Conventional Cross-correlation Research Articles

Matrix Pencil Method를 이용한 고분해능 TDOA 추정 기법

TDOA 기법은 위치추정 기법의 하나로 간단한 구조와 높은 정확도를 가지는 장점으로 인해 실내측위, 재머 위치추적, 인명구조 등에 자주 사용된다. 본 논문에서는 MPM(Matrix Pencil Method)를 이용한 고분해능 TDOA 추정 기법을 제안한다. 제안된 기법은 기존의 교차상관을 이용한 TDOA 기법에 비교하여 높은 정확도를 가지며 협대역 신호에 적용이 가능하다. 또한 잘 알려진 고분해능 기법 중 하나인 MUSIC(Multiple Signal Classification)에서 공분산 행렬을 사용하는 것과 달리 수집된 데이터를 바로 행렬로 만들어 사용하므로 복잡성이 낮은 특징이 있다. 제안된 기법의 성능을 검증하기 위해 소프트웨어 시뮬레이션 통해 추정 오차와 연산량 측면에서 MUSIC 기법과 비교하였다. TDOA which is one of the position estimation methods is used on indoor positioning, jammer localization, rescue of life, etc. due to high accuracy and simple structure. This paper proposes the super-resolution TDOA estimator using MPM(Matrix Pencil Method). The proposed estimator has more accuracy and is applicable to narrowband signal compared with the conventional cross-correlation. Furthermore, its complexity is low because obtained data directly is used for construction of matrix unlike the MUSIC(Multiple Signal Classification) which is one of the well-known super-resolution estimator using covariance matrix. To validate the performance of proposed estimator, errors of estimation and computational burden is compared to MUSIC through software simulation.

IEEE 802.16e 초기 레인징을 위한 상호 상관 누적 기반 타이밍 옵셋 추정 기법

본 논문에서는 IEEE 802.16e 초기 레인징을 위한 타이밍 옵셋 추정 기법을 제안한다. 기존의 연구에서는 수신 신호와 국부 (local) 신호의 상호 상관값만을 이용하여 타이밍 옵셋을 추정하였으나, 본 논문에서는 레인징 신호가 반복하여 전송된다는 특성을 이용하여 추가적인 상호 상관을 구하여 누적함으로써 상호 상관 함수의 main peak과 side peak의 전력 차이를 증가시킨다. 또한 모의실험을 통해 제안한 기법이 기존의 기법에 비해 우수한 타이밍 옵셋 추정 성능을 보임을 확인하였다. In this paper, we propose a timing offset estimation scheme for initial ranging of IEEE 802.16e systems. The conventional scheme estimates the timing offset by using the cross-correlation between the local and received signals only. On the other hand, this paper proposes a timing offset estimation scheme with additional cross-correlations accumulated on the conventional cross-correlation. The additional cross-correlations are obtained by using the ranging signal with a repetitive structure. Numerical results show that the proposed scheme provides the better timing offset estimation performance compared with that of the conventional scheme.

Micro-particle image velocimetry measurement of blood flow: validation and analysis of data pre-processing and processing methods

The intent of this paper is to investigate the application of a pre-processing method previously validated on glycerol to blood flows in microchannels and to compare the accuracy of results obtained when applied to a non-homogeneous fluid such as blood with results from previously applied processing methods for blood data. Comparisons of common processing methods are desired for a clear measure of accuracy in order to make recommendations for various flows. It is hypothesized that increasing the correlation window overlap improves the profile prediction. The amount of correlation window overlap and window shape in the processing of data have a significant effect on the results. Image pre-processing is explored to improve the correlation using the ‘image overlapping’ which is extended to the case of blood and the blood-specific pre-processing ‘base-clipping’ or ‘thresholding’ technique currently applied to blood. Both pre-processing methods are tested with multiple processing methods for two channel geometries: a straight rectangular channel and a Y-channel resulting in a controlled shear flow. The resulting profiles and calculations demonstrate that ‘image-overlapping’ is found to achieve a profile closer to the predicted theoretical profile than current blood pre-processing methods when both are applied to the same set of data and both are superior to conventional cross-correlation on its own. In all cases, pre-processing decreases the smoothness of the predicted profile. The use of ‘image-overlapping’ is shown to have greater accuracy when calculating the shear rate at the wall of the channel as well.

