A Novel Matched Filter Structure with Neuron MOS Devices

Based on the principle of the neuron MOS device,a novel matched filter structure which is easily realized by neuron MOS is presented and the details of circuit performance is analyzed.Compared to the conventional structure,the number of circuit elements is decreased greatly for the same function.The test chip is fabricated in 0.35μm process,and the measured result shows that the system structure is feasible and effective.

A high-resolution seismic catalog for the 2021 M_(S)6.4/M_(W)6.1 Yangbi earthquake sequence, Yunnan, China: Application of AI picker and matched filter

We present a high-resolution seismic catalog for the 2021 M_(S)6.4/M_(W)6.1 Yangbi sequence.The catalog has a time range of 2021-05-01 to 2021-05-28,and contains~8,000 well located events.It captures the features of the whole foreshock sequence and the early aftershocks.We designed a detection strategy incorporating both an artificial intelligent(AI)picker and a matched filter algorithm.Here,we adopt a hybrid AI method incorporating convolutional and recurrent neural network(CNN&RNN)for event detection and phase picking respectively(i.e.CERP),a light-weight AI picker that can be trained with small volume of data.CERP is first trained with detections from a STA/LTA and Kurtosis-based method called PAL,and then construct a rather complete template set of~4,000 events.Finally,the matched filter algorithm MESS augments the initial detections and measures differential travel times with cross-correlation,which finally results in precise relocation.This process gives 9,026 detections,among which 7,943 events can be well relocated.The catalog shows as expected power-law distribution of frequency magnitude and reveals detailed pattern of seismicity evolution.The main features are:(1)the foreshock sequence images simple fault geometry with consistent strike,but also show a variable event depth along strike;(2)the mainshock ruptures the same fault of the foreshock sequence and activate conjugate faults further to the southeast;(3)complex seismicity are developed in the post-seismic period,indicating complex triggering mechanisms.Thus,our catalog provides a reliable basis for further investigations,such as b-value studies,rupture process,and triggering relations.

DCT domain filtering method for multi-antenna code acquisition

For global navigation satellite system （GNSS） signals in Gaussian and Rayleigh fading channel, a novel signal detection algorithm is proposed. Under the low frequency uncertainty case, after performing discrete cosine transform （DCT） to the outputs of the partial matched filter （PMF） for every antenna, the high order com- ponents in the transforming domain will be filtered, then the equalgain （EG） combination for the inverse discrete cosine transform （IDCT） reconstructed signal would be done subsequently. Thus, due to the different frequency distribution characteristics between the noise and signals, after EG combination, the energy of signals has almost no loss and the noise energy is greatly reduced. The theoretical analysis and simulation results show that the detection algorithm can effectively improve the signal-to-noise ratio of the captured signal and increase the probability of detection under the same false alarm probability. In addition, it should be pointed out that this method can also be applied to Rayleigh fading channels with moving antenna.

Matched Filter Based Spectrum Sensing When Primary User Has Multiple Power Levels

In this paper,we investigate the matched filter based spectrum sensing in a more reasonable cognitive radio(CR) scenario when the primary user(PU) has more than one transmit power levels,as regulated in most standards,i.e.,IEEE 802.11 Series,GSM,LTE,LTE-A,etc.This new multiple primary transmit power(MPTP) scenario is specialized by two different targets:detecting the presence of PU and identifying the power level.Compared to the traditional binary sensing where only the presence of PU is checked,SU may attain more information about the primary network(making CR more "intelligent") and design the subsequent optimization strategy.The key technology is the multiple hypothesis testing as opposed to the traditional binary hypothesis testing.We discuss two situations under whether the channel phase is known or not,and we derive the closed form solutions for decision regions and several performance metrics,from which some interesting phenomenons are observed and the related discussions are presented.Numerical examples are provided to corroborate the proposed studies.

Novel matched filtering method and its application in radar system

The method of using a narrowband filter to realize matched filtering is derived.A novel method of using spectrum sampling to realize matched filtering is presented,and the method can conquer the disadvantages that the narrowband filter cannot adopt the adaptive scheduling of phased array radars and realize matched filtering for several waveforms.A novel error extraction method is proposed,which uses a time division multipath method to realize the intermediate frequency extraction.This method can save lots of space for vehicle-born radar systems,reduce the influence of amplitude and phase distortion caused by devices,and enhance the system reliability.Simulation results show that the spectrum sampling method is applicable,and the implementation of frequency spectrum sampling is elaborated.

