Digital Signal Processing Research Articles

Test and evaluation of radar systems operating in the modern electromagnetic spectrum

AbstractModern radar systems are critical infrastructure in defence and civilian applications. In the defence domain, modern radars operate in a highly contested, congested, and constrained electromagnetic environment. In the context of operating in this challenging environment, the challenges across the system life cycle are examined in testing modern radar systems which are characterised by advanced features, such as multi‐function capability, advanced digital signal processing, high resolution, wideband, and frequency agile systems that incorporate phase array and active electronically scanned array capabilities. The challenges and key objectives in testing these sophisticated modern radar systems are highlighted, as well as the enabling technologies that can support Test & Evaluation of such systems. An architecture for Hardware‐in‐the‐Loop testing, which leverages modular and flexible commercial‐of‐the‐shelf hardware, is proposed together with an application software that allows the testing of radar with a radar target generator.

W-band photonic-aided mm-wave ISAC system enabled by a shared OFDM signal waveform and a two-stage carrier frequency recovery algorithm.

Integrated sensing and communication (ISAC) systems will play a potential role in the upcoming six-generation (6G) networks. The reason is that ISAC systems can effectively solve the spectrum resource shortage problem and decrease the cost of deploying hardware equipment for simultaneously realizing communication and sensing. In this Letter, we successfully realize a W-band photonic-aided millimeter-wave (mm-wave) ISAC system enabled by a shared orthogonal-frequency-division-multiplexing (OFDM) signal waveform and two-stage carrier frequency recovery (CFR) algorithm. The digital-signal-processing (DSP)-based two-stage CFR algorithm includes the first-stage fractional frequency offset (FFO) estimation and compensation as well as the second-stage integer frequency offset (IFO) estimation and compensation. We experimentally analyze and verify that, with the introduction of the two-stage CFR algorithm, the system robustness to carrier frequency offset can be significantly enhanced. We also experimentally demonstrate, based on the ISAC system and our receiver DSP, a net data rate of up to 47.54 Gbit/s with a total signal bandwidth of 16 GHz over a 5.2 m wireless link at 94.5 GHz. Moreover, the sensing results indicate that the ISAC system can realize the detection of one target 2 m away from the transmitter with a ranging resolution of 0.98 cm and a ranging error of 4 mm. The system is anticipated to facilitate diverse potential applications in future 6G networks.

Comparative analysis of Vedic multiplier using Vedic sutras with existing multipliers in biomedical application

In today's computer world, a lot of real-time applications require rapid processing units. Arithmetic Logic Units (ALU) and Multiply-Accumulate (MAC) are the fundamental parts of these circuits and are necessary for their effective and rapid operation. The most significant prevalent part of digital signal processing devices is multipliers. The multiplier, adder, and registers need to be changed in order to maintain accuracy and increase execution speed, which will improve the performance of the ALU and MAC. The development of greater multipliers is being given priority for application in processors because of the increasing constraints on latency. To accelerate multiplication, it is essential to develop quicker multipliers. Vedic multipliers are preferred over different current expansions due to their low power consumption, fast operation, and efficient use of space. Vedic mathematics-based algorithms are often utilized to build quick, low-power multipliers. In addition to simulation results, this section covers the four sutras of Vedic mathematics: Urdhva Tiryakbhyam, Ekadhikena Purvena, Ekanyunena Purvena, and Nikhilam. Vedic multipliers are also compared to a variety of modern multipliers, including booth, Wallace, and array multipliers. All of the sutras are evaluated according to area, speed, power, propagation delay, and mean relative error (MRE) in the current research. The results of the study will be applied in the biomedical field.

Can AI Predict the Magnitude and Direction of Ortho-K Contact Lens Decentration to Limit Induced HOAs and Astigmatism?

