Some Aspects of Sidelobe Reduction in Pulse Compression Radars Using NLFM Signal Processing

Vizitiu, Iulian C.

doi:10.2528/pierc14010605

Cited by 22 publications

(13 citation statements)

References 25 publications

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“…One of the most important issues in the SAR system design is the software-defined SAR transceiver design [6][7][8][9][10]. In a typical SAR receiver that employs frequency chirping for pulse compression, the received SAR echo is processed using a matched filter (MF) to get its time-domain form at the MF output as a pulse that has a main lobe and multiple sidelobes.…”

Section: Introductionmentioning

confidence: 99%

“…Over the last decade, a lot of research works have been concerned with issue of SAR pulse compression. For example, the work of [9] proposes a radar pulse compression scheme through an approach that is related to the design of efficient non-linear frequency modulation (NLFM) waveforms namely, a temporal predistortioning method of LFM signals by some nonlinear frequency laws. This method produces a compressed radar pulse with SLL of about−40dB .…”

Section: Introductionmentioning

confidence: 99%

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Radar Pulse Compression with Optimized Weighting Window for SAR Receivers

Hussein

Helmy

Mohra

2022

Wireless Pers Commun

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This paper proposes a novel design of a software-defined matched filter (MF) for digital receivers of synthetic aperture radar (SAR). The block diagram of the proposed receiver is described in detail. The purpose of this filter is to produce a SAR pulse with higher compression ratio (CR) and lower side lobe level (SLL) than that produced by the conventional MF. The proposed design is based on the idea of time windowing of the SAR pulse to construct the transfer function of the receiver filter. The shape of the proposed time-domain window is optimized to achieve the filter design goals including the minimization of the SLL and the realization of the target value of the CR. The transmitted SAR pulse is, first, subjected to linear frequency modulation and then subjected to the optimized window. The width (time duration) of the proposed window is divided into equal time intervals. The proposed time-domain window is constructed as a sequential continuous piecewise linear segments. The instantaneous value of the time-domain window at the start of each time interval is optimized so as to achieve the optimization goals. The width of the time-domain window is shown to be proportional to the width of the compressed pulse after optimization. The number of the time intervals into which the time duration of the window is divided is shown to have a significant effect on the optimization results. The particle swarm optimization (PSO) technique is then applied to get the window shape that minimizes the SLL for a specific predetermined value of the pulse CR. It is shown that the iterations of the PSO are fastly convergent and that the applied algorithm is computationally efficient. Also, it is shown that the desired value of the pulse CR is achieved with accuracy of 100%. Moreover, the achieved SLLs are about − $$65\,\mathrm{dB}$$ 65 dB , $$- 90\,\mathrm{dB}$$ - 90 dB , $$- 114\,\mathrm{dB}$$ - 114 dB , and $$- 133\,\mathrm{dB}$$ - 133 dB for pulse CR of 5, 3, 2, and 1.5, respectively. Finally, for practical implementation of the introduced SAR pulse processing technique, the proposed optimized window is placed as a building block in a software-defined receiver of the SAR system.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Radar Pulse Compression with Optimized Weighting Window for SAR Receivers

Hussein

Helmy

Mohra

2022

Wireless Pers Commun

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“…Other methods use a waveform that has good autocorrelation function (ACF) properties with low autocorrelation sidelobe levels and reduced impulse response width (IRW). Such a waveform can be obtained by using binary codes [ 13 ], polyphase codes [ 14 ], Costas codes [ 15 ], and nonlinear frequency modulation (FM) [ 16 , 17 , 18 ]. Another method uses powerful convex optimization to generate a waveform that has a strong ACF and a PSLR of around

dB; see [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of an Enhanced Matched Filter for Sidelobe Reduction of Pulsed Linear Frequency Modulation Radar

Azouz

Abosekeen

Nassar

et al. 2021

Sensors

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Pulse compression techniques are commonly used in linear frequency modulated (LFM) waveforms to improve the signal-to-noise ratios (SNRs) and range resolutions of pulsed radars, whose detection capabilities are affected by the sidelobes. In this study, a sidelobe reduction filter (SRF) was designed and implemented using software defined radio (SDR). An enhanced matched filter (EMF) that combines a matched filter (MF) and an SRF is proposed and was implemented. In contrast to the current commonly used approaches, the mathematical model of the SRF frequency response is extracted without depending on any iteration methods or adaptive techniques, which results in increased efficiency and computational speed for the developed model. The performance of the proposed EMF was verified through the measurement of four metrics, including the peak sidelobe ratio (PSLR), the impulse response width (IRW), the mainlobe loss ratio (MLR), and the receiver operational characteristics (ROCs) at different SNRs. The ambiguity function was then used to characterize the Doppler effect on the designed EMF. In addition, the detection of single and multiple targets using the proposed EMF was performed, and the results showed that it overcame the masking problem due to its effective reduction of the sidelobes. Hence, the practical application of the EMF matches the performance analysis. Moreover, when implementing the EMF proposed in this paper, it outperformed the common MF, especially when detecting targets moving at low speeds and having small radar cross-sections (RCS), even under severe masking conditions.

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“…There have been a number of methods to generate frequency modulated signals, including the three-segment chirp function [15], arctan and Zak-transform [16] techniques. The optical fiber sensing community can benefit from further research on new schemes for easily adaptable use of NLFM waveforms in probes for spatially resolved optical reflectometry, including tools to compare the achievable range resolution qualities of different optical pulse compression techniques.…”

mentioning

confidence: 99%

Adaptable Pulse Compression in ϕ-OTDR With Direct Digital Synthesis of Probe Waveforms and Rigorously Defined Nonlinear Chirping

et al. 2022

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Recent research in Phase-Sensitive Optical Time Doman Reflectometry (ϕ-OTDR) has been focused, among others, on performing spatially resolved measurements with various methods including the use of frequency modulated probes. However, conventional schemes either rely on phase-coded sequences, involve inflexible generation of the probe frequency modulation or mostly employ simple linear frequency modulated (LFM) pulses which suffer from elevated sidelobes introducing degradation in range resolution. In this contribution, we propose and experimentally demonstrate a novel ϕ-OTDR scheme which employs a readily adaptable Direct Digital Synthesis (DDS) of pulses with custom frequency modulation formats and demonstrate advanced optical pulse compression with a nonlinear frequency modulated (NLFM) waveform containing a complex, rigorously defined modulation law optimized for bandwidth-limited synthesis and sidelobe suppression. The proposed method offers high fidelity chirped waveforms, and when employed in resolving a 50-cm event at ∼1.13 km using a 1.2-µs probe pulse, matched filtering with the DDS-generated NLFM waveform results in a significant reduction in range ambiguity owing to autocorrelation sidelobe suppression of ∼20 dB with no averages and windowing functions, for an improvement of ∼16 dB compared to conventional linear chirping. Experimental results also show that the contribution of autocorrelation sidelobes to the power in the compressed backscattering responses around localized events is suppressed by up to ∼18 dB when advanced pulse compression with an optical NLFM pulse is employed.

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Some Aspects of Sidelobe Reduction in Pulse Compression Radars Using NLFM Signal Processing

Cited by 22 publications

References 25 publications

Radar Pulse Compression with Optimized Weighting Window for SAR Receivers

Radar Pulse Compression with Optimized Weighting Window for SAR Receivers

Design and Implementation of an Enhanced Matched Filter for Sidelobe Reduction of Pulsed Linear Frequency Modulation Radar

Adaptable Pulse Compression in ϕ-OTDR With Direct Digital Synthesis of Probe Waveforms and Rigorously Defined Nonlinear Chirping

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