Using Array Methods to Identify and Process Weak Signals Generated by the Brightlight(Ⅰ) 50t Explosion

Waveforms generated by the 50t explosion of project Brightlight （ I ） were recorded by HILR array. Using array techniques, the author performed identification, f-k analysis, velocity spectrum analysis, etc. of the weak signals. The analysis results show that the signal-to-noise ratio after beamforming was obviously enhanced, and the signal could be clearly shown. The energy from this explosion was mainly concentrated in the 1 -8Hz range from f-k analysis. The velocity spectrum gave clear positions of event phases, which could not be seen in the original weak signals. The maximum energy distribution obtained by the Beaman method is close to the theoretical value in the azimuth-slowness domain.

Analysis of a kind of Duffing oscillator system used to detect weak signals

The stability of the periodic solution of the Duffing oscillator system in the periodic phase state is proved by using the Yoshizaw theorem, which establishes a theoretical basis for using this kind of chaotic oscillator system to detect weak signals. The restoring force term of the system affects the weak-signal detection ability of the system directly, the quantitative relationship between the coefficients of the linear and nonlinear items of the restoring force of the Duffing oscillator system and the SNR in the detection of weak signals is obtained through a large number of simulation experiments, then a new restoring force function with better detection results is established.

Vector tracking loops in GNSS receivers for dynamic weak signals

Vehicle positioning with the global navigation satellite system （GNSS） in urban environments faces two problems which are attenuation and dynamic. For traditional GNSS receivers hardly able to track dynamic weak signals, the coupling between all visible satellite signals is ignored in the absence of navigation state feedback, and thermal noise error and dynamic stress threshold are contradictory due to non-coherent discriminators. The vector delay/frequency locked loop （VDFLL） with navigation state feedback and the joint vector tracking loop （JVTL） with coherent discriminator which is a synchronization parameter tracking loop based on maximum likelihood estimation （MLE） are proposed to improve the tracking sensitivity of GNSS receiver in dynamic weak signal environments. A joint vector position tracking loop （JVPTL） directly tracking user position and velocity is proposed to further improve tracking sensitivity. The coherent navigation parameter discriminator of JVPTL, being able to ease the contradiction between thermal noise error and dynamic stress threshold, is based on MLE according to the navigation parameter based linear model of received baseband signals. Simulation results show that JVPTL, which combines the advantages of both VDFLL and JVTL, performs better than both VDFLL and JVTL in dynamic weak signal environments.

Method of Weak Signals Detection Based on Chaos Suppression in the Nonresonant Parametric Drive

The evolution of chaotic state of Iarenz system on the fa- miliar parameter space cabit is analyzed. Based on the principle of chaos suppression with ntmrestmaat parametric drive, the trodel of detecting weak periodic signals in strong noise is Imilt. According to the parametric equivalent relationship obtained using averaging method and rmtmmlization method, the critical values of detection parameters are determined, which lead to a sudden change of system dynamical behavior from periodic orbit to stable equilibritma point. Sinmlation results show that weak periodic signals in strong noise can be detected acomately with the proposed system. The method can obtain aoawate rane of parameter threshold through tlxxtetical analysis, and the detection criterion is rather simple, which is more convenieat for automatic detection.

N-th root slant stack for enhancing weak seismic signals

Seismic imaging of complicated underground structures with severe surface undulation(i.e.,double complex areas)is challenging owing to the difficulty of collecting the very weak reflected signal.Enhancing the weak signal is difficult even with state-of-the-art multi-domain and multidimensional prestack denoising techniques.This paper presents a time–space dip analysis of offset vector tile(OVT)domain data based on theτ-p transform.The proposed N-th root slant stack method enhances the signal in a three-dimensionalτ-p domain by establishing a zero-offset time-dip seismic attribute trace and calculating the coherence values of a given data sub-volume(i.e.,inline,crossline,time),which are then used to recalculate the data.After sorting,the new data provide a solid foundation for obtaining the optimal N value of the N-th root slant stack,which is used to enhance a weak signal.The proposed method was applied to denoising low signal-to-noise ratio(SNR)data from Western China.The optimal N value was determined for improving the SNR in deep strata,and the weak seismic signal was enhanced.The results showed that the proposed method effectively suppressed noise in low-SNR data.

