Adaptive Bistable Stochastic Resonance Based Weak Signal Reception in Additive Laplacian Noise

Weak signal reception is a very important and challenging problem for communication systems especially in the presence of non-Gaussian noise,and in which case the performance of optimal linear correlated receiver degrades dramatically.Aiming at this,a novel uncorrelated reception scheme based on adaptive bistable stochastic resonance(ABSR)for a weak signal in additive Laplacian noise is investigated.By analyzing the key issue that the quantitative cooperative resonance matching relationship between the characteristics of the noisy signal and the nonlinear bistable system,an analytical expression of the bistable system parameters is derived.On this basis,by means of bistable system parameters self-adaptive adjustment,the counterintuitive stochastic resonance(SR)phenomenon can be easily generated at which the random noise is changed into a benefit to assist signal transmission.Finally,it is demonstrated that approximately 8dB bit error ratio(BER)performance improvement for the ABSR-based uncorrelated receiver when compared with the traditional uncorrelated receiver at low signal to noise ratio(SNR)conditions varying from-30dB to-5dB.

Data Wipe-Off Technique for Tracking Weak GPS Signals

In this paper,the data wipe-off(DWO)algorithm is incorporated into the vector tracking loop of the Global Positioning System(GPS)receiver for improving signal tracking performance.The navigation data,which contains information that is necessary to perform navigation computations,are binary phase-shift keying(BPSK)modulated onto the GPS carrier phase with the bit duration of 20 ms(i.e.,50 bits per second).To continuously track the satellite’s signal in weak signal environment,the DWO algorithm on the basis of pre-detection method is adopted to detect data bit sign reversal every 20 ms.Tracking accuracy of a weak GPS signal is decreased by possible data bit sign reversal every 20 ms to the predetection integration time(PIT)or integration interval.To achieve better tracking performance in weak signal environment,the coherent integration interval can be extended.However,increase of the integration interval lead to decrease of the tracking accuracy by possible data bit sign reversal every 20 ms to the integration interval.When the integration interval of the correlator is extended over 20 ms in low C/No levels,the navigation DWO algorithm can be employed to avoid energy loss due to bit transitions.The method presented in this paper has an advantage to continuously estimate the navigation data bit and achieve improved tracking performance.Evaluation of the tracking performance based on the various integration intervals for the vector tracking loop of a GPS receiver will be presented.

Weak signal detection method based on novel composite multistable stochastic resonance

The weak signal detection method based on stochastic resonance is usually used to extract and identify the weak characteristic signal submerged in strong noise by using the noise energy transfer mechanism.We propose a novel composite multistable stochastic-resonance(NCMSR)model combining the Gaussian potential model and an improved bistable model.Compared with the traditional multistable stochastic resonance method,all the parameters in the novel model have no symmetry,the output signal-to-noise ratio can be optimized and the output amplitude can be improved by adjusting the system parameters.The model retains the advantages of continuity and constraint of the Gaussian potential model and the advantages of the improved bistable model without output saturation,the NCMSR model has a higher utilization of noise.Taking the output signal-to-noise ratio as the index,weak periodic signal is detected based on the NCMSR model in Gaussian noise andαnoise environment respectively,and the detection effect is good.The application of NCMSR to the actual detection of bearing fault signals can realize the fault detection of bearing inner race and outer race.The outstanding advantages of this method in weak signal detection are verified,which provides a theoretical basis for industrial practical applications.

Structural Design of High-precision Positioning System in Weak Signal Environment Based on UWB and IMU Fusion

Aiming at the problem that indoor positioning technology based on wireless ultra-wideband pulse technology is susceptible to non-line-of-sight effects and multipath effects in confined spaces and weak signal environments,a high-precision positioning system based on UWB and IMU in a confined environment is designed.The STM32 chip is used as the main control,and the data information of IMU and UWB is fused by the fusion filtering algorithm.Finally,the real-time information of the positioning is transmitted to the host computer and the cloud.The experimental results show that the positioning accuracy and positioning stability of the system have been improved in the non-line-of-sight case of closed environment.The system has high positioning accuracy in a closed environment,and the components used are consumer-grade,which has strong practicability.

