Digital Signal Processing Research Articles

Real-Time Method and Implementation of Head-Wave Extraction for Ultrasonic Imaging While Drilling

Extracting head waves and subsequently uploading their results from the downhole to the surface system in real time could improve the real-time guidance of ultrasonic imaging logging while drilling (UILWD) for drilling operations. To realize the downhole real-time extraction of head waves in this logging, three aspects were explored in this study. First, an improved energy ratio head-wave arrival extraction algorithm based on the weighting coefficients and characteristic functions, along with an amplitude detection method relying on peak-to-peak values, was proposed. Second, an echo reception pre-processing analog circuit and a digital signal processing circuit based on FPGA were designed. A pipeline algorithm was developed in FPGA to extract the arrival time and amplitude of the head wave. Finally, software simulations, laboratory tests, and field experiments related to this method were conducted. Our results showed that the real-time head-wave extraction method demonstrated a strong anti-noise ability in real time. The maximum relative error of the arrival time was less than 5%. The relative error of the amplitude was acceptable, and 90% of this value was within 5%. Through the measurement, the time of processing a single-channel waveform by a downhole algorithm was less than 15 ms, thus meeting the requirements for the real-time processing of downholes.

Analysing and predicting learning behaviours in computer science: A case study of the blended teaching mode in Digital Signal Processing course

Blended learning is the latest and inevitable trend in the development of education. Although blended learning research is on the rise, fewer studies examine the learning behaviour of college students in blended learning environments. This study aimed to investigate the learning behaviours of students in the field of computer science and examine these behaviours using data mining algorithms, taking the teaching practice of the Digital Signal Processing course as a case study. A total of 18 behavioural indicators were extracted and divided into three categories: basic learning behaviours, self-regulated learning behaviours, and extended learning behaviours. Data analysis of the behavioural indicators yielded the following conclusions: (1) Students did not have the habit of watching course playback and were less receptive to multiple online learning platforms; (2) Students’ midterm performance and duration of livestream watching directly affected their basic learning behaviours, with all indicators of self-regulated and extended learning behaviours showing significant correlations; (3) The clustering of learning behaviours yielded four different learner patterns, which calls for personalised teaching strategies; (4) The random forest algorithm had an accuracy of 95.4% in predicting performance of the four types of learners.

Computational Complexity Optimization of Neural Network-Based Equalizers in Digital Signal Processing: A Comprehensive Approach

Computational Complexity Optimization of Neural Network-Based Equalizers in Digital Signal Processing: A Comprehensive Approach

High Wideband Digital Oscilloscope Design

In most test applications, acquisition and analysis involving simultaneous processing of analog and digital signals. However, the bandwidth of most mainstream digital oscilloscopes is limited to 100 MHz, which is unable to meet the testing needs of high-frequency signals in complex electronic systems [1], and therefore, high-bandwidth digital oscilloscopes have emerged. Based on this background, this paper designs a digital oscilloscope hardware platform with high bandwidth by integrating FPGA and ARM technologies, aiming to meet the rigorous testing requirements of modern electronic systems. The FPGA module is based on the xc7s75fgga676 chip, which is mainly responsible for ADC control, data processing and frequency measurement functions. AM5708 is selected as the ARM module to realize the trigger, time base, amplitude and automatic setting functions of the oscilloscope. In order to ensure the accuracy and fidelity of waveform changes, the Sinc function interpolation method is used. This design further improves the acquisition bandwidth and processing speed on the basis of traditional MSO (Mixed Signal Oscilloscope) oscilloscopes, which is of great significance for the acquisition and processing of high-speed signals.