Background: The aim is to investigate induced higher-order aberrations (HOA)s and astigmatism as a result of non-toric ortho-k lens decentration and utilise artificial intelligence (AI) to predict its magnitude and direction. Methods: Medmont E300 Video topographer was used to scan 249 corneas before and after ortho-k wear. Custom-built MATLAB codes extracted topography data and determined lens decentration from the boundary and midpoint of the central flattened treatment zone (TZ). An evaluation was carried out by conducting Zernike polynomial fittings via a computer-coded digital signal processing procedure. Finally, an AI-based machine learning neural network algorithm was developed to predict the direction and magnitude of TZ decentration. Results: Analysis of the first 21 Zernike polynomial coefficients indicate that the four low-order and four higher-order aberration terms were changed significantly by ortho-k wear. While baseline astigmatism was not correlated with lens decentration (R = 0.09), post-ortho-k astigmatism was moderately correlated with decentration (R = 0.38) and the difference in astigmatism (R = 0.3). Decentration was classified into three groups: ≤0.50 mm, reduced astigmatism by -0.9 ± 1 D; 0.5~1 mm, increased astigmatism by 0.8 ± 0.1 D; >1 mm, increased astigmatism by 2.7 ± 1.6 D and over 50% of lenses were decentred >0.5 mm. For lenses decentred >1 mm, 29.8% of right and 42.7% of left lenses decentred temporal-inferiorly and 13.7% of right and 9.4% of left lenses decentred temporal-superiorly. AI-based prediction successfully identified the decentration direction with accuracies of 70.2% for right and 71.8% for left lenses and predicted the magnitude of decentration with root-mean-square (RMS) of 0.31 mm and 0.25 mm for right and left eyes, respectively. Conclusions: Ortho-k lens decentration is common when fitting non-toric ortho-k lenses, resulting in induced HOAs and astigmatism, with the magnitude being related to the amount of decentration. AI-based algorithms can effectively predict decentration, potentially allowing for better control over ortho-k fitting and, thus, preferred clinical outcomes.

Retraction Note: A nano-scale design of a multiply-accumulate unit for digital signal processing based on quantum computing

Retraction Note: A nano-scale design of a multiply-accumulate unit for digital signal processing based on quantum computing

Low Power Multiplier Using Approximate Adder for Error Tolerant Applications

In embedded applications and digital signal processing systems, multipliers are crucial components. In these applications, there is an increasing need for energy-efficient circuits. We use an approximate adder for error tolerance in the computational process to improve performance and reduce power consumption. Due to human perceptual constraints, computational errors do not significantly affect applications like image, audio, and video processing. Adiabatic logic (AL), which recycles energy, can also be used to build circuits that require less energy. In this work, we propose a carry save array multiplier employing an approximate adder based on CMOS logic and clocked CMOS adiabatic logic (CCAL) to conserve power. Additionally, using a precise full adder, multiplier parameters like average power and power delay product are calculated and compared with the multiplier. We performed simulations using 180 nm technology in Cadence Virtuoso.

Low-complexity adaptive multipath interference and channel noise mitigation scheme based on optimized detection for bandwidth-limited IM/DD systems.

In this Letter, we propose a low-complexity adaptive multipath interference (MPI) and channel noise mitigation (AMCM) scheme in the receiver digital signal processing (DSP) for bandwidth-limited intensity modulation and direct detection (IM/DD) transmission systems. Following channel equalization, MPI and channel noise are distributed in the low- and high-frequency parts, respectively, and exhibit the characteristics of bandstop filtering. The proposed AMCM is designed based on optimized detection, which incorporates an adaptive bandpass filter (BPF) and a log-maximum a posteriori estimation with a lookup table-based fixed number of surviving states (LUT-based FS-MAP) decoder. The adaptive BPF is capable of mitigating the MPI and channel noise based on spectral distribution. Moreover, the LUT-based FS-MAP decoder can eliminate intersymbol interference (ISI) introduced by the BPF. The proposed AMCM is implemented in an O-band 56-Gbaud IM/DD optical 4-level pulse amplitude modulation (PAM-4) system with a 10.7-GHz bandwidth over a 10-km standard single-mode fiber with different linewidths. The results demonstrate that the proposed AMCM scheme can enhance signal-to-interference ratio (SIR) tolerance to 11 dB with only three real-valued multiplications per symbol, achieving a 7% hard-decision forward error correction threshold. To the best of our knowledge, for the first time, this represents the inaugural instance of optimized detection being employed for MPI mitigation.