Weak GPS L1 Signal Acquisition Based on BPDC

It is difficult to achieve accurate acquisition of weak global positioning system( GPS) signals with traditional methods. A weak signal acquisition strategy based on block processing and differentially coherent( BPDC) is put forward after analyzing the advantages and disadvantages of coherent and non-coherent integration algorithms. Code phase parallel search of the pre-coherent integration is conducted by using fast Fourier transform( FFT),and the results are then differential coherent processed and block processed. BPDC method reduces computation cost compared with coherent and noncoherent( CNC) algorithm. The performance of the two algorithms is also compared based on simulated signals. The result shows that the noise suppression effect of BPDC algorithms is superior to that of traditional CNC algorithm,and the superiority of BPDC is more apparent with the reduction of carrier to noise ratio( CNR). In the case that the pre-coherent integration length is 4 ms and CNR is reduced to 28 dB-Hz,CNC algorithm cannot yet acquire signal correctly while BPDC has well acquisition performance. Therefore,for weak GPS signal acquisition,BPDC algorithm can acquire the signal with lower CNR and has better acquisition property.

Two-step compressed acquisition method for Doppler frequency and Doppler rate estimation in high-dynamic and weak signal environments

To acquire global navigation satellite system(GNSS)signals means four-dimension acquisition of bit transition,Doppler frequency,Doppler rate,and code phase in high-dynamic and weak signal environments,which needs a high computational cost.To reduce the computations,this paper proposes a twostep compressed acquisition method(TCAM)for the post-correlation signal parameters estimation.Compared with the fast Fourier transform(FFT)based methods,TCAM uses fewer frequency search points.In this way,the proposed method reduces complex multiplications,and uses real multiplications instead of improving the accuracy of the Doppler frequency and the Doppler rate.Furthermore,the differential process between two adjacent milliseconds is used for avoiding the impact of bit transition and the Doppler frequency on the integration peak.The results demonstrate that due to the reduction of complex multiplications,the computational cost of TCAM is lower than that of the FFT based method under the same signal to noise ratio(SNR).

Wigner-Matrix-Based Normality Test and Application to Weak Signal Detection in SISO/SIMO Systems

Based on the asymptotic spectral distribution of Wigner matrices,a new normality test method is proposed via reforming the white noise sequence.In this work,the asymptotic cumulative distribution function(CDF)of eigenvalues of the Wigner matrix is deduced.A numerical Kullback-Leibler divergence of the empirical spectral CDF based on test samples from the deduced asymptotic CDF is established,which is treated as the test statistic.For validating the superiority of our proposed normality test,we apply the method to weak 8PSK signal detection in the single-input single-output(SISO) system and the single-input multiple-output(SIMO)system.By comparing with other common normality tests and the existing signal detection methods,simulation results show that the proposed method is superior and robust.

Continuous Tracking of GPS Signals with Data Wipe-Off Method

The decentralized pre-filter based vector tracking loop(VTL)configuration with data wipe-off(DWO)method of the Global Positioning System(GPS)receiver is proposed for performance enhancement.It is a challenging task to continuously track the satellites’signals in weak signal environment for the GPS receiver.VTL is a very attractive technique as it can provide tracking capability in signal-challenged environments.In the VTL,each channel will not form a loop independently.On the contrary,the signals in the channels of VTL are shared with each other;the navigation processor in turn predicts the code phases.Thus,the receiver can successfully track signals even the signal strength from individual satellite is weak.The tracking loop based on the pre-filter provides more flexible adjustment to specific environments to reduce noise interference.Therefore,even if the signals from some satellites are very weak the receiver can track them from the navigation results based on the other satellites.The navigation data,which contains information necessary to perform navigation computations,are binary phase-shift keying(BPSK)modulated onto the GPS carrier phase with the bit duration of 20 ms(i.e.,50 bits per second)for the GPS L1 C/A signals.The coherent integration interval can be extended for improved tracking performance in signal-challenged environment.However,tracking accuracy is decreased by possible data bit sign reversal.The DWO algorithm can be employed to remove the data bit in I and Q correlation values so as to avoid energy loss due to bit transitions when the integration interval of the correlator is extended over 20 ms under the low carrier-to-noise ratio(C/No)environments.The proposed method has an advantage to provide continuous tracking of signals and obtain improved navigation performance.Performance evaluation of the tracking capability as well as positioning accuracy will be presented.