A 15-year-Long catalog of seismicity in the Eastern Tennessee Seismic Zone(ETSZ)using matched filter detection

We present a detailed catalog of 13671 earthquakes in the Eastern Tennessee Seismic Zone(ETSZ)that spans January 1,2005 to July 31,2020.We apply a matched filter detection technique on over 15 years of continuous data,resulting in arguably the most complete catalog of seismicity in the ETSZ yet.The magnitudes of newly detected events are determined by computing the amplitude ratio between the detections and templates using a principal component fit.We also compute the b-value for the new catalog and comparatively relocate a subset of newly detected events using XCORLOC and hypoDD,which shows a more defined structure at depth.We find the greatest concentration along and to the east of the New York-Alabama Lineament,as defined by the magnetic anomaly,supporting the argument that this feature likely is related to the generation of seismicity in the ETSZ.We examine seismicity in the vicinity of the Watts Bar Reservoir,which is located about 5 km from the epicenter of the M_(W) 4.4 December 12,2018 Decatur,Tennessee earthquake,and find possible evidence for reservoir modulated seismicity in this region.We also examine seismicity in the entire ETSZ to search for a correlation between shallow earthquakes and seasonal hydrologic changes.Our results show limited evidence for hydrologicallydriven shallow seismicity due to seasonal groundwater levels in the ETSZ,which contradicts previous studies hypothesizing that most intraplate earthquakes are associated with the dynamics of hydrologic cycles.

Hierarchical particle filter tracking algorithm based on multi-feature fusion

A hierarchical particle filter（HPF） framework based on multi-feature fusion is proposed.The proposed HPF effectively uses different feature information to avoid the tracking failure based on the single feature in a complicated environment.In this approach,the Harris algorithm is introduced to detect the corner points of the object,and the corner matching algorithm based on singular value decomposition is used to compute the firstorder weights and make particles centralize in the high likelihood area.Then the local binary pattern（LBP） operator is used to build the observation model of the target based on the color and texture features,by which the second-order weights of particles and the accurate location of the target can be obtained.Moreover,a backstepping controller is proposed to complete the whole tracking system.Simulations and experiments are carried out,and the results show that the HPF algorithm with the backstepping controller achieves stable and accurate tracking with good robustness in complex environments.

Algorithm of far-field centre estimation based on phase-only matched filter

Estimation of the far-field centre is carried out in beam auto-alignment. In this paper, the features of the far-field of a square beam are presented. Based on these features, a phase-only matched filter is designed, and the algorithm of centre estimation is developed. Using the simulated images with different kinds of noise and the 40 test images that are taken in sequence, the accuracy of this algorithm is estimated. Results show that the error is no more than one pixel for simulated noise images with a 99% probability, and the stability is restricted within one pixel for test images. Using the improved algorithm, the consumed time is reduced to 0.049 s.

Enhanced spectrum sensing using a combination of energy detector,matched filter and cyclic prefix

In this paper,we propose a sensing scheme based on energy detection,matched filter and cyclic prefix.Both Equal Gain Combining(EGC)and optimal combination of the aforementioned detectors are investigated in cooperative and non-cooperative spectrum sensing scenarios.In packet transmission systems such as OFDM(Orthogonal Frequency Division Multiple access)systems,the proposed scheme takes advantage of utilizing more samples than individual detectors,i.e.,cyclic prefix,training or pilot samples,and data payload samples.The proposed combine-sensing scheme offers higher detection probability and lower false alarm probability,as compared with the performance of individual detectors over the same frame duration.Simulation results are congruent with the theoretical curves and confirm the validity of our derivations.

Probability density analysis of SINR in massive MIMO systems with matched filter beamformer

This paper derives an approximate formula for probability density function(PDF) of received signal-to-interference-and-noise ratio(SINR) at user terminal when matched filter(MF) is adopted at a base station(BS).This distribution of SINR can be used to make an analysis of average sum-rate,outage probability,and symbol error rate of massive MIMO downlink with MF at BS.From simulation,it is found that the derived approximate analytical expression for PDF of SINR is consistent with the simulated exact PDF from the definition of SINR in medium-scale and large-scale MIMO systems.

Design of New SAWDQPSK Matched Filter

A new surface acoustic Wave differential quadraphase shift key（SAW DQPSK） spread spectrum （SS） signal matched filter based on the fusion of SS and differential modulation is reported. The design of multi-phase coded SAW matched filter is proposed rather than another design of SAW DQPSK filter, which can cut in a half of the delay time of SAW DQPSK matched filter and SAW fixed delay line（FDL） used for differential demodulation. This breakthrough is made the system largely reduce a size and process much easily. This method can also be feasible in other SAW MPSK matched filter design especially when the modulation phase number is larger than 4. The design example and its experimental results are given.

