Digital Detection Research Articles

Digital signal detection and recognition in the communication field combining DAEN and CNN

In communication, the detection and recognition of digital signals have always faced problems such as low adaptability and high misclassification rate. To address these issues, this study innovatively fused the deep auto-encoder network with convolutional neural networks to construct a novel digital signal detection and recognition model. Firstly, this study utilized the powerful feature extraction capabilities of the deep auto-encoder network to extract key feature information from massive amounts of data. Then these features were combined with convolutional neural networks to construct a detection and recognition model. These results confirmed that the constructed digital signal detection and recognition model had values of 93.75% and 94.18% in data detection recognition rate and average classification accuracy, respectively. Meanwhile, this model also performed well in terms of data processing accuracy and recall. In the comparison of data processing, the accuracy and recall rates were 93.59% and 94.67%, respectively, and the performance of data detection and recognition was better than that of the comparison methods. This indicates that the constructed digital signal detection and recognition model can significantly improve the reliability and robustness of signal detection and recognition. This paper brings new breakthroughs to the development of digital signal detection and recognition technology in communication.

Non-interference detection of digital signals in transmission line utilizing quantum sensor of nitrogen-vacancy centers

Digital signals play an extremely important role in the integration and multi-functionality of industrial instrumentation. With the expansion of industrial application scenarios, non-interference detection of digital signals in certain extreme environments has become the need of the hour. This paper demonstrates a method for non-interference Detection of transmission line digital signals based on nitrogen-vacancy (NV) centers in diamond. The optical readability and the sensitivity to magnetic fields of the NV centers are utilized to characterize the current-induced weak magnetic field signals by fluorescence signals in a confined space. By combining quantum sensing technology, quantum imaging technology and electromagnetic induction technology through NV centers, it is able to realize high sensitivity and high precision multi-point measurement and dynamic monitoring of electrical signals. The temporal resolution of the digital signal was evaluated by regulating the duration of the input current in the transmission line, and the lowest transmission current in a single transmission line and two transmission lines in a 1.2 mm × 1.2 mm imaging field of view was explored. The experimental results show that the time resolution of the detected digital signals is up to 30 μs. This research highlights the potential value of NV centers in digital signal processing and provides new research directions for detecting digital signals in extreme environments.

4FSK signal processing based on adaptive tristable stochastic resonance under levy noise

Aiming at the problem of low quality of coherent demodulation transmission signal of digital signal in the background of Levy noise, this paper proposes a new method of 4FSK signal reception based on adaptive tristable stochastic resonance (SR) system. The bit error rate (BER) of output signals of adaptive tristable SR system model and the traditional modulation model are compared by simulation. The numerical simulation results show that compared with the traditional model, the output BER of the 4FSK signal after demodulation of the adaptive tristable SR system model is reduced by 4% compared with the traditional model. The time domain image of 4FSK signal is clearer, the burrs are significantly reduced and the spectral amplitude of 4FSK signal is greatly improved. The success of this experiment suggests a strong promise of SR systems for digital signal detection in impact noise.

Focus on test, measurement, and analytical equipment

Focus on test, measurement, and analytical equipment

Comparative study of classifiers to mitigate intersymbol interference in diffuse indoor optical wireless communication links

The maximum data rate that can be achieved in diffuse indoor optical wireless communication (OWC) is limited due to the effect of intersymbol interference (ISI). The adverse effect of ISI on the system performance can be minimised using a channel equaliser at the receiver. In this study, digital signal detection is formulated as a classification problem and hence a classifier is adopted at the receiver. The bit error performance of classifiers with non-linear decision boundary including a multilayer perceptron (MLP), a support vector machine (SVM), the radial basis function (RBF), and the Bayesian classifier is studied along with traditional equaliser and reported here. The MLP offers the best performance; however there is trade-off between the performance and complexity especially at highly diffuse channel.

The Application Technique of Signal detecting for Optic Fiber Temperature Sensor

A temperature sensor based on polarization non–reciprocity(PNR)in fiber-optic Sagnac interferometer(PSI)can measure the temperature of one point in high precision. The phasic subtraction of two light beams was shifted while temperature field around the probe changed. Analyzing the temperature measuring theory of Sagnac fiber optic temperature sensor, a linear output model Was established. The all digital signal detection was based onsquare–wave modulation and demodulation. An all digital signal detecting system using C8051 F060 as its COre Was completed. The experimental data achieved by temperature experiments agree with theory well. The input and output of system achieve a linearity of 10°C. Discussion shows that this kind of temperature sensor can reach high precision.