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.

A Neural Network based Method for Detection of Weak Underwater Signals

Detection of weak underwater signals is an area of general interest in marine engineering.A weak signal detection scheme was developed; it combined nonlinear dynamical reconstruction techniques, radial basis function (RBF) neural networks and an extended Kalman filter (EKF).In this method chaos theory was used to model background noise.Noise was predicted by phase space reconstruction techniques and RBF neural networks in a synergistic manner.In the absence of a signal, prediction error stayed low and became relatively large when the input contained a signal.EKF was used to improve the convergence rate of the RBF neural network.Application of the scheme to different experimental data sets showed that the algorithm can detect signals hidden in strong noise even when the signal-to-noise ratio (SNR) is less than -40d B.

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.

Implication of two-coupled tri-stable stochastic resonance in weak signal detection

Stochastic resonance （SR） has been proved to be an effective approach to extract weak signals overwhelmed in noise. However, the detection effect of current SR models is still unsatisfactory. Here, a coupled tri-stable stochastic resonance （CTSSR） model is proposed to further increase the output signal-to-noise ratio （SNR） and improve the detection effect of SR. The effects of parameters a, b, c, and r in the proposed resonance system on the SNR are studied, by which we determine a set of parameters that is relatively optimal to implement a comparison with other classical SR models. Numerical experiment results indicate that this proposed model performs better in weak signal detection applications than the classical ones with merits of higher output SNR and better anti-noise capability.

Competitive Intelligence： Bibliometric Research on Early Signals

Considering the importance of the anticipated intelligence issue on the current scenario, this article aims at understanding the scientific production about the subject, contributing to future researchers with greater academic knowledge about the productivity in the area. Therefore, a bibliometric research was carried out on weak signals and correlated matters between 1980 and 2010 and was supported by the literature review about the subject. The suggested analysis contributes to greater academic knowledge on productivity in the field, providing a broad perspective for future researchers who catch sight of this subject as a potential for further studies.

The“depict”strategy for discovering new compounds in complex matrices:Lycibarbarspermidines as a case

The comprehensive detection and identification of active ingredients in complex matrices is a crucial challenge.Liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS)is the most prominent analytical platform for the exploration of novel active compounds from complex matrices.However,the LC-HRMS-based analysis workflow suffers from several bottleneck issues,such as trace content of target compounds,limited acquisition for fragment information,and uncertainty in interpreting relevant MS2 spectra.Lycibarbarspermidines are vital antioxidant active ingredients in Lycii Fructus,while the reported structures are merely focused on dicaffeoylspermidines due to their low content.To comprehensively detect the new structures of lycibarbarspermidine derivatives,a“depict”strategy was developed in this study.First,potential new lycibarbarspermidine derivatives were designed according to the biosynthetic pathway,and a comprehensive database was established,which enlarged the coverage of lycibarbarspermidine derivatives.Second,the polarity-oriented sample preparation of potential new compounds increased the concentration of the target compounds.Third,the construction of the molecular network based on the fragmentation pathway of lycibarbarspermidine derivatives broadened the comprehensiveness of identification.Finally,the weak response signals were captured by data-dependent scanning(DDA)followed by parallel reaction monitoring(PRM),and the efficiency of acquiring MS2 fragment ions of target compounds was significantly improved.Based on the integrated strategy above,210 lycibarbarspermidine derivatives were detected and identified from Lycii Fructus,and in particular,170 potential new compounds were structurally characterized.The integrated strategy improved the sensitivity of detection and the coverage of low-response components,and it is expected to be a promising pipeline for discovering new compounds.