Windowed overlapped frequency domain block filtering approach for direct sequence signal acquisition

This study applies a windowed frequency domain overlapped block filtering approach to acquire direct sequence signals. As a novel viewpoint, the windows not only allow pulse shaping without front-end pulse-shaping filter, but also increase the performance of the spectrum sensing unit, which can efficiently be implemented into this frequency domain receiver and may further be used for spectrum sensing in cognitive radios or narrowband interference cancellation in military radios. The proposed receiver is applicable for the initial time synchroni- zation of different signals containing a preamble. These signals include single carrier, constant envelope single carder, multicarrier, and even generalized multicarrier signals, making the proposed receiver structure a universal unit. Furthermore, the receiver can be used to perform filtering with long codes and compute the sliding correlation of an unknown periodic preamble. The receiver can further be modified to handle large Doppler shifts. We will also demonstrate herein the computational complexity and analysis of the acquisition performance in Rayleigh and Rician fading channels.

Fingerprints Matching Based on the Integrated Template

Traditional fingerprints matching approaches are based on the minutiae and the texture characteristics. It is difficult for today's techniques to deal with the images captured by the solid-state fingerprint sensors because the sampling area of these sensors is very small and only portion of the fingerprint can be obtained. In this paper, a novel integrated template has been built using several images and combining the minutiae with the texture characteristics at the same time. By using a kind of Gabor filters (eight directions) on the region around the reliable minutiae, local texture of each minutia termed as minutiacode is extracted. Further, a real-time matching algorithm using the integrated template is presented. The output is determined by the weight factor of the compound matching. Finally, experimental results show that this system performs well in reducing false reject rate (FRR).

Interpolation of near offset using surface-related multiples

In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation or extrapolation of adjacent channels for reconstruction of missing seismic data. In this method there are two steps, first, we construct pseudo-primaries by cross-correlation of surface multiple data to extract the missing near- offset information in multiples, which are not displayed in the acquired seismic record. Second, we correct the pseudo-primaries by applying a Least-squares Matching Filter （LMF） and RMS amplitude correction method in time and space sliding windows. Then the corrected pseudo-primaries can be used to fill the data gaps. The method is easy to implement, without the need to separate multiples and primaries. It extracts the seismic information contained by multiples for filling missing traces. The method is suitable for seismic data with surfacerelated multiples.

L1 norm optimal solution match processing in the wavelet domain

Greater attention has been paid to vintage-merge processing of seismic data and extracting more valuable information by the geophysicist. A match filter is used within many important areas such as splicing seismic data, matching seismic data with different ages and sources, 4-D seismic monitoring, and so on. The traditional match filtering method is subject to many restrictions and is usually difficult to overcome the impact of noise. Based on the traditional match filter, we propose the wavelet domain L1 norm optimal matching filter. In this paper, two different types of seismic data are decomposed to the wavelet domain, different detailed effective information is extracted for Ll-norm optimal matching, and ideal results are achieved. Based on the model test, we find that the L1 norm optimal matching filter attenuates the noise and the waveform, amplitude, and phase coherence of result signals are better than the conventional method. The field data test shows that, with our method, the seismic events in the filter results have better continuity which achieves the high precision seismic match requirements.

Data Analysis Methods and Signal Processing Techniques in Gravitational Wave Detection

Gravitational wave detection is one of the most cutting-edge research areas in modern physics, with its success relying on advanced data analysis and signal processing techniques. This study provides a comprehensive review of data analysis methods and signal processing techniques in gravitational wave detection. The research begins by introducing the characteristics of gravitational wave signals and the challenges faced in their detection, such as extremely low signal-to-noise ratios and complex noise backgrounds. It then systematically analyzes the application of time-frequency analysis methods in extracting transient gravitational wave signals, including wavelet transforms and Hilbert-Huang transforms. The study focuses on discussing the crucial role of matched filtering techniques in improving signal detection sensitivity and explores strategies for template bank optimization. Additionally, the research evaluates the potential of machine learning algorithms, especially deep learning networks, in rapidly identifying and classifying gravitational wave events. The study also analyzes the application of Bayesian inference methods in parameter estimation and model selection, as well as their advantages in handling uncertainties. However, the research also points out the challenges faced by current technologies, such as dealing with non-Gaussian noise and improving computational efficiency. To address these issues, the study proposes a hybrid analysis framework combining physical models and data-driven methods. Finally, the research looks ahead to the potential applications of quantum computing in future gravitational wave data analysis. This study provides a comprehensive theoretical foundation for the optimization and innovation of gravitational wave data analysis methods, contributing to the advancement of gravitational wave astronomy.

