Signal Acquisition Method Research Articles

A Review of Research on Side-channel Signal Acquisition for Cryptographic Chip

The side-channel attack includes signal acquisition, signal statistical analysis of the two parts. At home and abroad the current research on attacks mainly focuses on the side-channel statistical analysis method. However, the acquisition method of the leakage signal for the side-channel is lack of attention. Side-channel leakage signal acquisition is the premise to side-channel cryptanalysis. The acquisition of side-channel signal directly affects the quality of the results access of side-channel analysis. This paper talks the analysis of the research status of side-channel: "Attach importance to analysis, lose sight of collection," and summarizes the different existing methods of leak signal`s acquisition of side-channel, introduces traditional signal acquisition method of side-channel, the method of side-channel power signal acquisition, the method of electromagnetic signal acquisition and the method of how to collect side-channel time signal. Finally, this paper summarizes the introductive methods and prospects the acquisition method of side-channel signal.

Bayesian compressive sensing using wavelet based Markov random fields

Compressive sensing (CS) is a novel method for acquisition of signals below the Nyquist sampling rate. Many signals and images are sparse in the wavelet domain. Therefore, in CS reconstruction algorithms, in addition to the sparsity, tree-structure of wavelet coefficients can be used as a knowledge of the signal. Also, the probability of each element of the sparse vector to be negligible depends on the value of its neighbors. So in this paper, we propose a model which exploits both the tree structure and the neighborhood relation of the coefficients, named wavelet-based Markov random fields (WMRF), and we use Bayesian method for signal reconstruction. Variational Bayesian expectation maximization (VBEM) inference procedure is used to acquire posterior distributions of the model. Also, SESOP algorithm, which is based on MPL estimation, is employed to estimate model parameters. Simulation results demonstrate that the reconstruction error of the proposed algorithm is lower than that of the state-of-the-art algorithms.

Mathematical Modelling of Indian Regional Navigation Satellite System Receiver

<p class="p1">At present the armoured fighting vehicles are equipped with either global positioning system (GPS) receivers or integrated inertial navigation system (INS)/GPS navigation systems. During hostile situations, the denial/degradation of the GPS satellite signals may happen. This results in the requirement of an indigenous satellite based navigation system. Indian Space Research Organisation has developed an indigenous Indian regional navigation satellite system (IRNSS), with a seven satellite constellation to provide independent position, navigation and timing services over India and its neighbouring regions. In this paper, the development of IRNSS receiver using MATLAB as per IRNSS signal in space interface control document for standard positioning service is discussed. A method for faster IRNSS signal acquisition in frequency domain and delay locked loop code tracking for the acquired satellite signals are used. Models for navigation message decoding and pseudo range/user position calculations are developed using the algorithms provided in IRNSS ICD.</p>

Design and Implementation of Low-Power Analog-to-Information Conversion for Environmental Information Perception

Because sensing nodes typically have limited power resources, it is extremely important for signals to be acquired with high efficiency and low power consumption, especially in large-scale wireless sensor networks (WSNs) applications. An emerging signal acquisition and compression method called compressed sensing (CS) is a notable alternative to traditional signal processing methods and is a feasible solution for WSNs. In our previous work, we studied several data recovery algorithms and network models that use CS for compressive sampling and signal recovery. The results were validated on large data sets from actual environmental monitoring WSNs. In this paper, we focus on the hardware solution for signal acquisition and processing on separate end nodes. We propose the paradigm of an analog-to-information converter (AIC) based on CS theory. The system model consists of a modulation module, filtering module, and sampling module, and was simulated and analyzed in a MATLAB/Simulink 7.0 environment. Further, the hardware design and implementation of an improved digital AIC system is presented. We also study the performances of three different greedy data recovery algorithms and analyze the system power consumption. The experimental results show that, for normal environmental signals, the new system overcomes the Nyquist limit and exhibits good recovery performance with a low sampling frequency, which is suitable for environmental monitoring based on WSNs.

Methods of measurement signal acquisition from the rotational flow meter for frequency analysis

One of the simplest and commonly used instruments for measuring the flow of homogeneous substances is the rotational flow meter. The main part of such a device is a rotor (vane or screw) rotating at a speed which is the function of the fluid or gas flow rate. A pulse signal with a frequency proportional to the speed of the rotor is obtained at the sensor output. For measurements in dynamic conditions, a variable interval between pulses prohibits the analysis of the measuring signal. Therefore, the authors of the article developed a method involving the determination of measured values on the basis of the last inter-pulse interval preceding the moment designated by the timing generator. For larger changes of the measured value at a predetermined time, the value can be determined by means of extrapolation of the two adjacent interpulse ranges, assuming a linear change in the flow. The proposed methods allow analysis which requires constant spacing between measurements, allowing for an analysis of the dynamics of changes in the test flow, eg. using a Fourier transform. To present the advantages of these methods simulations of flow measurement were carried out with a DRH-1140 rotor flow meter from the company Kobold.