An alternative consideration for the testing procedure of the S-curve hypothesis

Backus et al. (Am Econ Rev 84:84–103, 1994) introduced a new theoretical interpretation of the short-run relationship between the terms of trade and the trade balance: movements in net exports and the tendency for the trade balance to be negatively correlated with current and future movements in the terms of trade, but positively correlated with past movements. There have been several papers aimed at testing the S-curve hypothesis in the related literature. The most common empirical approach used in those papers is the cross-correlation analysis. This paper highlights several deficiencies of the cross-correlation analysis when being used directly to test for the validity of the mentioned hypothesis. The purpose of this paper is to offer an alternative approach so as to combine the causality theory in econometrics with the testing procedure of the S-curve hypothesis via the cross-correlations. The paper’s empirical results reveal that disaggregated bilateral trade data between the United States and China almost never support the S-curve hypothesis, contrarily to a previous paper employing the same data, but utilizing the conventional cross-correlation analysis. Why this difference may have appeared is also discussed.

Dynamical lag correlation exponent based method for gas–solid flow velocity measurement using twin-plane electrical capacitance tomography

In a twin-plane electrical capacitance tomography (ECT) system, velocity measurement of two-phase flow is transformed into the time delay estimation problem, while the nongaussianity and nonstationarity of two-phase flow signals have put the validity of the conventional cross-correlation algorithm in jeopardy. To improve the robustness and reliability of flow velocity measurement, an alternative method is proposed based on the dynamical lag correlation exponent and applied to coal ash measurement in a pneumatic pipeline. Different from the cross-correlation method which picks the peak point of the cross-correlation function as the delayed frames between the upstream and downstream signals, the proposed method determines the delayed frames by finding the minimum point of the dynamical lag correlation exponent. The preliminary results of flow velocity measurement indicate that the proposed method is capable of detecting various velocities (8–25 m s−1), which is useful for monitoring and predicting flow instability.

Two-stage source tracking method using a multiple linear regression model in the expanded phase domain

This article proposes an efficient two-channel time delay estimation method for tracking a moving speaker in noisy and re-verberant environment. Unlike conventional linear regression model-based methods, the proposed multiple linear regression model designed in the expanded phase domain shows high estimation accuracy in adverse condition because its the Gaussian assumption on phase distribution is valid. Therefore, the least-square-based time delay estimator using the proposed multiple linear regression model becomes an ideal estimator that does not require a complicated phase unwrapping process. In addition, the proposed method is extended to the two-stage recursive estimation approach, which can be used for a moving source tracking scenario. The performance of the proposed method is compared with that of conventional cross-correlation and linear regression-based methods in noisy and reverberant environment. Experimental results verify that the proposed algorithm significantly decreases estimation anomalies and improves the accuracy of time delay estimation. Finally, the tracking performance of the proposed method to both slow and fast moving speakers is confirmed in adverse environment.

Timing synchronisation for orthogonal frequency division multiplexing using improved cross-correlation

A timing synchronisation method for orthogonal frequency division multiplexing (OFDM) using improved cross-correlation (ICC) is proposed in this study. The proposed method is derived in terms of maximum-a-posteriori (MAP) criterion over an additive white Gaussian noise (AWGN) channel. In this way, the proposed ICC method is able to take into consideration the surrounded data signals, which is not considered in the conventional cross-correlation (CCC) method and thus the timing accuracy is improved accordingly. Compared to the CCC method, the ICC method only appends a correction term to the cross-correlator output, which can be easily implemented using an iterative method. Therefore the complexity of the proposed ICC method has no significant increase. Simulation results show that the proposed ICC method significantly outperforms the CCC based timing method.

