Linear Sensor Array Research Articles

Effect of accelerometer location on mechanomyogram variables during voluntary, constant-force contractions in three human muscles.

To understand better the features of the mechanomyogram (MMG) with different force levels and muscle architectures, the MMG signals detected at many points along three muscles were analysed by the application of a linear array of MMG sensors (up to eight) over the skin. MMG signals were recorded from the biceps brachii, tibialis anterior and upper trapezius muscles of the dominant side of ten healthy male subjects. The accelerometers were aligned along the direction of the muscle fibres. One accelerometer was located over the distal muscle innervation zone, and the other six or seven accelerometers were placed over the muscle, forming an array of sensors with fixed distances between them. The array covered almost the entire muscle length in all cases. MMG signals detected from adjacent accelerometers had similar shapes, with correlation coefficients ranging from about 0.5 to about 0.9. MMG amplitude and characteristic spectral frequencies significantly depended on accelerometer location. The MMG amplitude was maximum at the muscle belly for the biceps brachii and the tibialis anterior. Higher MMG characteristic spectral frequencies were associated with higher amplitudes in the case of the biceps brachii, whereas the opposite was observed for the tibialis anterior muscle. In the upper trapezius, the relationship between characteristic spectral frequencies, MMG amplitude and contraction force depended on the accelerometer location. This suggested that MMG spectral features do not only reflect the mechanical properties of the recruited muscle fibres but depend on muscle architecture and motor unit territorial distribution. It was concluded that the location of the accelerometer can have an influence on both amplitude and spectral MMG features, and this dependence should be considered when MMG signals are used for muscle assessment.

Computationally efficient high-resolution DOA estimation in multipath environment

A computationally efficient direction of arrival (DOA) estimation algorithm using a linear array of equispaced sensors is proposed for a multipath environment with unknown correlated signals. The algorithm comprises two stages: a first stage for discriminating uncorrelated signals, and a second stage for resolving the directions of arrival of the correlated signals using covariance differencing and iterative spatial smoothing. Simulation results show that the proposed algorithm operates at a much lower computational cost compared to standard methods.

Wideband MVDR beamforming for acoustic vector sensor linear array

A wideband minimum variance distortionless response (MVDR) beamforming approach for an acoustic vector sensor linear array is presented, which is based on coherent signal subspace preprocessing, to solve the problem of direction of arrival (DOA) estimation for wideband coherent acoustic sources. The concept of wideband focusing is introduced into wideband processing for the acoustic vector sensor array, and the relationship between the wideband focusing matrices of the acoustic vector sensor array and the pressure sensor array is derived. Simulation results show that wideband MVDR beamforming of an acoustic vector sensor linear array outperforms that of a pressure sensor when dealing with wideband coherent sources, in the following aspects: realising unambiguous direction finding in the whole space, i.e. no left/right ambiguity problem; allowing the uniform interelement spacing to exceed the Nyquist half-wavelength upper limit; and having a better performance for DOA estimation when dealing with sources close to endfire.

Multiple signal extraction by multiple interference attenuation in the presence of random noise in seismic array data

A vector of digital filters is derived for the multichannel processing of the signals acquired by an array of sensors with the objective of extracting multiple desired signals by the attenuation of multiple interferences and random noise. The signals and interferences are assumed to have arbitrary waveforms with no a priori knowledge of these waveforms. The time duration of the recorded array data is assumed to be long enough to incorporate all time delayed propagated waveforms at the sensors of the array. The derivation is for the general case of an arbitrary array geometric configuration and is not confined to the special case of a linear array of equispaced sensors. The rationale adopted in the derivation of the filters is to give first priority at each discrete frequency to passing the signals, a second priority to canceling the interferences, and a third priority to attenuating the random noise. This rationale well suits the case of seismic data that are dominantly corrupted by strong interferences rather than random noise. Solving a constrained minimization problem derives the vector of array filters. The computation of this vector requires the application of a powerful matrix decomposition technique for the detection of any redundant and/or inconsistent constraints at each discrete frequency. The simulation results demonstrate the extraction ability of the derived filters in both the multiple input single output and the multiple input multiple output processing schemes.

Effect of atmospheric pressure fluctuations on low frequency and infrasound detection

A fundamental difficulty in low‐frequency and infrasound detection is the so‐called ‘‘wind noise’’ problem. At higher (>50 Hz), this wind noise is usually associated with the obstruction formed by the pressure pobe body. In this case, most of this wind noise can be adequately removed by the use of an appropriate wind screen. At lower frequencies ( 30 elements) 3‐axis pressure sensor array is used to quantify the relative magnitude of the intrinsic and induced pressure fluctuations. Signal processing algorithms are discussed which enchance the signal‐to‐noise ratio over that obtained using standard beam forming algorithms, by utilizing the localized nature of many of the fluctuations across the array. The effect of the height of the sensor above ground on the magnitude of the observed pressure flucutations is also examined using a 3‐axis linear pressure sensor array. Finally, the performance of a single‐element porous hose array is compared to that of a large‐element array.

