Complex Signal Processing Algorithms Research Articles

Proposal for Real-time Quality Control Method to Enhance Hydrological Application of Radar Rainfall

The primary aim of a rain radar is to observe ground-level rainfall accurately. Effective quality control of rain radar data is necessary to ensure accuracy. In the field of hydrology, various methods have been employed to improve the quality of radar rainfall by correcting or synthesizing it with gauge rainfall. However, it is more important to enhance the quality of radar polarimetric variables in order to improve the quality of radar rainfall. Rain radar systems generate various polarimetric variables through complex radar hardware systems and signal processing algorithms. Measurement errors may arise from equipment abnormalities, inappropriate operating settings, and obstructions in observation during signal processing algorithms and production process of polarimetric variables. Because rain radar is an observation device operating in real time, it entails more frequent and continuous quality control compared to flowmeters that intermittently measure streamflow. This study introduces a series of real-time quality control methods tailored for rain radar, including inspection of radar rainfall accuracy, quality analysis of polarimetric variables (ρ<sub>HV</sub>, Z<sub>DR</sub>, Φ<sub>DP</sub>), error estimation of polarimetric variables, and long-term variability of errors.

APPLICATION OF THE RED PITAYA PLATFORM IN THE TECHNOLOGY OF PROTOTYPING AUTOMATED EDDY CURRENT TESTING SYSTEMS

Automated eddy current non-destructive testing has an important role in the quality inspection system for products made of conductive materials both at the production stage and during their operation. The appearance of novel alloys, the complexity of product geometry and inspection conditions, and the increased requirements for the reliability and accuracy of inspection results stimulate the acceleration process of creating new eddy current inspection tools. The technology of prototyping makes it possible to solve this problem. The purpose of the article is to review the functionality and technical characteristics of Red Pitaya for use in the technology of prototyping eddy current inspection, as well as to create a prototype architecture of an automated eddy current inspection system based on it.The choice of the Red Pitaya platform as a convenient tool for prototyping automated systems was made due to its functionality, reliability, and availability. In general, the article highlights the advantages and prospects of using the Red Pitaya platform in the prototyping of automated eddy current non-destructive testing systems. The aspects of the Red Pitaya hardware and its capabilities for expanding the functionality, which allows to create highly efficient and flexible control systems, are considered in detail. The compatibility of Red Pitaya with other devices and accessories is considered, which significantly increases its versatility and adaptability to various requirements and applications.The article highlights the importance of using the Jupyter Notebook application in combination with Red Pitaya as a convenient tool for software development. This helps to facilitate the process of creating and programmatically implementing complex signal processing algorithms in eddy current control systems, and provides flexibility in creating new software products.Modern trends and prospects for the development of eddy current testing, market needs, and the ability to adapt to different application scenarios are taken into account in the proposed architecture of the prototype automated eddy current testing system.

Research on electronic stethoscope system and signal processing algorithm

Stethoscopes have an important role in non-invasive diagnosis of cardiovascular and respiratory diseases, digestive diseases, and other kinds of diseases. The emergence of high-end diagnostic devices and new diagnostic methods have caused the status of the stethoscope to decline. However, stethoscope has the advantages of simple operation, mature auscultation theory and low cost, and thus is still widely used in medical diagnosis. This paper first introduces the design and application of electronic stethoscope solutions based on contact sensors and air coupling sensors, and then introduces advanced algorithms for digital signal processing for the diagnosis and treatment of different diseases, including heart sound noise reduction algorithm, heart sound segmentation algorithm and heart sound feature extraction and recognition algorithm. Finally, this paper summarizes the application of the electronic stethoscope system in medical testing, and its future development direction. In summary, the electronic stethoscope system is a reliable medical testing tool, which can convert sound signals into digital signals through complex signal processing algorithms for more accurate detection of human physiological parameters. The research of this paper will be of great value to the research and application of electronic stethoscopes.

