Compressive radar sensing via one-bit sampling with time-varying thresholds

Li, Jian; Naghsh, Mohammad Mahdi; Zahabi, Sayed Jalal; Modarres-Hashemi, Mahmoud

doi:10.1109/acssc.2016.7869554

Cited by 44 publications

(22 citation statements)

References 18 publications

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“…The SNR losses indicate that the dynamic range is reduced for one-bit radar due to the application of one-bit quantization. A possible solution is to adopt the time varying threshold in one-bit radar system by accommodating large dynamic range of the received signal [7,18,35].…”

Section: ) Fas Caused By High-order Harmonicsmentioning

confidence: 99%

One-Bit LFMCW Radar: Spectrum Analysis and Target Detection

Jin

Zhu

et al. 2020

IEEE Trans. Aerosp. Electron. Syst.

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One-bit radar involving direct one-bit sampling is a promising technology for many civilian applications due to its low-cost and low-power consumptions. In this paper, problems encountered by one-bit LFMCW radar are studied and a two-stage target detection approach termed as DR-GAMP is proposed.Firstly, the spectrum of one-bit signal in a scenario of multiple targets is analyzed. It is indicated that high-order harmonics may result in false alarms (FAs) and cannot be neglected. Secondly, DR-GAMP is used to suppress the high order harmonics. Specifically, linear preprocessing and predetection are proposed to perform dimension reduction (DR), and then, generalized approximate message passing (GAMP) is utilized to suppress high-order harmonics. Finally, numerical simulations are conducted to evaluate the performance of one-bit LFMCW radar with typical parameters. It is shown that compared to conventional radar with linear processing approach, one-bit LFMCW radar has 0.5 dB performance gain when the input signal-to-noise ratios (SNRs) of targets are low. Moreover, it has 1.6 dB performance loss in a scenario with an additional high SNR target.

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Section: ) Fas Caused By High-order Harmonicsmentioning

confidence: 99%

One-Bit LFMCW Radar: Spectrum Analysis and Target Detection

Jin

Zhu

et al. 2020

IEEE Trans. Aerosp. Electron. Syst.

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“…Based on (12) and (14), the fundamental component of the one-bit complex signal of the first target can be represented by…”

Section: Harmonic Analysis Of One-bit Signalmentioning

confidence: 99%

“…Because the advantages of one-bit quantization, the applications of the one-bit ADC has recently attracted considerable research interest for 5G wireless communications [3]- [8], wireless sensor network (WSN) [9]- [11], radar [12]- [17] and so on. However, as for one-bit radar, how to carry out signal processing and target reconstruction based…”

Section: Introductionmentioning

confidence: 99%

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One-Bit LFM Pulse Radar: Harmonic Analysis and Target Reconstruction

et al. 2019

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One-bit radar, adopting one-bit analog-to-digital converters to perform signal sampling and quantization, is a promising technology for low-cost and resource-limited applications. In this paper, effects of one-bit quantization on the linear signal processing for the one-bit linear frequency modulated pulse radar are studied and a target reconstruction approach is proposed. Firstly, characteristics of 3-order harmonics of the one-bit signal are analyzed. It is indicated that when conventional linear signal processing methods are carried out, 3-order harmonics may not only raise the detection background but also result in false alarms. Secondly, a two-stage approach jointly performing the linear and nonlinear signal processing is proposed to suppress harmonics and recover true targets. Specifically, in the first stage, the linear signal processing is carried out to suppress unmatched harmonics and dimension reduction. In the second stage, based on a dimension-reduced signal observation model, generalized approximate message passing is utilized to suppress matched harmonics and recover true targets. The effectiveness of the proposed approach is demonstrated by numerical results.

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“…To cope with unit‐norm constraint, sophisticated optimisation methods [15], alternative constraints [18] or the functions that quantify the consistency between the measured 1‐bit quantised data and the reconstructed signal [5, 6] need to be used. However, some of the recent studies have proposed random time‐varying thresholds [21–26], where 1‐bit measurements are captured by comparing signals to time‐varying threshold levels. Thus, the quantisation to 1‐bit with properly chosen thresholds enables to recover the amplitude of the signal more accurately.…”

Section: Introductionmentioning

confidence: 99%