Fast Acquisition Method of GPS Signal Based on FFT Cyclic Correlation

Since the global positioning system began to operate, it has become more and more close to people’s lives, and has been applied to various fields now. In order to track and decode GPS signals, GPS signals need to be captured first. The necessary parameters of the captured GPS signal are immediately transmitted to the tracking process, and then the navigation message of the satellite can be obtained by tracking process. In this paper, the basic contents related to the signal structure of GPS system are briefly described. Then, the traditional GPS signal acquisition method based on time domain correlation method is introduced, and the GPS signal acquisition method based on FFT cyclic correlation method is discussed in this paper. By comparing the simulation results, two kinds of GPS signal acquisition methods are compared with the calculation time according to the method of controlling variables. For the two GPS signal acquisition methods, the variation of time delay error with SNR is simulated in this paper.

Effect of signal acquisition method on the fetal heart rate analysis with phase rectified signal averaging

Phase rectified signal averaging (PRSA) is increasingly used for fetal heart rate (FHR) monitoring, both with traces acquired with external Doppler cardiotocography (D-FHR), and with transabdominal fetal electrocardiography (ta-FHR). However, it is unclear to what extend the acquisition method influences the PRSA analysis, whether results from using one acquisition method are comparable to those based on FHR acquired by the other method, and if not, which should be the preferred method.To address these questions, we applied PRSA analysis to 28 antepartum synchronous recordings of the FHR using simultaneously D-FHR and ta-FHR. The data included late-onset intrauterine growth restricted (IUGR) fetuses (n = 20) and non-IUGR fetuses (n = 8), all of them at gestation ⩾34 weeks. PRSA analysis depends on two parameters intrinsic to the algorithm, T and S. We analyzed the data using parameters that included all values adopted by other researchers previously (derived from a literature search in PubMed and Google Scholar). T and S were adjusted for the difference in acquisition techniques. We found that the correlation between PRSA analysis based on D-FHR and ta-FHR decreased with decreasing values of the PRSA parameters T and S. Therefore, the acquisition technique affects PRSA values for high resolution PRSA (low values of T and S).In conclusion, for low resolution PRSA, the results from both acquisition methods are comparable. Because ta-FHR signals provide beat to beat data and thus capture more subtle differences in the heart rate variation than D-FHR signals (pre-processed by commercial monitors), we assumed that ta-FHR may provide potentially valuable extra information compared to D-FHR. However, no parameter settings or acquisition method seemed to have a diagnostic value for identifying the late-onset IUGR babies in our dataset.

Smart Driver Monitoring: When Signal Processing Meets Human Factors: In the driver's seat

This article provides an interdisciplinary perspective on driver monitoring systems by discussing state-of-the-art signal processing solutions in the context of road safety issues identified in human factors research. Recently, the human factors community has made significant progress in understanding driver behaviors and assessed the efficacy of various interventions for unsafe driving practices. In parallel, the signal processing community has had significant advancements in developing signal acquisition and processing methods for driver monitoring systems. This article aims to bridge these efforts and help initiate new collaborations across the two fields. Toward this end, we discuss how vehicle measures, facial/body expressions, and physiological signals can assist in improving driving safety through adaptive interactions with the driver, based on the driver's state and driving environment. Moreover, by highlighting the current human factors research in road safety, we provide insights for building feedback and mitigation technologies, which can act both in real time and postdrive. We provide insights into areas with great potential to improve driver monitoring systems, which have not yet been extensively studied in the literature, such as affect recognition and data fusion. Finally, a high-level discussion is given on the challenges and possible future directions for driver monitoring systems.