New low noise interface circuit for detecting weak current of micro-sensors

A new low noise interface circuit for detecting weak current of micro-sensors is designed.By using the transimpedance amplifier to substitute the charge amplifier,the closed-loop circuit can avoid the phase error of the charge amplifier.Therefore,the phase compensation devices will be cancelled,because there is no phase transformation through the transimpedance amplifier.As well as,by using CCCII devices to implement the high value feedback resistor of the impedance amplifier,the noise of the I-V transformation devices is reduced,comparing with the passive resistor.The floating resistor is easy to be integrated into chips,making the integration of the interface circuit of the intelligent sensors increase.Through the simulation,the phase error of the charge amplifier is almost 9°at 2 kHz and it changes with the working frequency of the micro-sensors making the phase compensation not easy.The value of the floating resistor is 250 kΩ where the bias current is 50 μA.The noise of the active resistor is 0.037 fV2/Hz,comparing with the noise of the passive resistor,which is 4.14 fV2/Hz.

Harmonicity Spectrum

Perceiving harmonic information (especially weak harmonic information) in time series has important scientific and engineering significance. Fourier spectrum and time-frequency spectrum are commonly used tools for perceiving harmonic information, but they are often ineffective in perceiving weak harmonic signals because they are based on energy or amplitude analysis. Based on the theory of Normal time-frequency transform (NTFT) and complex correlation coefficient, a new type of spectrum, the Harmonicity Spectrum (HS), is developed to perceive harmonic information in time series. HS is based on the degree of signal harmony rather than energy or amplitude analysis, and can therefore perceive very weak harmonic information in signals sensitively. Simulation examples show that HS can detect harmonic information that cannot be detected by Fourier spectrum or time-frequency spectrum. Acoustic data analysis shows that HS has better resolution than traditional LOFAR spectrum.

A Point-of-Care Test System for Biochemical Blood Analysis Based on ADUC824

A point-of-care test system has been studied in this paper.It was used to determine substances in blood such as Hemoglobin (HB),Aspartate Aminotransferase (AST),Creatine Kinase (CK) and so on.Based on the principle of amperometric determination,the research on detecting weak current signals was carried on.At the same time as to the weak signals (nA level),magnifying,sampling and processing the signals were also studied.Controlled by ADUC824 and assisted by other units, every substance could be determined automatically and rapidly integrated with the corresponding biosensor.In the experiment, the minimum detectable current of the instrument (YT2005-1) is 0.2 nA.With regard to the 1 nA which the experiment demanded,it could be up to the mustard.And the system can provide results in 180 s with a long term stability.

Asymmetric stochastic resonance under non-Gaussian colored noise and time-delayed feedback

Based on adiabatic approximation theory,in this paper we study the asymmetric stochastic resonance system with time-delayed feedback driven by non-Gaussian colored noise.The analytical expressions of the mean first-passage time(MFPT)and output signal-to-noise ratio(SNR)are derived by using a path integral approach,unified colored-noise approximation(UCNA),and small delay approximation.The effects of time-delayed feedback and non-Gaussian colored noise on the output SNR are analyzed.Moreover,three types of asymmetric potential function characteristics are thoroughly discussed.And they are well-depth asymmetry(DASR),well-width asymmetry(WASR),and synchronous action of welldepth and well-width asymmetry(DWASR),respectively.The conclusion of this paper is that the time-delayed feedback can suppress SR,however,the non-Gaussian noise deviation parameter has the opposite effect.Moreover,the correlation time plays a significant role in improving SNR,and the SNR of asymmetric stochastic resonance is higher than that of symmetric stochastic resonance.Our experiments demonstrate that the appropriate parameters can make the asymmetric stochastic resonance perform better to detect weak signals than the symmetric stochastic resonance,in which no matter whether these signals have low frequency or high frequency,accompanied by strong or weak noise.

