effectiveness of the proposed method is verified by a simulation experiment of an aircraft scattering point model and real data.

show abstract

“…It should be noted that in Figure 8 , after correctly estimating the NZ index when SNR ≥ 5 dB, the spectrum peak method can obtain a higher estimation accuracy of the chirp rate by means of high precision algorithms such as Fractional Fourier Transform (FrFT) [ 26 ], which is especially suitable for simple LFM signal. However, it is obvious that the spectral peak method needs more computation, requires much higher SNR threshold, otherwise fails under low SNR.…”

Section: Numerical Experimentsmentioning

confidence: 99%

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

Zhu

Chen

2018

Sensors

View full text Add to dashboard Cite

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.

show abstract

Parameter Estimation of LFM Signal by Direct and Spline Interpolation Based on FrFT

Cited by 6 publications

References 5 publications

Parameter estimation of LFM signal intercepted by improved dual‐channel Nyquist folding receiver

Parameter estimation of LFM signal intercepted by improved dual‐channel Nyquist folding receiver

An Inverse Synthetic Aperture Ladar Imaging Algorithm of Maneuvering Target Based on Integral Cubic Phase Function-Fractional Fourier Transform

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

Contact Info

Product

Resources

About