A framework via impulses-oriented Gini index and extreme value distribution for rolling bearing dynamic fault alarm and identification

Rolling bearing dynamic fault alarm and identification is essential in condition-based maintenance and can prevent serious accidents. However, an integrated framework with dynamic adaptability and full interpretability is rarely reported for this issue based on sparsity measures and statistical properties. Therefore, a framework via impulses-oriented Gini index and extreme value distribution is developed in this paper. First, for attenuating normal-phase amplitude oscillations of the Gini index, periodical impulses-oriented Gini index (PIGI) and sparsity-smoothed periodical impulses-oriented Gini index (SPIGI) are defined successively through enhanced envelope impulses extraction to improve incipient fault sensitivity and robustness against interferences. Next, a dynamic alarm threshold setting strategy is built by fitting the available PIGIs using generalized extreme value distribution (GEVD). Further, a novel framework, without prior knowledge and complex signal processing algorithms, is established based on PIGI, SPIGI, and GEVD-based thresholds for dynamic fault alarm and identification. The verification results on simulation and experimental data indicate that the proposed framework is effective in balancing false alarms and missed alarms and detecting incipient faults, and thus would have favorable application prospects.

Approximate Computing-Based Processing of MEA Signals on FPGA

Microelectrode arrays (MEAs) are essential equipment in neuroscience for studying the nervous system’s behavior and organization. MEAs are arrays of parallel electrodes that work by sensing the extracellular potential of neurons in their proximity. Processing the data streams acquired from MEAs is a computationally intensive task requiring parallelization. It is performed using complex signal processing algorithms and architectural templates. In this paper, we propose using approximate computing-based algorithms on Field Programmable Gate Arrays (FPGAs), which can be very useful in custom implementations for processing neural signals acquired from MEAs. The motivation is to provide better performance gains in the system area, power consumption, and latency associated with real-time processing at the cost of reduced output accuracy within certain bounds. Three types of approximate adders are explored in different configurations to develop the signal processing algorithms. The algorithms are used to build approximate processing systems on FPGA and then compare them with the accurate system. All accurate and approximate systems are tested on real biological signals with the same settings. Results show an enhancement in processing speed of up to 37.6% in some approximate systems without a loss in accuracy. In other approximate systems, the area reduction is up to 14.3%. Other systems show the trade between processing speed, accuracy, and area.

Prototyping the Symmetry-Based Chaotic Communication System Using Microcontroller Unit

Chaos-based communications are a promising application of chaos theory and nonlinear dynamics. Their key features include concealed transmission, high security, and native broadband signals. Many studies have recently been published devoted to this technology. However, the practical implementations of chaos-based communications are rare due to multiple shortcomings: high hardware requirements, complex signal processing algorithms, and a lack of efficient modulation techniques for chaotic signals. In this study, we consider a simple hardware prototype of a coherent chaos-based communication system based on a novel type of modulation: adaptive symmetry of the finite-difference scheme used in a chaos generator. We explicitly demonstrate the possibility of covertly transmitting data using a chaotic transmitter and receiver implemented in a general-purpose microcontroller unit. A comparison between traditional parameter and symmetry modulation is given through a return map analysis and bit error rate estimation. The communication secrecy is analyzed using quantified return map analysis. The obtained results confirm the possibility of creating chaos-based communication systems based on symmetry modulation.

Signal Processing Platform for Long-Range Multi-Spectral Electro-Optical Systems.

In this paper, we present a hardware and software platform for signal processing (SPP) in long-range, multi-spectral, electro-optical systems (MSEOS). Such systems integrate various cameras such as lowlight color, medium or long-wave-infrared thermal and short-wave-infrared cameras together with other sensors such as laser range finders, radars, GPS receivers, etc. on rotational pan-tilt positioner platforms. An SPP is designed with the main goal to control all components of an MSEOS and execute complex signal processing algorithms such as video stabilization, artificial intelligence-based target detection, target tracking, video enhancement, target illumination, multi-sensory image fusion, etc. Such algorithms might be very computationally demanding, so an SPP enables them to run by splitting processing tasks between a field-programmable gate array (FPGA) unit, a multicore microprocessor (MCuP) and a graphic processing unit (GPU). Additionally, multiple SPPs can be linked together via an internal Gbps Ethernet-based network to balance the processing load. A detailed description of the SPP system and experimental results of workloads for typical algorithms on demonstrational MSEOS are given. Finally, we give remarks regarding upgrading SPPs as novel FPGAs, MCuPs and GPUs become available.

