Showing papers on "Sampling (signal processing) published in 2018"
TL;DR: This note investigates sampled-data control for chaotic systems by introducing a modified Lyapunov functional that involves the state of a constant signal transmission delay so that the closed-loop system is asymptotically stable.
Abstract: This note investigates sampled-data control for chaotic systems. A memory sampled-data control scheme that involves a constant signal transmission delay is employed for the first time to tackle the stabilization problem for Takagi–Sugeno fuzzy systems. The advantage of the constructed Lyapunov functional lies in the fact that it is neither necessarily positive on sampling intervals nor necessarily continuous at sampling instants. By introducing a modified Lyapunov functional that involves the state of a constant signal transmission delay, a delay-dependent stability criterion is derived so that the closed-loop system is asymptotically stable. The desired sampled-data controller can be achieved by solving a set of linear matrix inequalities. Compared with the existing results, a larger sampling period is obtained by this new approach. A simulation example is presented to illustrate the effectiveness and conservatism reduction of the proposed scheme.
176 citations
TL;DR: Compared with a monostatic radar, improved radar performance and extended radar applications originated from the MIMO architecture can be achieved and low-speed electronics with real-time signal processing capability is feasible.
Abstract: A photonics-based multiple-input-multiple-output (MIMO) radar is proposed and demonstrated based on wavelength-division-multiplexed broadband microwave photonic signal generation and processing. The proposed radar has a large operation bandwidth, which helps to achieve an ultra-high range resolution. Compared with a monostatic radar, improved radar performance and extended radar applications originated from the MIMO architecture can be achieved. In addition, low-speed electronics with real-time signal processing capability is feasible. A photonics-based 2 × 2 MIMO radar is established with a 4-GHz bandwidth in each transmitter and a sampling rate of 100 MSa/s in the receiver. Performance of the photonics-based multi-channel signal generation and processing is evaluated, and an experiment for direction of arrival (DOA) estimation and target positioning is demonstrated, through which the feasibility of the proposed radar system can be verified.
85 citations
TL;DR: This paper presents a method to achieve the high range resolution induced by a large RF bandwidth, but with a much lower baseband bandwidth, consequently requiring a much slower ADC while at the same time delivering a velocity profile for each subcarrier.
Abstract: Recent publications show that the potential of using orthogonal frequency division multiplexing waveforms as radar signals. Since the range resolution is proportional to the RF bandwidth, the major obstacle that obstructs the practical use in automotive and other low-cost radars is the requirement to sample the received signal at sampling rates that span the whole RF signal bandwidth requiring ADCs with sampling rates in the order of GHz. This paper presents a method to achieve the high range resolution induced by a large RF bandwidth, but with a much lower baseband bandwidth, consequently requiring a much slower ADC while at the same time delivering a velocity profile for each subcarrier. In addition, the processing scheme induces a range migration compensation, independent of the number of targets. This is achieved with barely increased computational effort. The scheme is verified with simulations and measurements at 77 GHz.
71 citations
TL;DR: This paper addresses the issue of deceptive jamming against synthetic aperture radar (SAR) by using 1-bit sampling and time-varying threshold (TVT), which considerably simplify the jamming signal generation.
Abstract: This paper addresses the issue of deceptive jamming against synthetic aperture radar (SAR) by using 1-bit sampling and time-varying threshold (TVT). With 1-bit intercepted SAR signal, the multipliers involved in a convolution is replaced by xnor gates, which considerably simplify the jamming signal generation. Moreover, the TVT is used for 1-bit quantization before retransmission to retain the relative amplitude information of the jamming signal. As a result, the proposed deceptive jamming schemes are superior to their conventional counterpart in terms of realization. Effects of harmonics and oversampling are analyzed to evaluate the performance degradations caused by the 1-bit sampling and TVT. Simulation results are provided to confirm the validity of the proposed schemes.
60 citations
TL;DR: An asynchronous successive approximation register analog-to-digital converter (ADC) for wideband multi-standard systems is presented and the configurable asynchronous processing is employed to extend the flexibility of speed and resolution tradeoff.