Multistatic Passive Radar for drone detection based Random Finite State

Considering the implication of radar sensors in our daily life and environment. Localizing and identifying drones are becoming a research with a greater focus in recent years. Consequently, when an unmanned aerial vehicle is used with bad intention, this can lead to a serious public safety and privacy probem. This study investigate pratical use of spectrum range for multistatic passive radar (MSPR) signal processing . Firstly, signal processing is performed after MSPR sensing detection range ,this include multipath energy detection, reference signal extraction, and receiving antenna configuration. Secondly, based on the MSPR nature, the reference signal is extracted and analyzed. In addition,taking into consideration the vulnerability of passive radar when comes to a moving target localization and real time tracking detection ,a novel method for spectrum sensing and detection which relies on Gaussian filter is proposed. The main goal is to optimize the use of the reference signal extracted with minimum interference as the shared reference signal in spectrum sensing. This will improve the system detection capability and spectrum access. Finally, a recursive method based on Bernoulli random filter is proposed, this takes consideration of drone’s present and unknown states based on time. Moreover, a system is developed meticulously to track and enhance detection of the target. A careful result of the experiment demonstrated that spectral detection can be achieved accurately even when the drone is moving while chasing its position. It shows that Cramer Rao lower error bounds remains significantly within 3% range.

Recent Advances in Low-Power Digital Signal Processing Technologies for Data Center Applications

Recent Advances in Low-Power Digital Signal Processing Technologies for Data Center Applications

Encryption Technology of Optical Communication Network Based on Artificial Intelligence Technology

At present, research on enhancing information transmission security by addressing the two key issues of time delay signal elimination and key space expansion in chaotic secure communication systems has become a hot topic. In order to improve the encryption effect of optical communication network, this paper analyzes the encryption technology of optical communication network with AIT (artificial intelligence technology), designs the encryption scheme of optical communication network with the help of AIT, and takes the digital random sequence as the key. Moreover, this paper uses the digital signal processor to control the arbitrary wave generator to generate multi-ary step square wave, modulate the optical feedback and realize the highly random change of external cavity delay, thus eliminating the long external cavity delay information. This article proposes a chaotic secure communication system using digital sequences as keys and external cavity optical feedback, a device for forming a chaotic source through arbitrary wave phase modulation and single loop feedback, and a chaotic secure communication system with single feedback key phase modulation and injection synchronization. At the same time, this paper proposes a system scheme using single-loop optical feedback phase modulation, the CS(chaotic signal) with complex dynamic behavior is output, and the time-delay signal is effectively eliminated. This paper analyzes the strength and phase information of CS by autocorrelation and mutual information technology, and verifies the effect of optical communication network encryption technology. Through the analysis of experimental results, it can be seen that the optical communication network encryption technology based on AIT proposed in this paper can effectively improve the encryption effect of optical communication network. The algorithm model camera proposed in this article can be used in subsequent practice to improve communication encryption performance

Robust Voltage Control of a Single-Phase UPS Inverter Utilizing LMI-Based Optimization with All-Pass Filter Under System Uncertainty

This paper proposes a systematic control design for a single-phase LC-filtered inverter considering uncertain system parameters. One major difficulty in controlling single-phase power converters is the lack of a direct conversion method for transforming single-phase signals into dq-frame signals. By employing an all-pass filter in this proposed approach, it is possible to control the output voltage in terms of DC quantity or the dq-rotating frame. Furthermore, voltage stability and harmonic distortion (THD) minimization of the uninterruptible power supply (UPS) are major concerns in inverter design. Therefore, this controller uses integral action to get rid of steady-state errors and stabilize the closed-loop system by the state feedback control. In order to enlarge and guarantee the stability range in the presence of potential parameter fluctuations, an uncertainty model is being considered. In this context, the uncertainty models refer to the potential model with variations in the filter's inductance and capacitance caused by operating temperature, aging, and various external factors. The efficacy of the control approach is assessed through simulations and experiments, with the objective of comparing its results with those of the PI control using a control board featuring a TMS320F28335 digital signal processor. Consequently, the proposed approach offers lower THD at every load step with lesser afford in performance tuning in comparison to the PI method.