Near-field 3D imaging approach combining MJSR and FGG-NUFFT

A near-field three-dimensional(3 D)imaging method combining multichannel joint sparse recovery(MJSR)and fast Gaussian gridding nonuniform fast Fourier transform(FGGNUFFT)is proposed,based on a perfect combination of the compressed sensing(CS)theory and the matched filtering(MF)technique.The approach has the advantages of high precision and high efficiency:multichannel joint sparse constraint is adopted to improve the problem that the images recovered by the single channel imaging algorithms do not necessarily share the same positions of the scattering centers;the CS dictionary is constructed by combining MF and FGG-NUFFT,so as to improve the imaging efficiency and memory requirement.Firstly,a near-field 3 D imaging model of joint sparse recovery is constructed by combining the MF-based imaging method.Secondly,FGG-NUFFT and reverse FGG-NUFFT are used to replace the interpolation and Fourier transform in MF-based imaging methods,and a sensing matrix with high precision and high efficiency is constructed according to the traditional imaging process.Thirdly,a fast imaging recovery is performed by using the improved separable surrogate functionals(SSF)optimization algorithm,only with matrix and vector multiplication.Finally,a 3 D imagery of the near-field target is obtained by using both the horizontal and the pitching interferometric phase information.This paper contains two imaging models,the only difference is the sub-aperture method used in inverse synthetic aperture radar(ISAR)imaging.Compared to traditional CS-based imaging methods,the proposed method includes both forward transform and inverse transform in each iteration,which improves the quality of reconstruction.The experimental results show that,the proposed method improves the imaging accuracy by about O(10),accelerates the imaging speed by five times and reduces the memory usage by about O(10~2).

ECCM schemes in netted radar system based ontemporal pulse diversity

For a netted radar system to counteract the deceptionelectronic countermeasure （ECM） signals, an effective electroniccounter countermeasure （ECCM） approach is proposed. The proposedapproach is realized based on the new signaling strategyfor the temporal pulse diversity, which makes use of transmittingpulses at each pulse repetition interval （PRI） with specific transmissionpulse block, and then following proper processing andinformation fusion. The existence of the deceptive ECM signal isconfirmed by one station, while the other stations in the nettedradar with same parameters applied the pulse diversity skillfully.Meanwhile, this method ensured that, pulse diversity can be appliedin netted radar. The performance assessment shows that theproposed solutions are effective in presence of ECM signals. Thisalgorithm has been demonstrated by simulations. The presentedsimulation results are in excellent consensus with theoretical predictions.

A Modified Multiple Matching Method Based on Equipoise Pseudomulti-Channel Filter and Huber Nor

This study is aimed at improving multiple adaptive subtraction.We propose a modified pseudomulti-channel matching method based on the Huber norm,to adjust the matching differences on frequency and phase between the predicted multi-ples and original data.The second-order derivative of the predicted multiples is utilized to replace the derivative of its Hilbert transform.Due to the additional frequency term,this method can enhance the high-frequency component.We introduce 180◦phase rotation of the multiple channels,which can decrease phase differences.The Huber norm interpolates between smooth L2 norm treatment of small residuals and robust L1 norm treatment of large residuals.This method can eliminate the restriction of large value conditions from the L2 norm and weaken the condition of orthogonality from the L1 norm.The applications of the Pluto and Delft models shows that compared with pseudomulti-channel matching filter,the main frequency is increased from 36 Hz to 38 Hz,and the primary reflection wave is more concentrated.The practical application of field data verifies the effectiveness of the proposed method.

Purposeless repeated acquisition time-lapse seismic data processing

In China, most oil fields are continental sedimentation with strong heterogeneity, which on one side makes the reservoir prospecting and development more difficult, but on the other side provides more space for searching residual oil in matured fields. Time-lapse seismic reservoir monitoring technique is one of most important techniques to define residual oil distribution. According to the demand for and development of time-lapse seismic reservoir monitoring in China, purposeless repeated acquisition time-lapse seismic data processing was studied. The four key steps in purposeless repeated acquisition time-lapse seismic data processing, including amplitude-preserved processing with relative consistency, rebinning, match filtering and difference calculation, were analyzed by combining theory and real seismic data processing. Meanwhile, quality control during real time-lapse seismic processing was emphasized.