Modulation Transfer Function of a Pyroelectric Sensor Array Based on a Finite Element Model

Pyroelectric infrared sensor arrays are imaging devices for infrared radiation that utilize the temperature dependence of the remanent in polarization in pyroelectric materials. We use the finite element method for the calculation of the coupled thermo-electro-mechanical fields for an instance of a linear sensor array, derive the modulation transfer function from the simulation data, and compare the result to an analytical solution.

Simultaneous Principal-Component Extraction with Application to Adaptive Blind Multiuser Detection

SIPEX-G is a fast-converging, robust, gradient-based PCA algorithm that has been recently proposed by the authors. Its superior performance in synthetic and real data compared with its benchmark counterparts makes it a viable alternative in applications where subspace methods are employed. Blind multiuser detection is one such area, where subspace methods, recently developed by researchers, have proven effective. In this paper, the SIPEX-G algorithm is presented in detail, convergence proofs are derived, and the performance is demonstrated in standard subspace problems. These sub space problems include direction of arrival estimation for incoming signals impinging on a linear array of sensors, nonstationary random process subspace tracking, and adaptive blind multiuser detection.

Three-dimensional surface profile measurement of a moving object by a spatial-offset phase stepping method

This study proposes a new method for measuring the 3-D surface profile of an object moving at constant speed. A sinusoidal grating pattern is projected on a moving object. Then, grating patterns that are deformed according to the profile of the object are acquired by three linear array sensors. Since a linear array sensor records light intensity along an original grating line, the resultant image forms a fringe pattern that represents the profile of the object. Using three images obtained by the three linear array sensors, the phase distribution of the fringe pattern is calculated by a phase stepping method without any phase stepping devices. Consequently, the profile of the moving object can be evaluated from the phase of the fringes, since the value of the phase is simply proportional to the height of the object. Experimentation demonstrates that the accuracy is about 4.3% for the wrapped phase range of 2π rad with a speckle pattern present. The proposed method can be used for inspection of moving objects such as products on an assembly line.

Block Adjustment of High-Resolution Satellite Images Described by Rational Polynomials

model provides a rigorous, accurate method to block adjust This paper describes how to block adjust high-resolution Ikonos data outside of the ground stations. satellite imagery described by Rational Polynomial Coefficient This publication of a technique for block adjusting Ikonos (RPC) camera models and illustrates the method with an Ikonos images described by RPC data is motivated by a desire to satisfy example. By incorporating a priori constraints into the the needs of those users who would like to perform their own adjustment model, multiple independent images can be block adjustment, and to ensure that Ikonos images are proadjusted with or without ground control. The RPC block cessed in such way as to consistently achieve the highest possiadjustment model presented in this paper is directly related ble accuracy. In developing the adjustment model described to geometric properties of the physical camera model. Multiple here, the authors had access to the complete description of physical camera model parameters having the same net effect Ikonos imaging geometry, familiarity with all of the satellite on the object-image relationship are replaced by a single maneuvering modes, the resources of extensive test ranges and adjustment parameter. Consequently, the proposed method is imagery with which to test and validate, and the experience numerically more stable than the traditional adjustment of gained calibrating, testing, and troubleshooting Ikonos metric exterior and interior orientation parameters. This method is projects. generally applicable to any photogrammetric camera with a narrow field of view, calibrated, stable interior orientation, and Physical Camera Models accurate a priori exterior orientation data. As demonstrated Owing to the dynamic nature of satellite image collection, phoin the paper, for Ikonos satellite imagery, the RPC block togrammetric processing of satellite imagery is more compliadjustment achieves the same accuracy as the ground station cated than is aerial frame camera processing. Aerial cameras block adjustment with the full physical camera model. acquire the entire image at an instant of time with a unique exposure station and orientation. High-resolution pushbroom Background satellite cameras, including Ikonos, use linear sensor arrays

Near-field source localisation using bottom-mounted linear sensor array in multipath environment

The paper presents a 3-D near-field source localisation algorithm using a bottom-mounted linear sensor array for a multipath environment. The proposed algorithm utilises the signals from different paths plus a simple linear sensor array to estimate the 3-D location of a source, whereas conventional 3-D localisation algorithms require a 2-D array of sensors. The conic angles of the source signal are different for each path and each path signal has a different arrival time. As such, equations are derived for the source location, time difference of arrivals, and conic angles, then the location of the source is estimated by simultaneously solving these equations.