Fast GNSS satellite signal acquisition method based on multiple resamplings

A fast Global Navigation Satellite System (GNSS) satellite signal acquisition method based on resampling is presented. In contrast to traditional approaches, which perform a single-round search with a high data rate, the proposed method introduces a signal acquisition mechanism that uses data resampling. Starting from a resampled data rate slightly above the Nyquist frequency, the proposed method conducts multiple rounds of searches with an increasing sampling rate. After each round of searching, the satellites are sorted according to their relative signal strengths. By removing satellites at the bottom of each sorted list, the search space for satellite acquisition is continuously pruned. If a sufficient number of satellites are not acquired when the original data rate is reached, the method will switch to the weak-signal detection mode and use non-coherent integration for the satellites at the top on the list. The non-coherent integration process continues until either a sufficient number of satellites are acquired or the maximum number of steps is reached. The experimental results show that the proposed method can acquire the same set of satellites as traditional methods but with a considerably lower computational cost. The proposed method was implemented in a software-based GNSS receiver and can also be used in hardware-based receivers.

Impedance Cardiography Filtering Using Non-Negative Least-Mean-Square Algorithm

In general using several signal acquisition methods are applied to get cardio-impedance signal to analyse the cardiac output. The analysis completely based on frequency information obtained after applying frequency selection filters and frequency shaping filters. Here proposing a constructive approach involves a developed Non-Negative LMS (NNLMS) followed by filtering techniques to measure and overcome the limitations of commonly used approaches. The proposed technique performance is analysed by considering different types of noise environments like fundamental one white noise and also sum of sinusoidal noise. The simulation results are useful to measure the performance and accuracy under different noise environments also a comparative analysis is done with the proposed work with existing methods under different performance metrics by the help of quantitative analysis of algorithms. Simulation results are found to be satisfactory in the analysis of cardiac output.

Signal acquisition technology for photoelectric encoder based on FPGA

This paper studies the method of signal acquisition for the incremental photoelectric encoder based on FPGA. According to the specification of the photoelectric encoder, corresponding interface circuit is designed. With FPGA as the main control module, the peripheral circuit can work together harmoniously. The simulation analysis shows that results of frequency subdivision and direction discrimination are correct under the control of FPGA (Field Programmable Gate Array). A ZSP3806 photoelectric encoder is used as the sensor to detect the position of mirror scanning mechanism, and experimental result indicates that the angular displacement of measured value is consistent with theoretical requirements.

Realization of magnetic signal acquisition scheme for banknotes

In order to solve the problem of low signal-to-noise ratio (about 15 dB) in magnetic signal acquisition of banknotes, a new method of magnetic signal acquisition and processing is proposed taking RMB as an example. In this method, weak signal detection is performed to reduce the noise accompanied with the signal. Seven orders of Chebyshev (I) filter and the anti-jamming technology are used in the PCB layout, and grounding modes are introduced to reduce the noise of the amplitude waveform. The proposed method reduce the final output noise by 2/3 and the signal-to-noise ratio is increased to 24 dB. The experimental results show that the magnetic signal of RMB banknotes are acquired by the circuit stability, which provides an important guarantee for the improvements of the anti-counterfeit and discrimination for banknotes performance.

Data and pilot optimised combining method for new composite global navigation satellite system signal acquisition

With the increasing adoption of high bit rate navigation signals, the performance of detection is significantly affected by sign transition. To reduce the correlation loss caused by the sign transition, three optimised channel combining methods, which include the optimised non-coherent channel combining, optimised coherent channel combining and optimised differential channel combining, are proposed in this study. Three corresponding analytical expressions of probabilities of detection for the authors methods are derived. To better evaluate the performance of their methods, three corresponding analytical expressions of probabilities of detection for conventional channel combining methods in the presence of sign transition are also derived. Comparing with conventional channel combining and zero padding methods, although increasing the computational cost, their methods can achieve 2–2.5 and 4–6 dB acquisition sensitivity improvements according to the analytic and simulated results. Moreover, experiments on real data from global positioning system L5 further evaluate the detection performance of their methods.

Self-referenced ultra-broadband transient terahertz spectroscopy using air-photonics.

Terahertz (THz) air-photonics employs nonlinear interactions of ultrashort laser pulses in air to generate and detect THz pulses. As air is virtually non-dispersive, the optical-THz phase matching condition is automatically met, thus permitting the generation and detection of ultra-broadband THz pulses covering the entire THz spectral range without any gaps. Air-photonics naturally offers unique opportunities for ultra-broadband transient THz spectroscopy, yet many critical challenges inherent to this technique must first be resolved. Here, we present explicit guidelines for ultra-broadband transient THz spectroscopy with air-photonics, including a novel method for self-referenced signal acquisition minimizing the phase error, and the numerically-accurate approach to the transient reflectance data analysis.