Abstract: An asynchronous successive approximation register analog-to-digital converter (ADC) for wideband multi-standard systems is presented. The ADC can be configured as an 80-MS/s 10-b, 40-MS/s 11-b, or 20-MS/s 12-b converter. Time-interleaved technique is applied to expand sampling bandwidth exponentially while resolution scales down. The channel mismatches are cancelled by the digital calibration technique. The bulk-biasing technique is used in the sampling switch to reduce the influence of the charge injection caused by the top-plate sampling. In addition, the configurable asynchronous processing is employed to extend the flexibility of speed and resolution tradeoff. Moreover, the two-step digital-to-analog converter (DAC) switching method is proposed to reduce the switching energy of the DAC. Prototyped in 180-nm CMOS process, the ADC achieves the 56.7-/61.2-/64.6-dB signal-to-noise and distortion ratio (SNDR) and 72.3-/74.8-/75.5-dB spurious-free dynamic range (SFDR) at 80-/40-/20-MHz sampling frequency with the power consumption of 2.61/2.05/1.77 mW.
55 citations
TL;DR: An ultra-low-phase-noise injection-locked frequency multiplier (ILFM) for millimeter wave (mm-wave) fifth-generation transceivers is presented and is able to correct the frequency drifts of the quadrature voltage-controlled oscillator of the ILFM in a real-time fashion.
Abstract: An ultra-low-phase-noise injection-locked frequency multiplier (ILFM) for millimeter wave (mm-wave) fifth-generation transceivers is presented. Using an ultra-low-power frequency-tracking loop (FTL), the proposed ILFM is able to correct the frequency drifts of the quadrature voltage-controlled oscillator of the ILFM in a real-time fashion. Since the FTL is monitoring the averages of phase deviations rather than detecting or sampling the instantaneous values, it requires only 600 $\mu \text{W}$ to continue to calibrate the ILFM that generates an mm-wave signal with an output frequency from 27 to 30 GHz. The proposed ILFM was fabricated in a 65-nm CMOS process. The 10-MHz phase noise of the 29.25-GHz output signal was −129.7 dBc/Hz, and its variations across temperatures and supply voltages were less than 2 dB. The integrated phase noise from 1 kHz to 100 MHz and the rms jitter were −39.1 dBc and 86 fs, respectively.
50 citations
TL;DR: This paper identifies a natural duality between this problem and classical compressed sensing, and develops a restricted isometry property (RIP) similar to that in CS that achieves a stable signal recovery under the established RIP.
Abstract: In this paper, we study the recovery of a signal from a set of noisy linear projections (measurements), when such projections are unlabeled, that is, the correspondence between the measurements and the set of projection vectors (i.e., the rows of the measurement matrix) is not known a priori . We consider a special case of unlabeled sensing referred to as unlabeled ordered sampling (UOS) where the ordering of the measurements is preserved. We identify a natural duality between this problem and classical compressed sensing (CS), where we show that the unknown support (location of nonzero elements) of a sparse signal in CS corresponds to the unknown indices of the measurements in UOS. While in CS, it is possible to recover a sparse signal from an underdetermined set of linear equations (less equations than the signal dimension), successful recovery in UOS requires taking more samples than the dimension of the signal. Motivated by this duality, we develop a restricted isometry property (RIP) similar to that in CS. We also design a low-complexity alternating minimization algorithm that achieves a stable signal recovery under the established RIP. We analyze our proposed algorithm for different signal dimensions and number of measurements theoretically and investigate its performance empirically via numerical simulations. The results are reminiscent of a phase transition occurring in CS.
50 citations
TL;DR: The proposed waveform shaping filters can benefit variant applications of UFMC for its flexible performance tradeoffs as well as the improved anti-interference performance.
Abstract: The universal filtered multi-carrier (UFMC) has been taken as a promising candidate for future wireless communication, where a finite impulse response filter is employed to shape the waveform and enhance its resistance to inter-carrier interference. In previous studies, the Dolph–Chebyshev filter had been used due to its low-sidelobe levels, but at the cost of low flexibility to filter the performance control. Hence, this paper puts forward an effective scheme to design an anti-interference filter for UFMC system, where the Nyquist condition (or sampling inter-symbol interference equivalently), the in-band distortion, and the out-of-band emission are taken into consideration. First, this paper models the filter design as a constrained minimax optimization concerning above-mentioned filter performance indexes. Then, the original nonconvex constraints on Nyquist condition are approximately transformed to a linear matrix inequation and two linear inequations. Finally, the optimization problem is solved by semi-definite programming. The numerical examples explicitly demonstrate the flexible performance tradeoff of the proposed method, in which the included filter performance indexes can be effectively controlled. Moreover, the bit-error-rate (BER) tests of the UFMC system confirms the effectiveness of our study, where the designed filters show BER advantages over filters of the previous literature. Therefore, the proposed waveform shaping filters can benefit variant applications of UFMC for its flexible performance tradeoffs as well as the improved anti-interference performance.