Digital Ultrasonic Sensing Device with Programmable Frequency: Development and Analysis

Ultrasonic wave is widely used in Structure Health Monitoring (SHM) systems. A piezoelectric transducer (PZT) is one of the most widely used sensors to acquire the structure's ultrasonic wave. As today's world is digital, it is necessary to digitize the traditional analog PZT sensing system. This paper describes the development and analysis of a digital ultrasonic sensing device (DUSD) for PZT sensors. We removed the complexities of the analog circuit by interfacing the microcontroller directly with the charge amplifier circuit. The microcontroller used in this research is a 32-bit ARM Cortex-M4 with in-built FPU (Floating Point Unit) and DSP (Digital signal processing) instructions. These features make it possible to compute complex signal processing algorithms and methods in the controller itself. The developed sensing device can communicate with the user and other devices using Universal Asynchronous Receiver/Transmitter (UART). The user can select cut-off frequencies of both high pass filters (HPF) and low pass filters (LPF) as well as types of data (ultrasonic waves, damage index) that the user wishes to collect from the device. To illustrate the proficiencies of the device, the ultrasonic wave was collected and evaluated to detect the damage in the test specimen.

A 6-Bit 1.5-GS/s SAR ADC With Smart Speculative Two-Tap Embedded DFE in 130-nm CMOS for Wireline Receiver Applications

Implementing wireline receivers with a front-end analog-to-digital converter (ADC) allows for complex, flexible, and robust signal processing algorithms in the digital domain, as well as easy implementation of advanced modulation schemes beyond binary PAM2. However, the power consumption of the ADC and ensuing digital equalization is a key issue for such receivers in high-speed applications. Embedding analog equalization inside the ADC architecture allows for both a lower ADC resolution and a reduced-complexity digital equalizer, resulting in a more power-efficient receiver. This article presents a 6-bit 1.5-GS/s time-interleaved successive approximation register (SAR) ADC with low-overhead two-tap embedded decision-feedback equalizer (DFE). A smart speculative DFE is proposed to reduce additional conversion cycles required for the equalization realization in the ADC. Moreover, DFE functions are efficiently embedded in the capacitive digital-to-analog converter (DAC) references. The prototype ADC with two-tap DFE is implemented in a 130-nm CMOS process and achieves a 5.24-bit peak effective number of bits and 0.59-pJ/conversion-step figure-of-merit (FOM) at a 1.5-GS/s sampling rate while consuming 34.1 mW and occupying a core area of 0.32 mm2. The effectiveness of the embedded DFE in timing margin improvement is verified for 1.5-Gb/s operation over high-loss FR4 channels at a bit error rate (BER) of 10−9.

An FPGA comparative study of high‐level and low‐level combined designs for HEVC intra, inverse quantization, and IDCT/IDST 2D modules

SummaryTwo main design methods are currently widely adopted in dealing with complex signal processing algorithms. The first method is based on low‐level synthesis (LLS), which consists in writing the hardware description languages (HDL) code manually. However, the second method, called high‐level synthesis (HLS), generates the register transfer level (RTL) description automatically starting from a high‐level description language. The challenge in this paper was to study the impact of both design methods on such a complex application as the High Efficiency Video Coding (HEVC) decoder. With this end in view, we analyzed the complexity of the HEVC decoder in a software environment using version 10 of the HEVC test model (HM) reference software to determine which portions tended to get optimized. The combined architecture for the intra prediction (IP) and the inverse quantization and transform (IQ/IT) was then implemented in hardware using HLS and LLS. The findings obtained under the Xilinx Zynq 7045‐based field‐programmable gate array (FPGA) proved that the HLS implementation enabled a gain of about 80% in Look Up Table (LUTs) with an increase of 93% in DSP blocks compared with LLS implementation. Yet only the LLS solution could achieve the real‐time decoding of 4K@26fps instead of the 1080p@24fps by the HLS design.