Ten quick tips for clinical electroencephalographic (EEG) data acquisition and signal processing.

Electroencephalography (EEG) is a medical engineering technique aimed at recording the electric activity of the human brain. Brain signals derived from an EEG device can be processed and analyzed through computers by using digital signal processing, computational statistics, and machine learning techniques, that can lead to scientifically-relevant results and outcomes about how the brain works. In the last decades, the spread of EEG devices and the higher availability of EEG data, of computational resources, and of software packages for electroencephalography analysis has made EEG signal processing easier and faster to perform for any researcher worldwide. This increased ease to carry out computational analyses of EEG data, however, has made it easier to make mistakes, as well. And these mistakes, if unnoticed or treated wrongly, can in turn lead to wrong results or misleading outcomes, with worrisome consequences for patients and for the advancements of the knowledge about human brain. To tackle this problem, we present here our ten quick tips to perform electroencephalography signal processing analyses avoiding common mistakes: a short list of guidelines designed for beginners on what to do, how to do it, and what not to do when analyzing EEG data with a computer. We believe that following our quick recommendations can lead to better, more reliable and more robust results and outcome in clinical neuroscientific research.

Experimental Implementation of a TD3 Agent Based Speed Controller for Direct Torque Control of PMSM Drives

This manuscript presents a novel control approach for Permanent Magnet Synchronous Motors (PMSMs) by integrating the widely used Direct Torque Control (DTC) method with Deep Reinforcement Learning (DRL), specifically the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. The TD3 algorithm is well-suited to address the challenges posed by high-dimensional state and action spaces in PMSM drives. The conventional Proportional–Integral (PI) controller in the outer loop of DTC is replaced with the DRL based TD3 agent to overcome the limitations of traditional PI controllers, such as model dependency and complex parameter tuning. The DRL technique allows the agent to learn optimal control policies from experience, making it suitable for complex and nonlinear control problems. Extensive simulation studies demonstrate the effectiveness of the TD3-based control in achieving accurate speed tracking under varying operating conditions. Real-time experimental validation using a TMS320F28379D digital signal processor confirms the feasibility of the proposed DRL based approach. The research offers new insights into improving the performance of PMSM drives and paves the way for future advancements in electric drive control.

A Unified Hardware Design for Multiplication, Division, and Square Roots Using Binary Logarithms

Multiplication, division, and square root operations introduce significant challenges in digital signal processing (DSP) systems, traditionally requiring multiple operations that increase execution time and hardware complexity. This study presents a novel approach that leverages binary logarithms to perform these operations using only addition, subtraction, and shifts, enabling a unified hardware implementation—a marked departure from conventional methods that handle these operations separately. The proposed design, involving logarithm and antilogarithm calculations, exhibits an algebraically symmetrical pattern that further optimizes the processing flow. Additionally, this study introduces innovative log-domain correction terms specifically designed to minimize computation errors—a critical improvement over existing methods that often struggle with precision. Compared to standard hardware implementations, the proposed design significantly reduces hardware resource utilization and power consumption while maintaining high operational frequency.

Early-Stage Prototype Assessment of Cost-Effective Non-Intrusive Wearable Device for Instant Home Fetal Movement and Distress Detection: A Pilot Study.