Research and application of stochastic resonance in quad-stable potential system

To solve the problem of low weak signal enhancement performance in the quad-stable system,a new quad-stable potential stochastic resonance(QSR)is proposed.Firstly,under the condition of adiabatic approximation theory,the stationary probability distribution(SPD),the mean first passage time(MFPT),the work(W),and the power spectrum amplification factor(SAF)are derived,and the impacts of system parameters on them are also extensively analyzed.Secondly,numerical simulations are performed to compare QSR with the classical Tri-stable stochastic resonance(CTSR)by using the genetic algorithm(GA)and the fourth-order Runge–Kutta algorithm.It shows that the signal-to-noise ratio(SNR)and mean signal-to-noise increase(MSNRI)of QSR are higher than CTSR,which indicates that QSR has superior noise immunity than CTSR.Finally,the two systems are applied in the detection of real bearing faults.The experimental results show that QSR is superior to CTSR,which provides a better theoretical significance and reference value for practical engineering application.

Characteristics of piecewise linear symmetric tri-stable stochastic resonance system and its application under different noises

Weak signal detection has become an important means of mechanical fault detections. In order to solve the problem of poor signal detection performance in classical tristable stochastic resonance system(CTSR), a novel unsaturated piecewise linear symmetric tristable stochastic resonance system(PLSTSR) is proposed. Firstly, by making the analysis and comparison of the output and input relationship between CTSR and PLSTSR, it is verified that the PLSTSR has good unsaturation characteristics. Then, on the basis of adiabatic approximation theory, the Kramers escape rate, the mean first-passage time(MFPT), and output signal-to-noise ratio(SNR) of PLSTSR are deduced, and the influences of different system parameters on them are studied. Combined with the adaptive genetic algorithm to synergistically optimize the system parameters, the PLSTSR and CTSR are used for numerically simulating the verification and detection of low-frequency, high-frequency,and multi-frequency signals. And the results show that the SNR and output amplitude of the PLSTSR are greatly improved compared with those of the CTSR, and the detection effect is better. Finally, the PLSTSR and CTSR are applied to the bearing fault detection under Gaussian white noise and Levy noise. The experimental results also show that the PLSTSR can obtain larger output amplitude and SNR, and can detect fault signals more easily, which proves that the system has better performance than other systems in bearing fault detection, and has good theoretical significance and practical value.

A new frequency domain search strategy in high sensitivity GPS signal acquisition circuit designing

The contradiction between the sensitivity and the frequency domain searching speed of GPS signal acquisition circuit has been discussed for a long time. The signal integration operation which enhances the sensitivity of the system also makes the frequency slots narrower, which affects the speed of the system. In this research a high sensitivity GPS signal acquisition circuit is implemented with a new frequency domain search strategy. The new strategy combines DDS sweep strategy with cyclic shifting sweep strategy which makes the TTFF (time to first fix) reduced evidently. The extra hardware resource cost of the new strategy is acceptable. The speed advantage of the new frequency domain search strategy has been verified by hardware comparison tests.

Low-Noise Amplification, Detection and Spectroscopy of Ultra-Cold Systems in RF Cavities

The design and development of a cryogenic Ultra-Low-Noise Signal Amplification (ULNA) and detection system for spectroscopy of ultra-cold systems are reported here for the operation in the 0.5 - 4 GHz spectrum of frequencies (the “L” and “S” microwave bands). The design is suitable for weak RF signal detection and spectroscopy from ultra-cold systems confined in cryogenic RF cavities, as entailed in a number of physics, physical chemistry and analytical chemistry applications, such as NMR/NQR/EPR and microwave spectroscopy, Paul traps, Bose-Einstein Condensates (BEC’s) and cavity Quantum Electrodynamics (cQED). Using a generic Low-Noise Amplifier (LNA) architecture for a GaAs enhancement mode High-Electron Mobility FET device, our design has especially been devised for scientific applications where ultra-low-noise amplification systems are sought to amplify and detect weak RF signals under various conditions and environments, including cryogenic temperatures, with the least possible noise susceptibility. The amplifier offers a 16 dB gain and a 0.8 dB noise figure at 2.5 GHz, while operating at room temperature, which can improve significantly at low temperatures. Both dc and RF outputs are provided by the amplifier to integrate it in a closed-loop or continuous-wave spectroscopy system or connect it to a variety of instruments, a factor which is lacking in commercial LNA devices. Following the amplification stage, the RF signal detection is carried out with the help of a post-amplifier and detection system based upon a set of Zero-Bias Schottky Barrier Diodes (ZBD’s) and a high-precision ultra-low noise jFET operational amplifier. The scheme offers unique benefits of sensitive detection and very-low noise amplification for measuring extremely weak on-resonance signals with substantial low- noise response and excellent stability while eliminating complicated and expensive heterodyne schemes. The LNA stage is fully capable to be a part of low-temperature experiments while being operated in cryogenic conditions down to about 500 mK.