46 citations
TL;DR: This paper introduces a novel structure of the current controller, which includes the error-free sampling and the active resistance feedback, and improves the disturbance rejection by extending the range of permissible values of theactive resistance.
Abstract: Digital current controllers have the key impact on the performance of grid-side converters and ac drives. The voltage disturbances are commonly suppressed by enhancing the controller with an inner active resistance feedback. In cases where the switching noise and parasitic oscillations introduce sampling errors, conventional sampling is replaced by the oversampling-based error-free feedback acquisition which derives the average of the measured currents over the past switching period. The time delay introduced into the feedback path creates difficulties in designing the current controller with the active resistance. In this paper, we introduce a novel structure of the current controller, which includes the error-free sampling and the active resistance feedback. Devised structure improves the disturbance rejection by extending the range of permissible values of the active resistance. Controller structure is based on the internal model principles, and it maintains the input step response unaffected. This paper comprises analytical design, the gain setting procedure, computer simulation, and experimental results obtained from an experimental setup with a three-phase inverter, digital controller, and a permanent-magnet synchronous motor.
45 citations
TL;DR: In this article, a new method of active incoherent microwave imaging is presented that uses noise signals and spatial frequency sampling, which is based on interferometric spatialfrequency sampling arrays developed in radio astronomy, to implement the first active imaging method that samples in the spatial frequency domain.
Abstract: A new method of active incoherent microwave imaging is presented that uses noise signals and spatial frequency sampling. Building on interferometric spatial frequency sampling arrays developed in radio astronomy, active incoherent microwave imaging utilizes the transmission of noise signals to implement the first active imaging method that samples in the spatial frequency domain. In comparison to passive microwave imaging systems, active incoherent imaging requires receivers with far less sensitivity, and thus less overall cost. We present the theory behind the imaging technique and show experimental results from a 5.85-GHz system imaging in one and two dimensions. For 1-D images, the transmitter consisted of two noise generators, while the receive array was a synthesized linear array with elements placed in $1\lambda $ increments with the widest spacing of $15\lambda $ . For 2-D images, the transmitter consisted of three noise generators, while the receive array was a synthesized T-array with elements placed in $0.5\lambda $ increments. We demonstrate the reconstruction of 1-D and 2-D scenes consisting of spherical reflecting targets, using only 25 MHz of signal bandwidth and 10 $\mu \text{s}$ of integration time, both of which are an order of magnitude less than passive microwave and millimeter-wave imaging systems.
45 citations
TL;DR: In this paper, a sub-Nyquist MIMO radar (SUMMeR) system was proposed that performs both time and spatial compression. But, the work in this paper is restricted to the case of a single antenna.
Abstract: Multiple-input multiple-output (MIMO) radar exhibits several advantages with respect to the traditional radar array systems in terms of flexibility and performance. However, MIMO radar poses new challenges for both hardware design and digital processing. In particular, achieving high azimuth resolution requires a large number of transmit and receive antennas. In addition, digital processing is performed on samples of the received signal, from each transmitter to each receiver, at its Nyquist rate, which can be prohibitively large when high resolution is needed. Overcoming the rate bottleneck, sub-Nyquist sampling methods have been proposed that break the link between radar signal bandwidth and sampling rate. In this paper, we extend these methods to MIMO configurations and propose a sub-Nyquist MIMO radar (SUMMeR) system that performs both time and spatial compression. We present a range-azimuth-Doppler recovery algorithm from sub-Nyquist samples obtained from a reduced number of transmitters and receivers, that exploits the sparsity of the recovered targets’ parameters. This allows us to achieve reduction in the number of deployed antennas and the number of samples per receiver, without degrading the time and spatial resolutions. Simulations illustrate the detection performance of SUMMeR for different compression levels and shows that both time and spatial resolution are preserved, with respect to classic Nyquist MIMO configurations. We also examine the impact of design parameters, such as antennas’ locations and carrier frequencies, on the detection performance, and provide guidelines for their choice.
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TL;DR: This paper revisits and complete the approximation of the ESS in the specific context of importance sampling (IS) and shows that the multiple assumptions and approximations in the derivation of this approximation makes it difficult to be considered even as a reasonable approximation.