Imaging condition for nonlinear scattering-based imaging: Estimate of power loss in scattering

Imaging highly complex subsurface structures is a challenging problem because it must ultimately deal with nonlinear multiple-scattering effects (e.g., migration of multiples, wavefield extrapolation with nonlinear model interactions, amplitude-preserving migration) to overcome the limitations of linear imaging. Most of the current migration techniques rely on the linear single-scattering assumption, and therefore, fail to handle these complex scattering effects. Recently, seismic imaging has been related to scattering-based image-domain interferometry to address the fully nonlinear imaging problem. Building on this connection between imaging and interferometry, we define the seismic image as a locally scattered wavefield and introduce a new imaging condition that is suitable and practical for nonlinear imaging. A previous formulation of nonlinear scattering-based imaging requires the evaluation of volume integrals that cannot easily be incorporated in current imaging algorithms. Our method consisted of adapting the conventional crosscorrelation imaging condition to account for the interference mechanisms that ensure power conservation in the scattering of wavefields. To do so, we added the zero-lag autocorrelation of scattered wavefields to the zero-lag crosscorrelation of reference and scattered wavefields. In our development, we demonstrated that this autocorrelation of scattered fields fully replaces the volume scattering term required by the previous formulation. We also found that this replacement follows from the application of the generalized optical theorem. The resulting imaging condition accounts for nonlinear multiple-scattering effects, reduces imaging artifacts and improves amplitude preservation and illumination in the images. We addressed the principles of our nonlinear imaging condition and demonstrated its importance in ideal nonlinear imaging experiments, i.e., we presented synthetic data examples assuming ideal scattered wavefield extrapolation and studied the influence of different scattering regimes and aperture limitation.

Enhanced detection capability of non-volcanic tremor using a 3-level vertical seismic array network, VA-net, in southwest Japan

[1] This study evaluates a method that enhances detection of non-volcanic low frequency tremor (NVT) using VA-net, a 3-level vertical seismic array network that was recently constructed in southwest Japan. The method employs semblance analysis for continuous vertical array records and calculates semblance coefficients as a function of time and apparent vertical velocity. The sign of the best apparent velocity provides information about propagation direction, either upward or downward, allowing easy discrimination between seismic signals of natural origin and unwanted noise such as man-made vibrations. We applied the method to a NVT episode that occurred beneath the Kii Peninsula during November 2008, to demonstrate that NVT signals can be detected using only the 3-level array. Furthermore, we demonstrate that the method enables us to detect minor NVT activity which is not detected by a conventional envelope cross-correlation method, resulting in a dramatic improvement in detection capability.

Adaptive Line Enhancement for Improved Uplink Time Difference of Arrival Localization

The problem of locating mobile stations (MS) in cellular systems based on uplink time difference of arrival (UTDOA) of MS signal at spatially separated base stations with known locations is addressed in this paper. Multipath fading and channel noise are the main factors resulting in inaccurate mobile station position estimation. Therefore, use of the normalized least mean square (NLMS) algorithm based adaptive line enhancer (ALE) followed by a correlator is proposed to obtain more precise time difference of arrival (TDOA) estimation. The proposed technique applies the ALE as a pre-filter to signal cross correlation, leading to improved accuracy in TDOA estimation and consequently more precise positioning of MS. The robustness of the proposed technique is examined and analyzed through computer simulations. Simulation results indicate superior performance of the proposed ALE-UTDOA estimator over the conventional cross correlation method.

Multi-Cross-Correlation Method in Particle Image Velocimetry

ABSTRACTA multi-cross-correlation method (MCCM) was developed in a particle image velocimetry (PIV) auto-processing system to reduce spurious vectors and improve accuracy of measurements. This technique is an improvement based on conventional cross-correlation method (CCM). Four typical neighboring interrogation windows were specified to be overlapped and calculated by MCCM. A high cross-correlation value is obtained in which many particle images match up with their corresponding spatially shifted partners, and small cross-correlation peaks due to interference of noises during experiments are reduced. Several parameters such as out-of-plane motions, particle size, and seeding density are considered for checking both MCCM and conventional PIV algorithms. The examination gives authenticity to the merits of MCCM for avoiding particles loss or mistaken velocity vectors.