Clinical fetal monitoring devices can only be operated by medical professionals and are overly costly, prone to detrimental false positives, and emit radiation. Thus, highly accurate, easily accessible, simplified, and cost-effective fetal monitoring devices have gained an enormous interest in obstetrics. In this study, a cost-effective and user-friendly wearable home fetal movement and distress detection device is developed and assessed for early-stage design progression by facilitating continuous, comfortable, and non-invasive monitoring of the fetus during the final trimester. The functionality of the developed prototype is mainly based on a microcontroller, a single accelerometer, and a specialized fetal phonocardiography (fPCG) acquisition board with a low-cost microphone. The developed system is capable of identifying fetal movement and monitors fetal heart rhythm owing to its considerable sensitivity. Further, the device includes a Global System for Mobile Communication (GSM)-based alert system for instant distress notifications to the mother, proxy, and emergency services. By incorporating digital signal processing, the system achieves zero false negatives in detecting fetal movements, which was validated against an open-source database. The acquired results clearly substantiated the efficacy of the fPCG acquisition board and alarm system, ensuring the prompt identification of fetal distress.

Simplified coherent chaotic optical secure communication scheme based on the Kramers-Kronig receiver.

Enhancing physical layer encryption in fiber-optic networks remains a challenging yet vital task. In this Letter, we propose a simplified coherent chaotic secure optical communication scheme based on the Kramers-Kronig (KK) receiver. This scheme incorporates a semiconductor laser with a phase-conjugated optical feedback serving as a common chaotic source, and its chaotic output is directly injected into the two slave lasers arranged separately at the transmitter and receiver end to achieve high-quality synchronization of chaotic signals, with a corresponding chaotic bandwidth of 30.6 GHz. By virtue of the common-signal-induced broad chaotic synchronization, a proof-of-principle demonstration is successfully conducted. It involves the secure transmission of a 20 Gbaud 16-level quadrature amplitude modulation (16QAM) signal over a 50 km standard single-mode fiber (SSMF) link. At the receiver end, we deploy a KK receiver to reconstruct the field of the optical signal and hence enable signal compensation and recovery with offline digital signal processing (DSP). This method simplifies device requirements in the current chaotic coherent optical secure communication, offering a cost-effective mode and promising path for advancing physical layer encryption in inter-data center communications.

Enhancing microgrid production through particle swarm optimization and genetic algorithm

<p>The growing demand for sustainable and efficient energy solutions has led to research on optimizing renewable energy sources within microgrid systems. This study presents a comparative analysis of two prominent optimization techniques, particle swarm optimization (PSO) and genetic algorithm (GA), to enhance solar photovoltaic PV and wind production in microgrids. The aim is to achieve a balanced and efficient energy generation that closely matches the load demand, thereby minimizing energy wastage and ensuring a reliable energy supply. The two algorithms are employed using data representing PV and wind production, as well as load consumption, over a 24-hour period. The results are evaluated based on their ability to reduce the gap between energy production and load demand. Our findings reveal compelling insights into the performance of GA and PSO in the context of microgrid optimization. To validate the results obtained from the simulation, the PSO algorithm is implemented on an actual cart Digital Signal Processor DSP platform, using a processor-in-the-loop (PIL). This successful real-world application highlights the practical viability of utilizing PSO to improve solar PV and wind energy generation within microgrids.</p>

Research on data processing technology based on 6LiF/ZnO:Ga fiber neutron detector array

The 6LiF/ZnO:Ga fiber neutron detector, consisting of a 6LiF/ZnO:Ga scintillator, optical fiber, and PMT, has distinct advantages such as compactness, strong real-time online measurement capabilities, and resistance to electromagnetic interference. These characteristics make it highly suitable for neutron detection in confined spaces with significant electromagnetic interference. However, its small size limits the neutron detection efficiency of a single detector, necessitating the use of multiple fibers to construct a fiber array and enhance sensitivity. The goal is to study data processing techniques for the 6LiF/ZnO:Ga fiber detector array. Inside the FPGA, three digital signal processing channels are used to extract multiple information from signal such as the amplitude, timestamp, and measurement channel ID. The fast channel adopts triangular shaping to provide real-time baselines and timestamps for the discrimination channel and the slow channel. The slow channel adopt cascade shaping method to extract the amplitude of nuclear signal. The discrimination channel method adopt cascade discrimination method to realize the real-time discrimination between gamma signals, neutron signals and interference signals. The method has been successfully applied to 6LiF/ZnO:Ga fiber neutron detector arrays with different mass ratios, providing new solution for digital data processing in fiber neutron detector arrays.