Abstract: The effective sample size (ESS) is widely used in sample-based simulation methods for assessing the quality of a Monte Carlo approximation of a given distribution and of related integrals. In this paper, we revisit and complete the approximation of the ESS in the specific context of importance sampling (IS). The derivation of this approximation, that we will denote as $\widehat{\text{ESS}}$, is only partially available in Kong [1992]. This approximation has been widely used in the last 25 years due to its simplicity as a practical rule of thumb in a wide variety of importance sampling methods. However, we show that the multiple assumptions and approximations in the derivation of $\widehat{\text{ESS}}$, makes it difficult to be considered even as a reasonable approximation of the ESS. We extend the discussion of the ESS in the multiple importance sampling (MIS) setting, and we display numerical examples. This paper does not cover the use of ESS for MCMC algorithms.
TL;DR: The proposed empirical wavelet transform based M-class distribution-level phasor estimation technique is found to be least affected by the presence of dc components, harmonics, and noise and is suitable for synchronization with GPS clocks.
Abstract: Distribution-level signals are often contaminated with harmonics and noise, along with dynamic conditions like frequency deviations. This paper proposes an empirical wavelet transform (EWT) based M-class distribution-level phasor estimation technique under such polluted and dynamic conditions. The capability of the EWT of extracting different frequency components present in the signal makes it suitable for distribution-level phasor estimation. However, the empirical wavelet filters are designed on the basis of the Fourier spectrum of the signal, which, inturn suffers from a spectral leakage problem at off-nominal frequencies. To avoid the errors arising due to spectral leakage, a sample value adjustment based prefiltering technique is employed. The effectiveness of the proposed estimator is demonstrated on various simulated signals, field-data, and real-time signals obtained from the hardware implementation setup. The proposed algorithm is found to be least affected by the presence of dc components, harmonics, and noise. The use of a fixed window size and fixed sampling frequency makes it suitable for synchronization with GPS clocks. The proposed scheme is also able to provide an accurate harmonic phasor estimation.
12 Apr 2018
TL;DR: This work considers the problem of recovering the original signal from the measured modulo-operated signal and derives a sufficient condition on the sampling frequency for ensuring perfect reconstruction of the smooth signal.
Abstract: Self-reset analog-to-digital converters (ADCs) allow for digitization of a signal with a high dynamic range. The reset action is equivalent to a modulo operation performed on the signal. We consider the problem of recovering the original signal from the measured modulo-operated signal. In our formulation, we assume that the underlying signal is Lipschitz continuous. The modulo-operated signal can be expressed as the sum of the original signal and a piecewise-constant signal that captures the transitions. The reconstruction requires estimating the piecewise-constant signal. We rely on local smoothness of the modulo-operated signal and employ wavelets with sufficient vanishing moments to suppress the polynomial component. We employ Daubechies wavelets, which are most compact for a given number of vanishing moments. The wavelet filtering provides a sequence consisting of a sum of scaled and shifted versions of a kernel derived from the wavelet filter. The transition locations are estimated from the sequence using a sparse recovery technique. We derive a sufficient condition on the sampling frequency for ensuring perfect reconstruction of the smooth signal. We validate our reconstruction technique on a signal consisting of sinusoids in both clean and noisy conditions and compare the reconstruction quality with the recently developed repeated finite-difference method.
TL;DR: A 16-channel time-interleaved 10-bit SAR analog-to-digital converter (ADC), employing the proposed delta-sampling auxiliary SAR ADCs and a digital-mixing calibration technique to compensate timing-skew error, achieves a 2.6-GS/s sampling rate.
Abstract: A 16-channel time-interleaved 10-bit SAR analog-to-digital converter (ADC), employing the proposed delta-sampling auxiliary SAR ADCs and a digital-mixing calibration technique to compensate timing-skew error, achieves a 2.6-GS/s sampling rate. The ADC has been fabricated in a 40-nm CMOS technology and achieves a 50.6-dB signal-to-noise-and-distortion ratio at Nyquist rate while dissipating 18.4 mW from a 1.1-V power supply. The digital calibration improves interleaving spurious tones from −33.6 to −63.2 dB in the best case.
TL;DR: Constant linear velocity spiral scanning (CLV-SC) is introduced as a novel beam scanning method to maximize the data acquisition efficiency of ultrahigh speed 4D OCT systems and achieves more uniform transverse sampling compared to raster scanning.