Complex-Valued FastICA Estimator with a Weighted Unitary Constraint: A Robust and Equivariant Estimator

Independent component analysis (ICA), as a statistical and computational approach, has been successfully applied to digital signal processing. Performance analysis for the ICA approach is perceived as a challenging task to work on. This contribution concerns the complex-valued FastICA algorithm in the range of ICA over the complex number domain. The focus is on the robust and equivariant behavior analysis of the complex-valued FastICA estimator. Although the complex-valued FastICA algorithm as well as its derivatives have been widely used methods for approaching the complex blind signal separation problem, rigorous mathematical treatments of the robust measurement and equivariance for the complex-valued FastICA estimator are still missing. This paper strictly analyzes the robustness against outliers and separation performance depending on the global system. We begin with defining the influence function (IF) of complex-valued FastICA functional and followed by deriving its closed-form expression. Then, we prove that the complex-valued FastICA algorithm based on the optimizing cost function is linear-equivariant, depending only on the source signals.

Opto-electronic machine learning network for Kramers-Kronig receiver linearization

We numerically demonstrate the use of an opto-electronic network comprising a photonic reservoir and an electronic feedforward equalizer (FFE) to linearize a Kramers-Kronig (KK) receiver. The KK receiver is operated under stringent conditions, with restricted sampling rates and low carrier powers, resulting in a nonlinear behavior. We propose two different network configurations, varying in the placement of the FFE component, and evaluate their ability to linearize the KK receiver. By training these networks on back-to-back systems, we arrive at a generic solution that significantly enhances the receiver performance, independent of specific link characteristics. The trained networks are tested in a plug-and-play manner across diverse short-reach links that employ standard digital signal processing blocks for the qualization. Our results show significant improvement in receiver linearity, resulting in a reduction in bit error rate of up to a factor of four.

Adaptive multi-band modulation for robust and low-complexity faster-than-Nyquist non-orthogonal FDM IM-DD systems

Faster-than-Nyquist non-orthogonal frequency-division multiplexing (FTN-NOFDM) has been shown to have good robustness against the steep frequency roll-off in a bandwidth-limited optical communication system. Among various FTN-NOFDM techniques, the non-orthogonal matrix precoding (NOM-p) based FTN has relatively high compatibility, which can easily utilize the existing advanced digital signal processing (DSP) techniques in the conventional OFDM. In this work, we propose what we believe to be a novel FTN-NOFDM scheme with adaptive multi-band modulation. By dividing the single-band NOM-p into multiple-band NOM-p, the proposed scheme is able to assign different quadrature amplitude modulation (QAM) levels to different sub-bands, leading to better utilization of the low-pass-like channel as well as reduced computational complexity. The impacts of sub-band number and bandwidth compression factor on the bit-error-rate (BER) performance and complexity are experimentally analyzed in a 32.23-Gb/s and 20-km intensity modulation-direct detection (IM-DD) optical transmission system. Results show that the proposed scheme with a proper sub-band number can lower the BER and greatly reduce the complexity compared to the conventional single-band scheme.

Research on Tunnel Boring Machine Tunnel Water Disaster Detection and Radar Echo Signal Processing

This study focused on the detection of water inrush in tunnels excavated by full-section hard rock tunnel boring machines (TBMs) and employed ground penetrating radar methods for conducting research on radar signal processing algorithms. The research demonstrates that conventional techniques are inadequate for eliminating the interference of TBM equipment on radar signal propagation. This study employs a radar antenna array method for signal transmission, utilizing a wavelet double-threshold filtering algorithm and wave propagation theory to suppress clutter. These methods exhibit strong signal reception capabilities and are effective in eliminating 13.1% of the direct wave components. The adoption of a novel, efficient radar signal imaging algorithm simplifies the imaging process. Results of verification indicate that the synthetic aperture algorithm, enhanced with cross-correlation calculation, yields the optimal imaging effect. This investigation, which was conducted in conjunction with the construction of a diversion tunnel in a specific region, has confirmed the applicability of the ground penetrating radar method for the detection of water inrush in TBM tunnels by conducting a comparative analysis of the direct wave removal algorithm and the integration of the optimal imaging algorithm. The innovative application of ground penetrating radar within TBM tunnels, along with a targeted technology to mitigate signal interference from metal equipment, has led to the selection of an appropriate algorithm for both signal processing and imaging. This approach offers a novel solution for the detection of water source disasters in TBM tunnels.