An End-to-End Modular Framework for Radar Signal Processing: A Simulation-Based Tutorial

An End-to-End Modular Framework for Radar Signal Processing: A Simulation-Based Tutorial

Метод обработки сигналов токов статора асинхронного двигателя для диагностики обрыва стержня ротора

The study is relevant due to high requirements to the reliability of the operation of auxiliary mechanisms of thermal power plants (TPP). The main source of mechanical power of auxiliary mechanisms of TPPs is high-voltage induction motor with squirrel cage rotor (IMSC). One of the most difficult causes of emergency shutdown to detect early is a broken rotor bar. The breakage of IMSC rotor bar is of latent character. It can be for a long time without considerable influence on the machine operation mode. Nevertheless, the fact of the breakage can be considered as an emergency condition of IMSC, and the consequences of leaving the groove of the magnetic core are irreversible. Scientifically, early diagnostics of IMSC rotor bars breakage of TPP auxiliary needs is both a difficult and extremely urgent task. The existing methods of diagnostics of such damage are based on measurement and analysis of vibration and acoustic physical quantities. The most common electrical parameter, used as a source of information, as a rule, is current consumption. And most of methods are based on Fourier analysis. The purpose of the study is to develop a mathematical algorithm to process digitized curves of stator phase currents to diagnose high-voltage IMSC. The theory of electric machines, the method of analytical approximation of experimental data, the method of regression analysis have been used to solve the problem. Experimental data is obtained, and testing of the algorithm is conducted on an experimental installation with a 0,4 kV induction motor with a modified design of the active part of the rotor developed for physical simulation of IMSC broken rotor bar. This paper proposes a new method of digital processing of stator current signals based on the regression analysis method for diagnostics of IMSC rotor winding. The authors have developed an algorithm for mathematical processing of digitized stator current curves based on regression analysis in the cosine-sine basis to identify the diagnostic sign of failure of one rotor bar of IMSC rotor. The authors have determined the number of harmonic components that best describe the initial signal from the point of view of the balance between saving computational resources and accuracy of approximation. A mathematical algorithm to detect the rotor bar breakage of an induction motor based on regression analysis of stator currents has been obtained and tested. It allows to detect rotor circuit damage with 97 % accuracy. At the same time the diagnostic sign changes its level when one bar breaks by 5 %. It is recommended to adapt the algorithm to the programming languages of microprocessor relay protection units.

Method for determining phase shift using two-phase interpolation transformation

This study focuses on a method for accurately determining the phase shift between two harmonic signals. The proposed technique compares the waveform of the combined signal, which is obtained by applying a two-phase interpolation transformation, with a set of predefined reference functions. This study aims to develop a method for accurately measuring the phase shift between two harmonic signals to reduce the measurement errors caused by phase asymmetry in signal transmission channels and minimize the costs associated with parameter control. The sources of error in the proposed measurement method are identified and addressed. The task involves setting up the measurement objective to determine the phase shift between two harmonic signals. This section presents the analyses of known methods for measuring phase shifts using of analog-to-digital conversion. The next step involves selecting indicators and criteria to determine how closely the investigated signal matches the reference function. Then, we propose the synthesis of an algorithm to find the extremum of the sum of squares deviations for the set of reference functions and the investigated signal, relying on the golden ratio method. Finally, the paper will analyze possible sources of error that could affect the measurement outcome. The methods used are the following: methodology for conducting digital signal processing and measuring error estimation, numerical methods for extremum search, and methodology for single-factor experiments. The following results were obtained. A proposed compensation method for measuring phase shift is based on comparing the shape of the normalized signal, which is obtained as a result of the summation of harmonic signals after their semiperiodical transformation, with a set of normalized reference functions synthesized by computational means. A list of measurement and auxiliary operations, which should be ideally conducted to implement this measurement method, has been determined. An analysis of the components of measurement errors was conducted. Conclusions. The scientific novelty of the obtained results lies in the following: a method for measuring the phase shift of a signal has been developed, which, in our opinion, should be classified as a compensatory measurement method. This will significantly reduce the error component caused by the phase asymmetry of signal transmission channels and reduce the costs of controlling parameters (up to 10%) without decreasing the quality of control; a list of the measuring and auxiliary operations necessary for the implementation of the proposed measurement method has been identified; sources of errors have been determined.