Re-scaling and adaptive stochastic resonance as a tool for weak GNSS signal acquisition

Weak global navigation satellite system (GNSS) signal acquisition has been a limitation for high sensitivity GPS receivers. This paper modifies the traditional acquisition algorithms and proposes a new weak GNSS signal acquisition method using re-scaling and adaptive stochastic resonance (SR). The adoption of classical SR is limited to low-frequency and periodic signals. Given that GNSS signal frequency is high and that the periodic feature of the GNSS signal is affected by the Doppler frequency shift, classical SR methods cannot be directly used to acquire GNSS signals. Therefore, the re-scaling technique is used in our study to expand its usage to high-frequency signals and adaptive control technique is used to gradually determine the Doppler shift effect in GNSS signal buried in strong noises. The effectiveness of our proposed method was verified by the simulations on GPS L1 signals. The simulation results indicate that the new algorithm based on SR can reach – 181 dBW sensitivity with a very short data length of 1 ms.

Discrete Kalman Filter based Sensor Fusion for Robust Accessibility Interfaces

Human-machine interfaces have evolved, benefiting from the growing access to devices with superior, embedded signal-processing capabilities, as well as through new sensors that allow the estimation of movements and gestures, resulting in increasingly intuitive interfaces. In this context, sensor fusion for the estimation of the spatial orientation of body segments allows to achieve more robust solutions, overcoming specific disadvantages derived from the use of isolated sensors, such as the sensitivity of magnetic-field sensors to external influences, when used in uncontrolled environments. In this work, a method for the combination of image-processing data and angular-velocity registers from a 3D MEMS gyroscope, through a Discrete-time Kalman Filter, is proposed and deployed as an alternate user interface for mobile devices, in which an on-screen pointer is controlled with head movements. Results concerning general performance of the method are presented, as well as a comparative analysis, under a dedicated test application, with results from a previous version of this system, in which the relative-orientation information was acquired directly from MEMS sensors (3D magnetometer-accelerometer). These results show an improved response for this new version of the pointer, both in terms of precision and response time, while keeping many of the benefits that were highlighted for its predecessor, giving place to a complementary method for signal acquisition that can be used as an alternative-input device, as well as for accessibility solutions.

Laser interference signal acquisition for Fourier transform spectrometer

The laser interference signal provides effective control signal for the reliable operation of atmospheric sounder. Main components of interferometer are presented by analyzing the principle of swinging interferometer in this paper. In order to acquire the laser interference signal, it is necessary to design a method of signal acquisition for the interferometer with analyzing the noise performance of the preamplifier. By means of an interference experiment of He–Ne laser, the sinusoidal signal is obtained, the frequency of which varies with change of angular velocity of moving mirrors. The experimental results indicate that the principle of swing interferometer is feasible, and that the method of interference signal acquisition is correct.

A two-step MF signal acquisition method for wireless underground sensor networks

Signal acquisition plays a critical role on the bit error rate (BER) of a direct sequence spread spectrum (DS/SS) communication system working with low frequency. In this paper, we propose a new signal acquisition method. The acquisition process includes coarse matched filter (MF) location in the first stage and an accurate MF acquisition as a verification mode for the second stage. The performance metrics, including mean acquisition time (MAT) and power consumption, are accuracy. The results indicate that when the signal-to-noise ratio (SNR) keeping consistent, the MAT of the proposed method is less than the original one. When the SNR is around -5dB, the system mismatch rate is about 5:6 x 10-4, which takes only one percent of those achieved in the original acquisition algorithms. The two-step MF acquisition method is stable except its power consumption being a little higher than the original method.

An Improved Method for Fast Acquisition of Broadband and High-Speed Hopping Signals

An Improved Method for Fast Acquisition of Broadband and High-Speed Hopping Signals

Stability control simulation of temperature sensor network with temperature difference fluctuation

With the large temperature differences, the temperature sensor network node will have fluctuations in the signal acquisition, resulting in the fast single random node energy consumption and the network instability. In this paper, the temperature signal acquisition method of the network is proposed based on sink node path selection algorithm; the based on temperature sensing network stability BTS protocol and transfer Markov chain model of the network is constructed. In the fluctuation environment, when the network node makes the abnormal energy variation, the deviation compensation is taken for the node; the new network communication path is stably ordered; and the temperature information acquisition is completed. The simulation results show that this new method has better performance in the temperature sensing and signal acquisition, and it can realise the non-uniform heat transfer. The stability communication is realised.