Periodic-phase-diagram similarity method for weak signal detection

The periodic-phase-diagram similarity method is proposed to identify the frequency of weak harmonic signals.The key technology is to find a set of optimal coefficients for Duffing system,which leads to the periodic motion under the influence of weak signal and strong noise.Introducing the phase diagram similarity,the influences of strong noise on the similarity of periodic phase diagram are discussed.The principle of highest similarity of periodic phase diagram with the same frequency is detected by discussing the persistence of similarity of periodic motion phase diagram under the strong noise and the periodic-phase-diagram similarity method is constructed.The weak signals of early fault and strong noise are input into Duffing system to obtain the identified system.The stochastic subharmonic Melnikov method is extended to obtain the conditions of the optimal coefficients for the identified system.Based on the results,the constructed frequency conversion harmonic weak signals are considered to form a datum periodic system.With the change of frequency in the datum periodic system,the phase diagram similarity of the two constructed systems can be calculated.Based on the periodic-phase-diagram similarity method,the frequency of weak harmonic signals can be identified by the principle of highest similarity of periodic phase diagram with the same frequency.The results of numerical simulation and the early fault diagnosis results of actual bearings verify the feasibility of the periodic-phase-diagram similarity method.The accuracy of the detection effect is 97%,and the minimum signal-to-noise ratio is−80.71 dB.

Preliminary Application of Scale Transformation Stochastic Resonance in Dual-Sequence Frequency Hopping System

Aiming at the detection failure of strong noise interference in the dual channel of the dual-sequence frequency hopping(DSFH),the scale transformation stochastic resonance(STSR)is applied for the first time,and the output signal to noise ratio(SNR)is raised effectively,at the same time,the symbol reception is completed for DSFH at low input SNR.Firstly,the radio frequency(RF)and intermediate frequency(IF)signals are analyzed based on the super-heterodyne reception of DSFH;secondly,the equations of probability density function(PDF),output power spectrum and SNR of the STSR output are derived for the IF signal;finally,the algorithm of the optimal matching STSR is proposed with the optimal matching parameters.The simulation results show that the algorithm can effectively solve the detection failure,as the global output SNR of DSFH is strongly improved that the output SNR can reach-17.72 d B when the input SNR is-20 d B after the processing of the optimal matching STSR.

A type of collective detection scheme with improved pigeon-inspired optimization

Purpose-With increasing demand of localization service in challenging environments where Global Navigation Satellite Systems(GNSS)signalsare considerably weak,a powerful approach,the collective detection(CD),has been developed.However,traditional CD techniques are computationally intense due to the large clock bias search space.Therefore,the purpose of this paper is to develop a new scheme of CD with less computational burden,in order to accelerate the detection and location process.Design/methodology/approach-This paper proposes a new scheme of CD.It reformulates the problem ofGNSS signal detection as an optimization problem,and solves it with the aid of an improved Pigeon-Inspired Optimization(PIO).With the improved PIO algorithm adopted,the positioning algorithm arrives to evaluate only a part of the points in the search space,avoiding the problems of grid-search method which is universally adopted.Findings-Faced with the complex optimization problem,the improved PIO algorithm proves to have good performance.In the acquisition of simulated and real signals,the proposed scheme of CD with the improved PIO algorithm also have better efficiency,precision and stability than traditional CD algorithm.Besides,the improved PIO algorithm also proves to be a better candidate to be integrated into the proposed scheme than particle swarm optimization,differential evolution and PIO.Originality/value-The novelty associated with this paper is the proposition of the new scheme of CD and the improvement of PIO algorithm.Thus,this paper introduces another possibility to ameliorate the traditional CD.