Weak wide-band signal detection method based on small-scale periodic state of Duffing oscillator

The conventional Duffing oscillator weak signal detection method, which is based on a strong reference signal, has inherent deficiencies. To address these issues, the characteristics of the Duffing oscillator＇s phase trajectory in a small- scale periodic state are analyzed by introducing the theory of stopping oscillation system. Based on this approach, a novel Duffing oscillator weak wide-band signal detection method is proposed. In this novel method, the reference signal is discarded, and the to-be-detected signal is directly used as a driving force. By calculating the cosine function of a phase space angle, a single Duffing oscillator can be used for weak wide-band signal detection instead of an array of uncoupled Duffing oscillators. Simulation results indicate that, compared with the conventional Duffing oscillator detection method, this approach performs better in frequency detection intervals, and reduces the signal-to-noise ratio detection threshold, while improving the real-time performance of the system.

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).

Design of a Weak Signal Detecting Circuit in the Infrared Spectrum Absorbed Type Gas Sensor

In the infrared spectrum absorbed type gas concentration sensor,voltage signal obtained from the two-channel thermopile infrared detector TPS2534 is very weak.In order to solve this problem,the authors have established the structure of the sensor and designed weak signal detecting circuit of the sensor based on infrared spectrum absorption principle,differential de-noising principle and weak signal detecting principle.The authors have made experiments using CH4 gas.The results show that the circuit can remove noise effectively and detect weak electrical signal obtained from the detector.

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 d BW sensitivity with a very short data length of 1 ms.

TLR signaling that induces weak inflammatory response and SHIP1 enhances osteogenic functions

Toll-like receptor （TLR）-mediated inflammatory response could negatively affect bone metabolism. In this study, we determined how osteogenesis is regulated during inflammatory responses that are downstream of TLR signaling. Human primary osteoblasts were cultured in collagen gels. Pam3CSK4 （P3C） and Escherichia coli lipopolysaccharide （EcLPS） were used as TLR2 and TLR4 ligand respectively. Porphyromonas gingivalis LPS having TLR2 activity with either TLR4 agonism （Pg1690） or TLR4 antagonism （Pg1449） and mutant E. coli LPS （LPxE/LPxF/WSK） were used. IL-lp, SH2-containing inositol phosphatase-1 （SHIP1） that has regulatory roles in osteogenesis, alkaline phosphatase and mineralization were analyzed. 3α-Aminocholestane （3AC） was used to inhibit SHIP1. Our results suggest that osteoblasts stimulated by P3C, poorly induced IL-1β but strongly upregulated SHIP1 and enhanced osteogenic mediators. On the contrary, EcLPS significantly induced IL-1β and osteogenic mediators were not induced. While Pg1690 downmodulated osteogenic mediators, Pg1449 enhanced osteogenic responses, suggesting that TLR4 signaling annuls osteogenesis even with TLR2 activity. Interestingly, mutant E. coli LPS that induces weak inflammation upregulated osteogenesis, but SHIP1 was not induced. Moreover, inhibiting SHIP1 significantly upregulated TLR2-mediated inflammatory response and downmodulated osteogenesis. In conclusion, these results suggest that induction of weak inflammatory response through TLR2 （with SHIP1 activity） and mutant TLR4 ligands could enhance osteogenesis.

Adaptive stochastic resonance method for weak signal detection based on particle swarm optimization

In order to solve the parameter adjustment problems of adaptive stochastic resonance system in the areas of weak signal detection,this article presents a new method to enhance the detection efficiency and availability in the system of two-dimensional Duffing based on particle swarm optimization.First,the influence of different parameters on the detection performance is analyzed respectively.The correlation between parameter adjustment and stochastic resonance effect is also discussed and converted to the problem of multi-parameter optimization.Second,the experiments including typical system and sea clutter data are conducted to verify the effect of the proposed method.Results show that the proposed method is highly effective to detect weak signal from chaotic background,and enhance the output SNR greatly.