Robust multi-scale image matching for deriving ice surface velocity field from sequential satellite images

The cross-correlation-based image matching method has been widely used to derive ice surface motion information from sequential satellite images through tracking spatial displacements of surface features over time. However, this conventional method is not adequate for handling areas with a high velocity variation, in which case a large search window has to be specified in order to find the correct match points for fast-moving features. The computation involved in the cross-correlation matching with a large search window is often so intensive that only a sparse set of velocity measurements can be attempted. Furthermore, with a greater search window the cross-correlation method is prone to more spurious matches. This article presents a robust multi-scale image matching method to address the deficiencies of the conventional cross-correlation technique. The main idea is to use approximate match points obtained at a coarse resolution as a guide for searching for more precise matches at a higher resolution. A robust local statistical operator is embedded at each scale in the multi-scale matching process to eliminate match outliers. The strategy of progressively refining the match precision from coarse-resolution images to the full-resolution image allows for a small search range in pixels. Our robust multi-scale matching method significantly speeds up the computation and also reduces the occurrences of bad and spurious match points. We have implemented our method as a software tool with a graphical user interface and successfully applied it to process sequential Radarsat synthetic aperture radar images for extracting high-resolution velocity fields for Antarctic glaciers and ice shelves. This software tool will be freely available to the public through the Internet.

Refinement procedure for the image alignment in high-resolution electron tomography

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data.

Integrating Fast Karnough Map and Modular Neural Networks for Simplification and Realization of Complex Boolean Functions

In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous nonmodular designs, a clear reduction in the order of computations and hardware requirements is achieved. Keywords—Boolean Functions, Simplification, Karnough Map, Implementation of Logic Functions, Modular Neural Networks.

하이브리드 PTV-PIV알고리듬에 의한 고정밀 와도 추정

Abstract. A PTV algorithm was constructed using a linear transformation, in which the merits of the con-ventional PIV and PTV were adopted. In PIV calculations, the obtained velocity vectors are affected bythe filtering effects by its calculation principle. PTV techniques are widely used for their excellences ofmeasuring small scaled flows, such as nano and bio flows. However, PTVs produce vector errors due tointerpolation process. To overcome these problems, a hybrid PTV algorithm was constructed by combiningPTVs' and PIVs' benefits using a linear transformation. The Taylor-Green vortex flows were generatedfor the tests of vorticity calculations. The conventional gray-level cross-correlation PIV technique and 2-Frame PTV technique were tested for the same flows for comparisons with those obtained by the con-structed hybrid algorithm. The excellence of the constructed hybrid algorithm was validated through anactual experiment on the cylinder wake. Key Words: PIV(입자영상유속계), PTV(입자추적유속계), Hybrid Algorithm(하이브리드알고리듬 ), CylinderWake( 실린더후류), Vorticity(와도)

Using instantaneous phase coherence for signal extraction from ambient noise data at a local to a global scale

SUMMARY Stacks of ambient noise cross-correlations are more and more routinely used to extract empirical Green's functions between station pairs. The success of the cross-correlations is due to waves which are recorded by both stations and that constructively sum at lag times which equal their propagation time between the station pair. Stacking cross-correlograms corresponding to different time spans improves the azimuthal noise coverage and further enhances the signals. Here we show how the instantaneous phase coherence can be used for a more efficient signal extraction from ambient noise cross-correlations. The instantaneous phase coherence is obtained by analytic signal processing and can be employed through the phase cross-correlation and/or through the time-frequency domain phase-weighted stack. The phase cross-correlation is more sensitive to waveform similarity but less sensitive to strong amplitude features than the conventional cross-correlation. The time-frequency domain phase-weighted stack cleans the ambient noise cross-correlograms by attenuating incoherent noise and permits an improved signal identification. We show that both approaches are powerful tools in the recovery of signals from ambient noise data and show examples where they improve the extraction of P and Rayleigh waves by considering local and global scale applications.