Orbital angular momentum radiator multiplexing electromagnetic waves in free space.

Orbital angular momentum (OAM) modes of electromagnetic (EM) waves have been extensively studied to obtain more than two independent channels at a single frequency. Thus far, however, multiple radiators have been used to achieve this goal in wireless communications. For the first time, a single radiator was designed to simultaneously transmit three OAM waves in free space at the same frequency. Our design makes use of the radiating resonant modes of a dielectric resonator antenna (DRA). For demonstration, a wireless communication system consisting of a pair of transmitting and receiving OAM DRAs was setup and measured. Three EM waves carrying three different signals were transmitted and received successfully, increasing the system throughput without requiring any complex signal processing algorithms. It confirms that a single radiator can wirelessly transmit more than two independent EM waves at a single frequency by using multi-OAM modes. The work is useful for the future high-speed wireless communication systems.

VibroNet: Recurrent neural networks with multi-target learning for image-based vibration frequency measurement

Information on the vibration characteristics of machinery or civil structures is crucial in identifying or diagnosing potential malfunctions or faults. The use of cameras in vibration frequency measurement enables the acquisition of spatially high-density information of a distant measurement target. Cameras can be used for remote monitoring or as contact-less inspection sensors for machinery or civil structures owing to their low cost, high availability, and ease of installation. However, this requires complex image processing and signal processing algorithms to interpret the vibration frequency from image data. This paper proposes an image- and machine-learning-based method to measure the vibration frequency, in which long short-term memory-recurrent neural networks (LSTM-RNNs) and multi-target learning are used to predict the vibration frequency components directly. The results of the proposed method are compared against the results obtained using an accelerometer and eddy current sensor in the frequency domain. The methodology was applied in forced vibration and free vibration laboratory experiments and real-world structure experiments including a membrane structure and a cable bridge. The experimental results show that the proposed method is robust and accurate. Proposals for future applications and research directions of this methodology and limitations and challenges in real-world implementations are presented.

CCi-MOBILE: Design and Evaluation of a Cochlear Implant and Hearing Aid Research Platform for Speech Scientists and Engineers.

Hearing loss is an increasingly prevalent condition resulting from damage to the inner ear which causes a reduction in speech intelligibility. The societal need for assistive hearing devices has increased exponentially over the past two decades; however, actual human performance with such devices has only seen modest gains relative to advancements in digital signal processing (DSP) technology. A major challenge with clinical hearing technologies is the limited ability to run complex signal processing algorithms requiring high computation power. The CCi-MOBILE platform, developed at UT-Dallas, provides the research community with an open-source, flexible, easy-to-use, software-mediated, powerful computing research interface to conduct a wide variety of listening experiments. The platform supports cochlear implants (CIs) and hearing aids (HAs) independently, as well as bimodal hearing (i.e., a CI in one ear and HA in the contralateral ear). The platform is ideally suited to address hearing research for: both quiet and naturalistic noisy conditions, sound localization, and lateralization. The platform uses commercially available smartphone/tablet devices as portable sound processors and can provide bilateral electric and acoustic stimulation. The hardware components, firmware, and software suite are presented to demonstrate safety to the speech scientist and CI/HA user, highlight user-specificity, and outline various applications of the platform for research.