Assessment of the potential of a new generation of surface nuclear magnetic resonance instruments

ABSTRACTThe technique of magnetic resonance sounding (MRS) has shown several improvements in data processing, inversion and interpretation during the last years. Along with these improvements, detailed innovations on instrumentation have been demanded to support their use. Latest developments in surface nuclear magnetic resonance (NMR) instrumentation promise to fulfil these hardware requirements such as decreased dead time, improved digital signal detection, multi‐channel capabilities and improved reference techniques with the second generation surface NMR instruments.In this paper, we compare data from two generations of instruments and assess the impact of the improvements on practical issues, i.e., the increased accuracy of data due to shorter dead times and new noise reduction approaches and the feasibility for efficient 2D measuring schemes. Well‐known and documented test sites and synthetic considerations are used to evaluate these developments.First, the relaxation signals of different devices using the same loop match each other. The inversion results coincide within the range of data errors. Decay time estimation appears to be more stable for the new generation instrument.Second, the potential of shorter effective dead times (considering a relaxation of the protons during the pulse) is investigated using statistical analysis of synthetic data sets with different decay times and noise levels. The additionally measured data at early times significantly improve the scope and accuracy of the determined parameters initial amplitude and time and thus extend the range of formations to be characterized. A field example comparing an effective dead time of 18 ms and 45 ms is presented.Two different reference techniques were successfully applied for noise cancellation at the very noisy test site Nauen. We observed an equivalent signal improvement using the software‐based and hardware‐based technique. However, software noise cancellation approaches are easily adaptable and extendable.Finally, considerations are given how to efficiently carry out 2D surveys using multi‐channel instruments. A 2D field data set using the GMR demonstrates that 2D surveys can already be realized in moderate measuring times.The new generation of instruments provides comparable results and improved capabilities that will enable surface NMR measurements to be applied in a wider range of applications.

Focus on test and measurement

Focus on test and measurement

Digitalization of highly precise fluxgate magnetometers

This paper describes the theory behind all three known ways of digitalizing the fluxgate magnetometers: analogue magnetometers with digitalized output using high resolution ADC, application of the delta–sigma modulation to the sensor feedback loop and fully digital signal detection. At present time the Δ–Σ ADCs are mostly used for the digitalization of the highly precise fluxgate magnetometers. The relevant part of the paper demonstrates some pitfalls of their application studied during the design of the magnetometer for the new Czech scientific satellite MIMOSA. The part discussing the application of the Δ–Σ modulation to the sensor feedback loop theoretically derives the main advantage of this method—increasing of the modulation order and shows its real potential compared to the analog magnetometer with consequential digitalization. The comparison is realized on the modular magnetometer allowing configurations with modulator inside and outside the feedback loop. The last principle is demonstrated on the project of the fully digital fluxgate magnetometer based on the digital signal processor (DSP). The results of the presented projects are compared with recently published competitive projects. The main objective of the paper is then to discuss the potential, real advantages and weakness of each concept and to examine their convenience for future implementations.

Recent advances in high-speed underwater acoustic communications

In recent years, underwater acoustic (UWA) communications have received much attention as their applications have begun to shift from military toward commercial. Digital communications through UWA channels differ substantially from those in other media, such as radio channels, due to severe signal degradations caused by multipath propagation and high temporal and spatial variability of the channel conditions. The design of underwater acoustic communication systems has until recently relied on the use of noncoherent modulation techniques. However, to achieve high data rates on the severely band-limited UWA channels, bandwidth-efficient modulation techniques must be considered, together with array processing for exploitation of spatial multipath diversity. The new generation of underwater communication systems, employing phase-coherent modulation techniques, has a potential of achieving at least an order of magnitude increase in data throughput. The emerging communication scenario in which the modern underwater acoustic systems mill operate is that of an underwater network consisting of stationary and mobile nodes. Current research focuses on the development of efficient signal processing algorithms, multiuser communications in the presence of interference, and design of efficient modulation and coding schemes. This paper presents a review of recent results and research problems in high-speed underwater acoustic communications, focusing on the bandwidth-efficient phase-coherent methods. Experimental results are included to illustrate the state-of-the-art coherent detection of digital signals transmitted at 30 and 40 kb/s through a rapidly varying one-mile shallow water channel.

The choice of signal processing parameters in high density digital recording channels

For a high density NRZ recording channel the influence of head to tape spacing fluctuations and channel noise on digital signal detection were considered. It was determined that optimum levels of decision taking in the presence of additive noise and head to tape parameter changes coincide. Relationships which determine the signal to noise ratio change by integrating equalization or recorded signal waveform pre-emphasis were reviewed.