Zero-Crossing Tracking Technique for Noninvasive Ultrasonic Temperature Estimation

The purpose of this study was to investigate the feasibility of a zero-crossing tracking (ZCT) technique for temperature estimation using ultrasound images. The backscattered ultrasound radio frequency (RF) echo from a heated region experiences time shifts, which have been identified as causing a gross effect on sound speed changes and thermal expansion. The ZCT technique tracks the shifts in the zero-crossing instants between preheated and postheated A-lines to estimate the echo shifts caused by local temperature changes. Compared to the conventional cross-correlation (CCR) technique, ZCT does not require intensive computational loadings for correlation operations; hence, the computational efficiency could be improved. Phantom experiments were performed to compare the results of temperature estimation by using the ZCT and CCR techniques. The imaging probe was a commercial linear array, and a high-intensity focused ultrasound transducer was used as a heating source. The acquired RF echo data were processed using the ZCT and CCR techniques. The estimation results of both techniques were similar. However, the ZCT technique yielded up to 7-fold better computational efficiency than the CCR technique. The ZCT technique has the ability to monitor temperature changes with superior processing speed. This method could be an alternative signal-processing technique for ultrasonic temperature estimation.

Synchronization and Relative Timing Jitter Measurement of Femtosecond and Picosecond Laser Regenerative Amplifiers

In this paper, precise synchronization of the femtosecond and picosecond laser regenerative amplifiers with different wavelengths and independent seed oscillators was achieved using the electronic phase-locked loop and global clock techniques. The root-mean-square relative timing jitter of the two regenerative amplifiers was measured as 0.66 ps using a modified statistical method based on the error propagation relation between the independent variables and the conventional optical cross-correlation technique. The results suggest that this method is more accurate and requires simple optical setups for low-pulse repetition rate lasers.

An Efficient Packet Detection Method with a Verification Mode in MB-OFDM UWB Systems

In this paper, we propose a novel packet detection method using a cross-correlation scheme with a verification mode in ultra wide-band (UWB) systems adopting multi-band OFDM (MB-OFDM) techniques. In the packet detection process, a cross-correlation scheme has the advantage of performing the acquisition of transmitted time-frequency code (TFC) for frequency hopping as well as packet detection with low hardware costs; however, it suffers from performance degradation caused by an imperfect decision process using a threshold value compared with an auto-correlation method. By using a verification mode, the proposed method improves detection performance of a cross-correlation technique considerably. This is because the verification mode can reduce a false alarm probability on packet detection by reconfirming whether or not the desired signal is received and can effectively reject temporal small correlation peaks due to the noise or sub-path signals having smaller energies. For the verification of proposed algorithm, we employ CM1 and CM4 channel models given in IEEE802.15.3a and compare the detection performance between conventional algorithms as well as the proposed one by using computer simulations. Experimental results show that the proposed scheme can reduce a packet detection error probability (PDER) to about 10?3 in CM1 channel and about 10?2 in CM4 channel at SNR = 9 dB compared with conventional methods having more than 10?1 PDER. From the experimental results, we can find that the proposed algorithm can compensate for performance degradation under high SNR condition caused by using a fixed single threshold value. We also estimate the power consumption of algorithms by utilizing both the total number of multiplications and additions employed in the algorithms and the consuming power of hardware elements under 0.13 um CMOS technology. Next, we discover that the proposed method can reduce computational complexity by a minimum of 24.5% compared with conventional cross-correlation algorithms. From the experimental and power estimation results, we can see that the proposed method is very useful for packet detection in UWB MB-OFDM systems, in which low-power implementation is an important issue.

A Study on the Pitch Search Time Reduction of G.723.1 Vocoder by Improved Hybrid Domain Cross-correlation

In this paper we proposed a new algorithm that can reduce the open-loop pitch estimation time of G.723.1. The time domain cross-correlation method is simple but has long processing time by recursive multiplication. For reduction of processing time, we use the method that compute the cross-correlation by multiplying the Fourier value of speech by it's complex conjugate. Also, we can reduce the processing time by omitting the bit-reversing of FFT and IFFT for time-frequency domain transform. As a result, the processing time of improved hybrid domain cross-correlation algorithm is reduced by 67.37% of conventional time domain cross-correlation.