Abstract: Ultrahigh speed optical coherence tomography (OCT) systems with >100 kHz A-scan rates can generate volumes rapidly with minimal motion artifacts and are well suited for 4D imaging (volumes through time) applications such as intra-operative imaging. In such systems, high OCT data acquisition efficiency (defined as the fraction of usable A-scans generated during the total acquisition time) is desired to maximize the volumetric frame rate and sampling pitch. However, current methods for beam scanning using non-resonant and resonant mirror scanners can result in severe scan distortion and transverse oversampling as well as require acquisition dead times, which limit the acquisition efficiency and performance of ultrahigh speed 4D OCT. We introduce constant linear velocity spiral scanning (CLV-SC) as a novel beam scanning method to maximize the data acquisition efficiency of ultrahigh speed 4D OCT systems. We demonstrate that CLV-SC does not require acquisition dead times and achieves more uniform transverse sampling compared to raster scanning. To assess its clinical utility, we implement CLV-SC with a 400 kHz OCT system and image the anterior eye and retina of healthy adults at up to 10 volumes per second with isotropic transverse sampling, allowing B-scans with equal sampling pitch to be extracted from arbitrary locations within a single volume. The feasibility of CLV-SC for intra-operative imaging is also demonstrated using a 800 kHz OCT system to image simulated retinal surgery at 15 volumes per second with isotropic transverse sampling, resulting in high quality volume renders that enable clear visualization of surgical instruments and manipulation of tissue.
18 May 2018
TL;DR: This paper uses 512-point FFT based digital EW receiver, requires minimum pulse width of 750 ns and frequency separation between two simultaneous pulses is 2.63 MHz to extract the key parameters accurately.
Abstract: This paper brings out a unique FPGA based pulse detection and characterization approach for digital wideband ESM receiver targeted for EW applications. The proposed approach uses a high speed ADC and FPGA based architecture for sampling and digital signal processing of the received RADAR signals to extract the key parameters such as Frequency (F), Time of Arrival (TOA), Pulse Width (PW) and Pulse Repetition Interval (PRI). The proposed novel FFT based digital EW receiver is designed and verified by MATLAB and SIMULINK tools and VHDL code for same algorithm is generated using HDL Coder for FPGA implementation. The current paper uses 512-point FFT based digital EW receiver, requires minimum pulse width of 750 ns and frequency separation between two simultaneous pulses is 2.63 MHz to extract the key parameters accurately. The simulated and measured results for Pulse detection algorithm are presented.
TL;DR: A single-pixel digital holography system with phase-encoded illumination using a digital micromirror device (DMD) as a spatial light modulator (SLM) is presented, far exceeding the stringent frame-rate of liquid crystal SLMs.
Abstract: A single-pixel digital holography system with phase-encoded illumination using a digital micromirror device (DMD) as a spatial light modulator (SLM) is presented. The enhanced switching rate of DMDs, far exceeding the stringent frame-rate of liquid crystal SLMs, allows recording and reconstruction of complex amplitude distributions in just a few seconds. A single amplitude binary modulation device is used for concurrently displaying the phase-encoded sampling patterns, compensating the distortion of the wavefront, and applying phase-shifting, by means of computer generated holograms. Our detection system consists of a simple photodiode that sequentially records the irradiance fluctuations corresponding to the interference between object and reference beams. The system recovers phase and amplitude information even when a diffuser is placed in front of the photodiode.
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TL;DR: This chapter introduces temporal sub-Nyquist processing for estimating the target locations using less bandwidth than conventional systems, and paves the way to cognitive radars which share their transmit spectrum with other communication services, thereby providing a robust solution for coexistence in spectrally crowded environments.
Abstract: In the past few years, new approaches to radar signal processing have been introduced which allow the radar to perform signal detection and parameter estimation from much fewer measurements than that required by Nyquist sampling. These systems - referred to as sub-Nyquist radars - model the received signal as having finite rate of innovation and employ the Xampling framework to obtain low-rate samples of the signal. Sub-Nyquist radars exploit the fact that the target scene is sparse facilitating the use of compressed sensing (CS) methods in signal recovery. In this chapter, we review several pulse-Doppler radar systems based on these principles. Contrary to other CS-based designs, our formulations directly address the reduced-rate analog sampling in space and time, avoid a prohibitive dictionary size, and are robust to noise and clutter. We begin by introducing temporal sub-Nyquist processing for estimating the target locations using less bandwidth than conventional systems. This paves the way to cognitive radars which share their transmit spectrum with other communication services, thereby providing a robust solution for coexistence in spectrally crowded environments. Next, without impairing Doppler resolution, we reduce the dwell time by transmitting interleaved radar pulses in a scarce manner within a coherent processing interval or "slow time". Then, we consider multiple-input-multiple-output array radars and demonstrate spatial sub-Nyquist processing which allows the use of few antenna elements without degradation in angular resolution. Finally, we demonstrate application of sub-Nyquist and cognitive radars to imaging systems such as synthetic aperture radar. For each setting, we present a state-of-the-art hardware prototype designed to demonstrate the real-time feasibility of sub-Nyquist radars.