Detecting the audible alarm of residual smoke detectors and its applications

A novel digital signal detection technology has been implemented in low-power, low-cost large-scale CMOS integrated circuit technology. Standby power for this spatial dual-diversity two channel receiver is less than 10 microamperes at three volts, permitting the receiver to be battery-powered for over one year by a set of standard alkaline flashlight batteries. This signal processing technology is downward compatible with most of the tens of millions of smoke detectors already installed and operational in residences worldwide, and upward compatible with battery powered smoke detectors now being marketed and sold throughout the US and the world.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Adaptive schemes for noise filtering and edge detection by use of local statistics

Some adaptive schemes for noise filterings and edge detection of digital signals are developed. They are bases on the minimum-mean-square-error estimate of the information-bearing signal corrupted by additive noise. The estimate is computed using the local statistics of the input signal and noise. The output is fed back to the input, and the difference between the input and the output is used as the noise estimator. The local statistics of signal and noise are computed through a moving signal window and a moving noise window, which are over the input signal and the noise estimator, respectively. These schemes change their performance according to the local signal-to-noise ratio adaptively. Two kinds of adaptive filtering algorithms and an edge detection algorithm are considered. Their performance in the presence of noise is evaluated and compared to the performance of some other methods. Simulation results on one-dimensional signals and real images are presented. >

Optical detectors: Three contenders: Depending on the application, the photoeonductor, p-i-n diode, or avalanche photodiode may prove the best choice

Although there are many types of photodetectors, only three are commonly considered for the direct detection of digital signals in optical communications: the photoconductor, the p-i-n diode, and the avalanche photodiode. The advantages and disadvantages of each type are discussed. The problems of speed, security, and noise are stressed.

Detection of digital signals transmitted over a known time-varying channel

A technique has recently been developed whereby it is possible, without undue complexity and without any adaptive linear prefiltering, to achieve near-maximum-likelihood detection of a sampled digital signal, where there is intersymbol interference extending over several samples of the signal. It is, however, important here that the channel impulse response does not undergo large changes with time, since, when it does, a considerable increase in the complexity of the system may be required to maintain correct operation. The paper describes a development of the detection process whereby correct operation is achieved with a relatively simple system, even when the channel introduces severe frequency-selective fading of the type sometimes experienced over HF radio links. Results of computer-simulation tests are presented, showing the tolerance of a synchronous serial data-transmission system to additive white Gaussian noise, when a 4-point quadrature amplitude modulated signal is transmitted at 2400 bit/s over a model of an HF radio link, with two independent Rayleigh fading sky waves and frequency spreads of 0.5, 1 and 2Hz, and when the novel detection process is used at the receiver. Correct estimation of the channel is assumed throughout.

MLD and mse algorithms for adaptive detection of digital signals in the presence of interchannel interference

Adaptive mean-square error (mse) and maximum-likelihood detection (MLD) algorithms for a dual-channel digital communication system in the presence of interchannel interference and white Gaussian noise are presented. The mse algorithm forms estimates of the transmitted symbols from a linear combination of received symbols using weights that minimize the mse between transmitted and estimated symbols. The nonlinear MLD algorithm minimizes the probability of symbol error by maximizing the probability of the received signal samples on the two channels over ail possible transmitted symbol pairs. The probability of error is derived for the two algorithms when quadrature phase-shift keying (QPSK) is used as a modulation technique, and is compared with that of a dual-channel QPSK system having no compensation for the crosstalk.

On optimal quantum receivers for digital signal detection

Several problems are formulated concerning M-ary quantum signal detection. Two of these problems admit the direct application of general optimization theory for deriving the mathematical specification of the optimal receiver. The optimality conditions are stated without proofs, which will be presented elsewhere. Certain simple applications of our conditions are described.

On the Optimum Detection of Digital Signals in the Presence of White Gaussian Noise-A Geometric Interpretation and a Study of Three Basic Data Transmission Systems

This paper considers the problem of optimally detecting digital waveforms in the presence of additive white Gaussian noise. A technique for representing the transmitted signals and the additive noise which leads to a geometric interpretation of the detection problem is presented on a tutorial level. Subsequently, this technique is used to derive the optimum detector for each of three basic data transmission systems: m-level Phase Shift Keyed, m-level Amplitude Shift Keyed and m-level Frequency Shift Keyed. Corresponding probability of error curves are derived, compared and discussed with reasonable detail.