Architecture and FPGA prototype of cycle stealing DMA array signal processor for ultrasound sector imaging systems

Array Signal Processor (ASP) is widely used in antenna-array beamforming applications, such as RADAR, SONAR, Medical Ultrasound, Multiple-Input-Multiple-Output (MIMO) etc. In this paper, architecture and Field Programmable Gate Array (FPGA) Prototype of a Cycle Steeling Direct Memory Access (DMA) Digital Beamformer (DBF) for Ultrasound Sector Imaging Systems is proposed. The architecture is based on delay and sum and it requires Fine Delay (FD) and Coarse Delay (CD) values to steer and dynamically focus the array, and apodization weights to improve the directivity. To improve the Fine delay accuracy Minimum Mean Square Error (MMSE) interpolation filter is proposed and implemented. To support wide Field of View (FOV) steering, immense delay values are required and real-time computations are hard for high sampling rate systems. Also, the precomputed delay values require huge memory, which causes a significant increase in the ASP area. To solve this problem, a cycle stealing DMA controller based on Quad Serial Peripheral (QSPI) interface to load delay values from external flash without disturbing ASP processing has been proposed and realized. Moreover, for debuggability,the architecture supports custom JTAG debug interface logic and lock-up latch based Design for Testability (DFT) Scan chain for multiple clock domains. The paper also presents the design and implementation of an Ultrasound Sector Imaging System Prototype setup to emulate the ASP. Most of the existing research work in this area supports ultrasound echo acquisition to PC and processing. However, the designed prototype helps researchers to validate computationally complex Ultrasound signal processing algorithms like ASP on FPGA and further processing on PC.

Measuring transducers for optical diagnostic system with multifunctional unitary photovoltaic converters

Modern measuring transducers for optical diagnostic system should perform automatic parameter estimation of optical signal and automatic switching between different energetic and optical sensitivity ranges. Traditional solution of this problem lies in the field of multi-sensory systems, complex optical schemes and complex signal processing algorithms. The paper aims at the development of new measuring transducers for optical diagnostic system on a basis of multifunctional unitary photovoltaic converters built on semiconductors with low-concentration deep dopants that form multiple energy levels for different charge states in the band gap. Relative complexity of physical processes accompanying the recharge of several energy levels of multiply-charged deep dopant makes it possible to realize the multifunctionality of a photoelectric converter albeit simple sensor design.The proposed unitary photovoltaic converters proved to have extended functional characteristics and increased ranges of energetic characteristic (by dozens dB) and spectral sensitivity characteristic with possible shifts of red margin by 2 to 4 μm in the spectral sensitivity range of 1–10 μm. Energetic and spectral sensitivity characteristic ranges could be switched either by measurement signal itself or by additional control inputs. Possible materials for resistive or barrier photovoltaic converter structure are Germanium, Silicon, А3В5 systems and other semiconductors including that compatible with «non-silicon» technologies and structures on sapphire substrate.

Compressed Wideband Spectrum Sensing: Concept, Challenges, and Enablers

Spectrum sensing research has mostly been focusing on narrowband access, and not until recently have researchers started looking at wideband spectrum. Broadly speaking, wideband spectrum sensing approaches can be categorized into two classes: Nyquist-rate and sub-Nyquist-rate sampling approaches. Nyquist-rate approaches have major practical issues that question their suitability for realtime applications; this is mainly because their high-rate sampling requirement calls for complex hardware and signal processing algorithms that incur significant delays. Sub-Nyquist-rate approaches, on the other hand, are more appealing due to their less stringent sampling-rate requirement. Although various concepts have been investigated to ensure sub-Nyquist rates, compressive sampling theory is definitely one concept that has attracted so much interest. This paper explains and illustrates how compressive sampling has been leveraged to improve wideband spectrum sensing by enabling spectrum occupancy recovery with sub-Nyquist sampling rates. The paper also introduces new ideas with great potential for further wideband spectrum sensing enhancements, and identifies key future research challenges and directions that remain to be investigated.