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TL;DR: A general bound on expected discounted regret is established and the application of satisficing Thompson sampling to linear and infinite-armed bandits is studied, demonstrating arbitrarily large benefits over Thompson sampling.
Abstract: Much of the recent literature on bandit learning focuses on algorithms that aim to converge on an optimal action. One shortcoming is that this orientation does not account for time sensitivity, which can play a crucial role when learning an optimal action requires much more information than near-optimal ones. Indeed, popular approaches such as upper-confidence-bound methods and Thompson sampling can fare poorly in such situations. We consider instead learning a satisficing action, which is near-optimal while requiring less information, and propose satisficing Thompson sampling, an algorithm that serves this purpose. We establish a general bound on expected discounted regret and study the application of satisficing Thompson sampling to linear and infinite-armed bandits, demonstrating arbitrarily large benefits over Thompson sampling. We also discuss the relation between the notion of satisficing and the theory of rate distortion, which offers guidance on the selection of satisficing actions.
TL;DR: The results show that channel bandwidth utilization can be reduced by increasing the sampling time while keeping the system stable, and the event-triggered controller implemented can further reduce the required bandwidth.
Abstract: Efficient estimation of wideband spectrum is of great importance for applications such as cognitive radio. Recently, sub-Nyquist sampling schemes based on compressed sensing have been proposed to greatly reduce the sampling rate. However, the important issue of quantization has not been fully addressed, particularly, for high resolution spectrum and parameter estimation. In this paper, we aim to recover spectrally sparse signals and the corresponding parameters, such as frequency and amplitudes, from heavy quantizations of their noisy complex-valued random linear measurements, e.g., only the quadrant information. We first characterize the Cramer-Rao bound under Gaussian noise, which highlights the trade-off between sample complexity and bit depth under different signal-to-noise ratios for a fixed budget of bits. Next, we propose a new algorithm based on atomic norm soft thresholding for signal recovery, which is equivalent to proximal mapping of properly designed surrogate signals with respect to the atomic norm that motivates spectral sparsity. The proposed algorithm can be applied to both the single measurement vector case, as well as the multiple measurement vector case. It is shown that under the Gaussian measurement model, the spectral signals can be reconstructed accurately with high probability, as soon as the number of quantized measurements exceeds the order of K log n, where K is the level of spectral sparsity and n is the signal dimension. Finally, numerical simulations are provided to validate the proposed approaches.
TL;DR: A blind SNSS algorithm, referred to as the residual energy ratio based detector (RERD), is proposed, which bypasses the need for the above-mentioned prior knowledge and performs spectrum sensing in a more autonomous way.
Abstract: Rooted in the compressed sensing theory, sub-Nyquist spectrum sensing (SNSS) has been considered as a promising approach to dealing with difficulties and limitations of conventional wideband spectrum sensing in cognitive radio (CR) networks. Most existing SNSS methods require some prior knowledge of the monitored frequency bands, such as the spectrum occupancy/sparsity level and/or the noise power, to determine a termination condition used by an underlying iterative signal recovery process. However, such prior knowledge may be difficult to acquire in practical CR scenarios. To address this problem, we propose a blind SNSS algorithm, referred to as the residual energy ratio based detector (RERD), which bypasses the need for the above-mentioned prior knowledge and performs spectrum sensing in a more autonomous way. The RERD algorithm, which is based on the modulated wideband converter (MWC) sub-Nyquist sampling framework, employs energy ratios of adjacent channels of the MWC as test statistics. We derive closed-form expressions of the decision threshold and the false alarm probability following the Neyman–Pearson criterion. Simulation results show that, without requiring the aforementioned prior knowledge, the RERD algorithm can accurately determine the support of a multiband signal contaminated by background noise in a wide range of signal-to-noise ratio. Moreover, the RERD algorithm is shown to be robust to a range of sparsity orders and different number of sampling channels.
TL;DR: In this article, the authors consider a combined sampling and source coding problem in which an analog stationary Gaussian signal is reconstructed from its encoded samples, under the additional constraint that the samples are quantized or compressed in a lossy manner under a limited bitrate budget.