KTz Neuron in Electromagnetic Radiation with a Novel Flux-Controlled Memristor

In this paper, a novel discrete flux-controlled generalized memristor is proposed to be used in Electromagnetic Radiation (EMR) KTz neuron. The introduction of flux-controlled memristor can simulate the behavior changes of the neuron under EMR. The stability of flux-controlled memristor EMR KTz Neuron (EKN) map is discussed, and the fixed point of the system is characterized. With the change of parameters, the complex and rich dynamical characteristics of the EKN map are demonstrated. The firing patterns under different initial values are also investigated, and discharge waveforms similar in general shape and structure to human heart and brain disease phenomena are analyzed. Finally, the hardware implementation is verified on the Digital Signal Processing (DSP) platform. The results show that these findings are of great value for the practical applications of neural networks, with a theoretical basis provided.

Optimized power and speed of Split-Radix, Radix-4 and Radix-2 FFT structures

Fast Fourier transform (FFT) is a fundamental building block for digital signal processing applications where high processing speed is crucial. Resource utilization in implementing FFT structures can be minimized by optimizing the performance of multipliers and adders used within the design. FFTs are also widely used in various machine learning algorithms. To achieve increased processor efficiency and reduced resource utilization, we propose a hardware design for Radix-2, Radix-4, and Split-Radix FFT architectures that utilizes a novel parallel prefix adder. This design offers lower power consumption, smaller chip area, and faster operation compared to existing architectures. Our performance analysis focuses on metrics such as power consumption, clock speed, and hardware complexity for Radix-2, Radix-4, and Split-Radix FFT algorithms implemented with the proposed adder. We compare these metrics using our proposed arithmetic structure against existing adder designs. The results indicate that the Split-Radix FFT architecture achieves lower power consumption and smaller chip area compared to Radix-4 and Radix-2 methods. Additionally, the Split-Radix FFT exhibits a higher clock speed. Therefore, based on these findings, the Split-Radix algorithm appears to be a compelling choice for implementation on field-programmable gate arrays due to its high speed and lower power consumption.

Performance Analysis of Microwave Photonic Spectral Filters based on Optical Microcombs

AbstractMicrowave transversal filters, which are implemented based on the transversal filter structure in digital signal processing, offer a high reconfigurability for achieving a variety of signal processing functions without changing hardware. When implemented using microwave photonic (MWP) technologies, also known as MWP transversal filters, they provide competitive advantages over their electrical counterparts, such as large operation bandwidth, strong immunity to electromagnetic interference, and low loss when processing signals at high frequencies. Recent advances in high‐performance optical microcombs provide compact and powerful multi‐wavelength sources for MWP transversal filters that require a larger number of wavelength channels to achieve high performance, allowing for the demonstration of a diverse range of filter functions with improved performance and new features. Here, a comprehensive performance analysis for microcomb‐based MWP spectral filters based on the transversal filter approach is presented. First, the theoretical limitations are investigated in the filter spectral response induced by finite tap numbers. Next, the distortions are analyzed in the filter spectral response resulting from experimental error sources. Finally, the influence of input signal's bandwidth on the filtering errors is assessed. These results provide a valuable guide for the design and optimization of microcomb‐based MWP transversal filters for a variety of applications.