Nonlinear FM waveform design to reduction of sidelobe level in autocorrelation function

Ghavamirad, Roohollah; Babashah, Hossein; Sebt, Mohammad Ali

doi:10.1109/iraniancee.2017.7985379

Cited by 21 publications

(12 citation statements)

References 13 publications

(18 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method was applied in [15]. In Section 4, the results are compared against the proposed method.…”

Section: Nlfm Signal Design With Stationary Phase Methodsmentioning

confidence: 99%

“…To start the algorithm, we set the θ (0) equal to the phase value obtained from the stationary phase method for the Fourier transform of the NLFM signal [16]. Thus, by repeating the algorithm, we obtain the desired NLFM signal, and because the amplitude of NLFM signal is constant, so we can multiply the amplitude of the obtained signal in the constant coefficient A.…”

Section: Optimal Phasementioning

confidence: 99%

See 1 more Smart Citation

Sidelobe level reduction in ACF of NLFM waveform

Ghavamirad

Sebt

2019

IET Radar, Sonar & Navigation

Self Cite

View full text Add to dashboard Cite

In this paper, an iterative method is proposed for nonlinear frequency modulation (NLFM) waveform design based on a constrained optimization problem using Lagrangian method. To date, NLFM waveform design methods have been performed based on the stationary phase concept which we have already used it in a previous work. The proposed method has been implemented for six windows of Raised-Cosine, Taylor, Chebyshev, Gaussian, Poisson, and Kaiser. The results reveals that the peak sidelobe level of autocorrelation function reduces about an average of 5 dB in our proposed method compared with the stationary phase method, and an optimum peak sidelobe level is achieved. The minimum error of the proposed method decreases in each iteration which is demonstrated using mathematical relations and simulation. The trend decrement of minimum error guarantees convergence of the proposed method.

show abstract

“…This method was applied in [15]. In Section 4, the results are compared against the proposed method.…”

Section: Nlfm Signal Design With Stationary Phase Methodsmentioning

confidence: 99%

Section: Optimal Phasementioning

confidence: 99%

Sidelobe level reduction in ACF of NLFM waveform

Ghavamirad

Sebt

2019

IET Radar, Sonar & Navigation

Self Cite

View full text Add to dashboard Cite

show abstract

“…In (8), W K×N is the discrete Fourier transform (DFT) matrix. We now take a partial derivative of (5) with respect to the vector x.…”

mentioning

confidence: 99%

“…Noteworthy, to start the algorithm from an appropriate point, the obtained phase from the stationary phase concept [8] is taken as the initial phase (u (0) ), then, by the following the algorithm, we try to get close to the optimal condition. The proposed algorithm is efficient as long as the minimum error value is reducing in each iteration.…”

mentioning

confidence: 99%

Phase improvement algorithm for NLFM waveform design to reduction of sidelobe level in autocorrelation function

2018

View full text Add to dashboard Cite

In this paper, a phase improvement algorithm has been developed to design the nonlinear frequency modulated (NLFM) signal for the four windows of Raised-Cosine, Taylor, Chebyshev, and Kaiser. We have already designed NLFM signal by stationary phase method. The simulation results for the peak sidelobe level of the autocorrelation function in the phase improvement algorithm reveal a significant average decrement of about 5 dB with respect to stationary phase method. Moreover, to evaluate the efficiency of the phase improvement algorithm, minimum error value for each iteration is calculated.Introduction: Goal of pulse compression is to increase bandwidth and improve range resolution [1]. There are several methods for pulse compression. For example, coding methods such as Barker, Huffman, Zadoff-Chu, etc. are utilized in pulse compression [2], but due to the phase discontinuity and the signal amplitude variability (such as the Huffman codes), they result in loss increment in the receiver (due to mismatching) [3]. The linear frequency modulation (LFM) method has received much attention since its phase continuity and the constant amplitude of the signal, but it suffers from relatively high sidelobes in autocorrelation function (ACF) [3].The NLFM method has been proposed to reduce the sidelobes level in ACF. In NLFM method, the signal amplitude is constant and the frequency variations with respect to time is nonlinear. Stationary phase concept (SPC) is commonly used in NLFM method. SPC explains that power spectral density (PSD) in a frequency is relatively high if the related frequency variation is low with regard to time [3]. Using this method leads to noticeable sidelobes level decrement in ACF. Additionally, it causes the main lobe width to increases slightly but negligible.The phase improvement algorithm (PIA) is proposed here to be used after the stationary phase method. This method is designed based on the phase matching techniques. To start the algorithm, an appropriate value for the phase is used which comes from stationary phase method. The algorithm is repeated several times in order to get closer to the optimal phase value where sidelobes level are significantly reduced compared to the stationary phase method.The remainder of the letter is organized as follows: Second section outlines the proposed phase improvement algorithm. In the third section, the simulation results of the proposed algorithm are discussed and a comparison between SPC and the proposed method is made. Finally, the fourth section concludes the paper.

show abstract

“…To provide an example that quantifies the PSLR improvement when NLFM pulses are used, Fig. 2.7, presented in the work of Ghavamirad [2], compares the detection of LFM with NLFM pulses. In this particular case, a PSLR of less than 15 dB is found for LFM pulses, whereas a PSLR of ∼ 35 dB is obtained when NLFM pulses are used.…”

Section: Nlfmmentioning

confidence: 99%

Time-Resolved Optical Spectroscopy for Laser Chirp Characterization and Self-Heterodyne Generation of LFM and NLFM Microwave Pulses

BRAGA¹

View full text Add to dashboard Cite

show abstract

Nonlinear FM waveform design to reduction of sidelobe level in autocorrelation function

Cited by 21 publications

References 13 publications

Sidelobe level reduction in ACF of NLFM waveform

Sidelobe level reduction in ACF of NLFM waveform

Phase improvement algorithm for NLFM waveform design to reduction of sidelobe level in autocorrelation function

Time-Resolved Optical Spectroscopy for Laser Chirp Characterization and Self-Heterodyne Generation of LFM and NLFM Microwave Pulses

Contact Info

Product

Resources

About