Abstract: Representing a continuous-time signal by a set of samples is a classical problem in signal processing. We study this problem under the additional constraint that the samples are quantized or compressed in a lossy manner under a limited bitrate budget. To this end, we consider a combined sampling and source coding problem in which an analog stationary Gaussian signal is reconstructed from its encoded samples. These samples are obtained by a set of bounded linear functionals of the continuous-time path, with a limitation on the average number of samples per unit time given in this setting. We provide a full characterization of the minimal distortion in terms of the sampling frequency, the bitrate, and the signal’s spectrum. Assuming that the signal’s energy is not uniformly distributed over its spectral support, we show that for each compression bitrate there exists a critical sampling frequency smaller than the Nyquist rate, such that the distortion in signal reconstruction when sampling at this frequency is minimal. Our results can be seen as an extension of the classical sampling theorem for bandlimited random processes in the sense that they describe the minimal amount of excess distortion in the reconstruction due to lossy compression of the samples and provide the minimal sampling frequency required in order to achieve this distortion. Finally, we compare the fundamental limits in the combined source coding and sampling problem to the performance of pulse code modulation, where each sample is quantized by a scalar quantizer using a fixed number of bits.
TL;DR: In this article, a frequency adaptive discrete Fourier transform (DFT) based repetitive control (RC) scheme for dc/ac converters is proposed to eliminate waveform distortion by generating infinite magnitude on the interested harmonics.
Abstract: This paper proposes a frequency adaptive discrete Fourier transform (DFT) based repetitive control (RC) scheme for dc/ac converters. By generating infinite magnitude on the interested harmonics, the DFT-based RC offers a selective harmonic scheme to eliminate waveform distortion. The traditional DFT-based selective harmonic RC, however, is sensitive to frequency fluctuation since even very small frequency fluctuation leads to a severe magnitude decrease. To address the problem, the virtual variable sampling (VVS) method, which creates an adjustable virtual delay unit to closely approximate a variable sampling delay, is proposed to enable the DFT-based selective harmonic RC to be frequency adaptive. Moreover, a selective odd-order harmonic DFT filter is developed to deal with the dominant odd order harmonic. Because it halves the number of sampling delays in the DFT filter, the system transient response gets nearly a 50% improvement. A comprehensive series of experiments of the proposed VVS DFT-based selective odd-order harmonic RC controlled programmable ac power source under frequency variations are presented to verify the effectiveness of the proposed method.
TL;DR: In this paper, a distributed signal sampling method was proposed and implemented to provide impedance for a battery management system (BMS), where the battery cell perturbing current and its response voltage for impedance calculation were sampled separately to be compatible with BMS.
Abstract: Battery impedance based state estimation methods receive extensive attention due to its close relation to internal dynamic processes and the mechanism of a battery. In order to provide impedance for a battery management system (BMS), a practical on-board impedance measuring method based on distributed signal sampling is proposed and implemented. Battery cell perturbing current and its response voltage for impedance calculation are sampled separately to be compatible with BMS. A digital dual-channel orthogonal lock-in amplifier is used to calculate the impedance. With the signal synchronization, the battery impedance is obtained and compensated. And the relative impedance can also be obtained without knowing the current. For verification, an impedance measuring system made up of electronic units sampling and processing signals and a DC-AC converter generating AC perturbing current is designed. A type of 8 Ah LiFePO4 battery is chosen and the valuable frequency range for state estimations is determined with a series of experiments. The battery cells are connected in series and the impedance is measured with the prototype. It is shown that the measurement error of the impedance modulus at 0.1 Hz–500 Hz at 5 °C–35 °C is less than 4.5% and the impedance phase error is less than 3% at <10 Hz at room temperature. In addition, the relative impedance can also be tracked well with the designed system.
TL;DR: This paper proposes a novel CS-based A2I architecture called non-uniform wavelet sampling, which extracts a carefully-selected subset of wavelet coefficients directly in the RF domain, which mitigates the main issues of existing A 2I converter architectures.