On Smartphone Power Consumption in Acoustic Environment Monitoring Applications

In this paper, we provide a systematic analysis of smartphone power consumption in background audio recording scenarios. We report comprehensive measurement results for several Android smartphone models with diverse hardware specifications, running different types of Android operating systems (OS). Our experimental results show that with respect to background audio sensing applications, the major impact on smartphone power consumption is associated with the core audio recording functionality. On the other hand, moderately complex digital signal processing algorithms (e.g., sound pressure level estimation, acoustic feature extraction, and audio fingerprinting) that operate simultaneously with background audio recording do not significantly affect overall smartphone power consumption or battery life. Power consumption varies significantly from model to model, and we found no obvious correlation between the power consumption of background audio recording scenarios and factors such as the year of release, the OS version, or the model of smartphone processor or system-on-chip (SoC) hardware.

E. Torroja’s bridge: Tailored experimental setup for SHM of a historical bridge with a reduced number of sensors

This paper presents the design of an experimental setup with a reduced number of sensors for the structural health monitoring of the historical bridge of Posadas (Córdoba, Spain), designed by the eminent engineer Eduardo Torroja in 1957. The motivation of this study stems from the need for safeguarding this piece of cultural heritage. In particular, the singularity of this historical construction, a steel–concrete composite typology consisting of a concrete deck slab and inverted bowstring steel trusses, makes continuous in-service condition assessment essential for its maintenance. Nevertheless, the application of existing continuous monitoring systems to such large-scale structures entails considerable investments as well as complex signal processing algorithms. Whereby the optimization of the number of sensors and their location is of the utmost interest. In this line, this work presents the application of an Optimal Sensor Placement (OSP) methodology to tailor an experimental setup for a cost-efficient continuous monitoring of the E. Torroja’s bridge. Due to the fact that most OSP approaches are model-based, it is essential to count on a sufficiently accurate numerical model. To this aim, an extensive vibration-based operational modal analysis is first conducted with a large number of accelerometers. Afterward, a three-dimensional finite element model of the E. Torroja’s bridge is updated on the basis of the experimentally identified dynamic properties with a genetic optimization algorithm. Finally, an optimal sensor placement methodology is utilized to design an experimental setup with a limited number of sensors for long-term monitoring purposes. The results demonstrate that few sensors are needed to accurately assess the main resonant frequencies and mode shapes.

Secure and reliable object tracking in wireless sensor networks

Mobile object tracking is one of the most important applications of Wireless Sensor Networks (WSNs) deployed in battlefields, wildlife or habitat monitoring applications. Existing object tracking algorithms are mostly centralized and based on heavy and complex signal processing algorithms, hence they cannot be applied to resource constrained WSNs directly. Object tracking algorithms of WSNs should be designed by considering energy conservation, bandwidth and communication overheads. Moreover, as practical object tracking applications are typically used in mission-critical applications, security is another important design matter to be considered. In mission-critical applications, sensor nodes are deployed in hostile fields and they can be easily captured by intruders. Such compromised nodes can be used to falsify the collected data and threaten the object tracking reliability. In this paper, we propose a novel secure and reliable object tracking protocol that considers security and object tracking tasks simultaneously. The basic idea behind the proposed protocol is to ensure tracking security using reputation based trust concept for individual sensor nodes. The performance evaluation results show that the proposed protocol allows the network to retain the reliability of tracking data even in the presence of compromised nodes, thereby achieving secure and reliable object tracking process.

Estimation of speech source direction for hearing aid application using smartphone

In our hearing aid research project funded by NIH-NIDCD we utilize smartphone and its features as a powerful platform to implement complex signal processing algorithms which would improve hearing aid applications. Among the required algorithms, is finding the direction of arrival of speech source signals which can improve the performance of hearing aid devices for the users. In this poster presentation, a signal processing algorithm for estimating the speech source direction and its real-time implementation on an Android smartphone are demonstrated. The visual display of source direction on the smartphone panel can be used to align the phone and its two microphones in the right direction of source to enhance the signal to noise ratio and improve the reception of speech signal. A demo unit will be presented showing the real-time operation of the proposed method on an Android smartphone.