A novel five-dimensional non-Hamiltonian conservative hyperchaotic system with multiple amplitude-modulated behaviors

In this work, we propose a new five-dimensional non-Hamiltonian conservative hyperchaotic system with infinitely many equilibrium points. Both this system and its fractional-order system are characterized by multiparametric modulation of the system amplitude. Variation of the parameter a can cause the system’s motion state to transform between quasi-periodic, chaotic, and hyperchaotic. This system shows its multistability when the initial value x10 is changed. It is important to note that the order q3 in fractional-order system not only controls the system amplitude but also affects the system property. NIST (National Institute of Standards and Technology) tests illustrate that the conservative system can be applied as a random number generator. Finally, a DSP (Digital Signal Processing) based hardware experiment platform confirms the physical realizability of the system.

Implementation of a Reverse Carry Propagate Adder Based On Efficient VLSI for Hardware Security and Area Consumption

The various techniques inbuilt in the VLSI (Very Large Scale Integration) designing is originated from the basis of adder circuits. When these adder circuits are processed in the higher digital signal processing systems, the adders have to exhibit high performance, good efficiency with reduced cost and area of implementation. The major objective of designing the VLSI design is minimizing the complexity and to perform the operations more effectively. Whereas in some other methods, the logic circuit designing is made larger in order to achieve higher efficiency. This in turn, results in the reduction of hardware security and makes the computation more complex. This paper utilizes the RCPA adder logic to reduce the area for the implementation and enhancing the hardware security. By implementing RCPA adder circuit, the carry propagates in the opposite direction from the most significant bit to the least significant bit. The usage of shift accumulator improves the speed of process and reduces the area required. By implementing the reverse propagation of the carry in the adder circuit, computation time is optimized and the implementation is made efficient with the reduction in the delay.

The UTMOST-NS: a fully digital, wide-field transient search facility operating at a centre frequency of 831 MHz

ABSTRACT The Molonglo Cross was first commissioned in 1965, as a transit radio (408 MHz) interferometer with the largest collecting area in the Southern hemisphere. In 1981, the telescope was redeveloped as an Earth-rotation synthesis interferometer using only the East–West arm (843 MHz), known as the Molonglo Observatory Synthesis Telescope. While the East–West arm was revitalized in the 2010s, the (slightly larger) North–South (NS) arm, which consists of two co-linear paraboloid cylindrical reflectors spanning 2 × 778 m × 12.7 m, had not been used for over 40 yr. Re-fitting this 19 800-m2 collecting area with modern electronics is a cost-effective way of producing a significant survey instrument. The upgrades made to the entire signal chain of the NS arm from the antenna through the transport, digitization, and digital signal processing are described, along with the subsequent performance of the system. The instrument was designed to undertake pulsar timing and searching for dispersed single pulses [e.g. from fast radio bursts (FRBs)]. The upgraded system operated across the 806.25–856.25-MHz frequency range, and had a primary beam that spans 12.7 × 2.5 deg. It had dual linear polarization capability and a lower system temperature and wider bandwidth compared with the East–West system. The digital signal processing was performed on servers with graphics processing units, which enabled low-latency, high-speed data processing, and made use of pipelines built from existing and custom codes. It timed around 70 pulsars per day while running concurrent FRB searches at nearly 100 per cent duty cycle during its operation.

The main directions of enhancement of digital antenna arrays

The development of modern radio electronic systems causes an increase in the requirements for the parameters of antenna devices (AU) and causes the transition from previously used mirror antennas and passive phased array antennas (FAA) to active FAA (AFAA), the considerable advantage of which is a significant reduction in energy losses of transmitted and received signals by reducing the distance of the low-noise amplifier input and output of power amplifier to the antenna element. Further development of the AU is the transition from AFAA with analog beamforming to digital antenna arrays (DAR) with digital beamforming, the advantages of which are due to the possibility of forming multibeam receiving and transmitting radiation patterns with independent control of the direction and shape of the beams, as well as the possibility of flexible change of operating modes. The use of a DAR with two-dimensional electronic scanning provides a significant increase in the efficiency of radio-electronic systems. Thus, their use in radar provides a gain in the efficiency of using the time, energy, frequency and spatial resources of radar with CAR up to 13 times compared with radar with passive FAA and AFAA with one-dimensional scanning. The disadvantages of the DAR are the high cost and increased energy consumption due to the installation of active elements in each transceiver channel, as well as the long time required to create new products, associated with a large amount of software and a complex structure for building a CAR. To overcome these disadvantages, manufacturers of antenna arrays and developers of the radio-electronic element base are creating new technical solutions. The main directions of development of technologies for the production of DAR functional devices that reduce the cost and reduce the time needed to create new products are shown: the development of common modules that allow you to create scalable DAR, increasing the integration of microwave monolithic integrated circuits with the placement of the maximum number of transceiver channels on one chip, increasing the integration of ASIC, including ADCs, DACs and digital signal processing devices, increasing the clock frequencies of digital functional nodes, as well as the development of circuit solutions for building nodes with low energy consumption.