Abstract: Feature extraction, such as spectral occupancy, interferer energy and type, or direction-of-arrival, from wideband radio-frequency (RF) signals finds use in a growing number of applications as it enhances RF transceivers with cognitive abilities and enables parameter tuning of traditional RF chains. In power and cost limited applications, e.g., for sensor nodes in the Internet of Things, wideband RF feature extraction with conventional, Nyquist-rate analog-to-digital converters is infeasible. However, the structure of many RF features (such as signal sparsity) enables the use of compressive sensing (CS) techniques that acquire such signals at sub-Nyquist rates; while such CS-based analog-to-information (A2I) converters have the potential to enable low-cost and energy-efficient wideband RF sensing, they suffer from a variety of real-world limitations, such as noise folding, low sensitivity, aliasing, and limited flexibility. This paper proposes a novel CS-based A2I architecture called non-uniform wavelet sampling. Our solution extracts a carefully-selected subset of wavelet coefficients directly in the RF domain, which mitigates the main issues of existing A2I converter architectures. For multi-band RF signals, we propose a specialized variant called non-uniform wavelet bandpass sampling (NUWBS), which further improves sensitivity and reduces hardware complexity by leveraging the multi-band signal structure. We use simulations to demonstrate that NUWBS approaches the theoretical performance limits of $\ell_{1}$ -norm-based sparse signal recovery. We investigate hardware-design aspects and show ASIC measurement results for the wavelet generation stage, which highlight the efficacy of NUWBS for a broad range of RF feature extraction tasks in cost- and power-limited applications.
TL;DR: This work extends the recently proposed frequency-domain beamforming (FDBF) framework to plane-wave imaging and demonstrates the use of FDBF for shear-wave elastography by generating velocity maps from the beamformed data processed at sub-Nyquist rates.
Abstract: Ultrafast imaging based on coherent plane-wave compounding is one of the most important recent developments in medical ultrasound. It significantly improves the image quality and allows for much faster image acquisition. This technique, however, requires large computational load motivating methods for sampling and processing rate reduction. In this work, we extend the recently proposed frequency-domain beamforming (FDBF) framework to plane-wave imaging. Beamforming in frequency yields the same image quality while using fewer samples. It achieves at least fourfold sampling and processing rate reduction by avoiding oversampling required by standard processing. To further reduce the rate, we exploit the structure of the beamformed signal and use compressed sensing methods to recover the beamformed signal from its partial frequency data obtained at a sub-Nyquist rate. Our approach obtains tenfold rate reduction compared with standard time-domain processing. We verify performance in terms of spatial resolution and contrast based on the scans of a tissue mimicking the phantom obtained by a commercial Aixplorer system. In addition, in vivo carotid and thyroid scans processed using standard beamforming and FDBF are presented for qualitative evaluation and visual comparison. Finally, we demonstrate the use of FDBF for shear-wave elastography by generating velocity maps from the beamformed data processed at sub-Nyquist rates.
TL;DR: S sampling formula for signals that are bandlimited to a disc of radius in the linear canonical transform (LCT) domain is derived and obtained in the fractional Fourier transform domain.
Abstract: We derive sampling formula for signals that are bandlimited to a disc of radius $R$ in the linear canonical transform (LCT) domain. By bandlimitedness in a disc $D$ in the LCT domain, we mean that the LCT $F(\omega)$ of a signal $f(t)$ vanishes outside the disc $D.$ We first express the signal in polar coordinates and then obtain the sampling formula. The samples of the angle $\theta$ are taken at $2N+1$ uniformly distributed points on the unit circle while the samples of the radial distance $r$ are taken at the zeros of the Bessel function. As a special case, we obtain sampling formula for signals that are bandlimited to a disc in the fractional Fourier transform domain.
TSMC1
TL;DR: A dynamic-dark-signal-region detection technique is used to mitigate differential nonlinearity (DNL) errors due to ramp slope mismatch and the figure of merit of this paper is 2.02 nVrms/Hz.
Abstract: This paper presents a sub-electron temporal readout noise, 8.3 Mpixel and 1.1- $\mu \text{m}$ pixel pitch 3-D-stacked CMOS image sensor (CIS). A conditional correlated multiple sampling (CMS) technique is introduced to selectively reduce the dark pixel noise by using a full-range ramp and a small-range ramp. In this way, a sub-electron temporal readout noise CIS is achieved without degrading the frame rate dramatically, compared to the conventional CMS method. A column-parallel single slope ADC with dark pixel detection function is proposed as well. A dynamic-dark-signal-region detection technique is used to mitigate differential nonlinearity (DNL) errors due to ramp slope mismatch. The implemented prototype in 45-nm CIS/65-nm CMOS occupies an area of 35.89 mm2. This paper achieves a 0.66erms− with 5-time sampling at a frame rate of 7.2 frames/s, which corresponds to a sample-rate frequency of 36.1 kHz for the column ADC. The DNL (11 b) is improved from +0.98 LSB/−0.94 LSB to +0.29 LSB/−0.39 LSB by using dynamic dark-signal region technique. The figure of merit of this paper is 2.02 nVrms/Hz.