Ultra-Efficient Low-Power Retinal Nano Electronic Circuit for Edge Enhancement and Detection Using 7 nm FinFET Technology

Ultra-Efficient Low-Power Retinal Nano Electronic Circuit for Edge Enhancement and Detection Using 7 nm FinFET Technology

Thin-film lithium niobate-based electro-optic comb cloning for self-homodyne coherent communication.

As the optical communication industry advances, metropolitan area networks (MANs) and radio access networks (RANs) are extensively deployed on a large scale, demanding energy-efficient integrated light sources and simplified digital signal processing (DSP) technologies. The emergence of thin-film lithium niobate (TFLN) has given rise to high-performance, energy-efficient on-chip modulators, making on-chip optical frequency comb (OFC) more appealing. Owing to the phase uniformity and stability of this chip-scale device, it has been possible to eliminate the carrier frequency phase estimation (CPE) in DSP stacks using comb-clone-enabled self-homodyne detection. Here we report the first use, to our knowledge, of a TFLN on-chip electro-optic (EO) frequency comb to realize comb cloning and self-homodyne coherent detection. We transmit three optical pilot tones and eight data channels encoded with 20 Gbaud polarization-multiplexed 16-ary quadrature amplitude modulation (PM-16-QAM) over 10 km and 80 km standard single-mode fibers. The bit error ratios (BERs) of the eight channels reach below 10-3, a result made possible by our on-chip comb. The scalability and mass producibility of on-chip EO combs, combined with the simplified DSP, show potential in our proposed fifth-generation (5G) RAN and MAN transmission scheme.

Design and Implementation of Braun Multiplier using Verilog: Research

Abstract: Multiplication is widely used in places like digital signal processing, image processing, instrumentation that require multilayer components. Carry Save Adder and ripple carry adder both are used in parallel processing architecture. They are widely used for signed multiplication i.e. for both negative and positive numbers. We have now designed a Braun multiplier (BM) to improve the speed, power and area capability. We are using the Xilinx tool to verify Braun multipliers using Verilog. We are taking the following considerations: checking using FPGA based instruments and implementing code using Verilog-VHDL. The adders are integrated into multipliers. The result of this research is to modify BM to improve the performance along with reduction in power consumed and also using less area.

DSP-based inter-channel interference monitoring in flexible wavelength-routed networks

The efficiency of optical networks employing flexible wavelength division multiplexing (WDM) can be increased by maximizing the throughput of each individual channel, provided that the position of its neighboring channel is known with sufficient accuracy in order to avoid inter-channel interference. In this paper, we propose a digital signal processing (DSP) algorithm, leveraging the use of an artificial neural network (ANN), to estimate the neighboring channels’ distance by processing raw digital samples from a standard coherent receiver. We present an efficient dataset design approach, based on Latin hypercube sampling (LHS), in order to effectively optimize and validate the algorithm under different assumptions on the optical WDM channels. We investigate the accuracy of the ANN-based DSP scheme through simulation analysis, highlighting its potential in relation to the characteristics of the optical network. Finally, we validate our approach in an experimental setup using standard commercial coherent transceivers. The experimental results show that the distance from the neighboring WDM channels can be estimated with a root mean square error of less than 1.5 GHz for a channel under test with a symbol rate of 52 GBaud.