CORN CANOPY TEMPERATURES MEASURED WITH A MOVING INFRARED THERMOMETER ARRAY

Measurement of water stress and scheduling of irrigation are both enabled by noncontact infrared thermometers(IRTs). Technological advances have miniaturized IRTs and reduced power requirements so that inexpensive selfpoweredunits are now commercially available. The objective of this work was to test a linear array of IRT sensors mounted on acenterpivot irrigation machine, and to use this IRT array to examine spatial variation in water stress of corn under fourirrigation treatments imposed on a highly variable field with a center pivot equipped for sitespecific irrigation andagrochemical application. An array of 26 IRTs was mounted on the pivot, which was run dry for a full circle on 7 days duringthe 1999 corn growing season. Procedures were developed to adjust for time lag during the 3.5hr measurement period.Significant differences were obtained among the varying water treatments, as expected, but also among plots within the samesoil map unit and among soil map unit means. Distinct spatial patterns, not necessarily related to the 1:1200scale soil map,were observed. These results emphasize the necessity to consider soil water relations during the development of managementrecommendations for sitespecific agriculture.

Tracking direction of arrival with adaptive decomposed filters

An adaptive technique for the estimation and tracking of the direction of arrival of multiple nonstationary plane waves from the outputs of a uniform linear array of sensors is presented. This task is performed by using a decomposed filtering structure to spatially isolate each signal component while a second stage is used to estimate the parameters of interest (angle of arrival). This results in a computationally simple algorithm suitable for the case of large arrays which enables the tracking of rapidly moving sources. The proposed approach is also applicable to the case of coherent signals.

Fluorescent Fiber-Optic Sensor Arrays Probed Utilizing Evanescent Fiber-Fiber Coupling

Optical-fiber sensors that use fluorescent probes located in the fiber cladding are of great interest for monitoring physical and chemical properties in their environment. The interrogation of a fluorophore with a short laser pulse propagating through the fiber core allows for the measurement of the location of the fluorophore by measuring the time delay between the exciting pulse and the returning fluorescence pulse. The spatial resolution of such an array of fluorescent sensors is limited since a minimum separation of the fluorophores is required to resolve returning light pulses. For many applications a closer spacing of sensor regions is desirable, particularly for fibers prepared by using our recently introduced one-dimensional combinatorial chemistry method [A. W. Schwabacher et al., J. Am. Chem. Soc. 121, 8669 (1999)]. This method allows for efficient preparation of large, diverse, and densely packed linear arrays of sensors. We demonstrate that by using a second fiber as an optical delay line, the minimum spacing between adjacent sensor regions can be well below the fluorescence lifetime limit. Since the coupling between the two fibers is evanescent, the attenuation of the excitation pulse is low, making long arrays of sensor regions feasible. Moreover, we identify the conditions that allow for the optical readout of long arrays of sensors.

Directivity factors for linear arrays of velocity sensors

Some of the features unique to beamforming a linear array of acoustic velocity sensors, which are not present with scalar-sensing elements (such as conventional pressure sensors), are described in this paper. Four types of sensors are considered here: a uniaxial motion sensor, which measures acoustic particle velocity along a single axis; a biaxial motion sensor measuring velocity in two orthogonal directions; a triaxial motion sensor that measures all three orthogonal components of the velocity vector; and a sensor, denoted as an acoustic vector sensor, that measures acoustic pressure as well as the complete velocity vector. Comparisons are made of the directivity index for each type of sensor and for linear arrays of sensors. It is shown that uniaxial velocity sensors can have a maximum directivity factor three times greater than an omnidirectional pressure sensor, a gain in directivity index of 4.8 dB. Not surprisingly, this directivity gain is highly dependent on signal arrival direction. Indeed, a uniaxial velocity sensor’s directivity can be less than that of an omnidirectional pressure, indicative of a loss in signal level. These comparisons further indicate that a single vector sensor can provide 6 dB of directivity gain, four times the directivity of a pressure sensor. Line arrays of directional sensors can have a directivity index approximately 5 dB greater than that of an identical line array of pressure sensors for approximately all azimuthal array steerings.

Simple and accurate direction of arrival estimator in the case of imperfect spatial coherence

We consider the direction-finding problem in the imperfect spatial coherence case, i.e., when the amplitude and phase of the wavefront vary randomly along the array aperture. This phenomenon can originate from propagation through an inhomogeneous medium. It is also encountered in the case of spatially dispersed sources. We derive a fast and accurate estimator for the direction of arrival of a single source using a uniform linear array (ULA) of sensors. The estimator is based on a reduced statistic obtained from the subdiagonals of the covariance matrix of the array output. It only entails computing the Fourier transform of an (m-1)-length sequence where m is the number of array sensors. A theoretical analysis is carried out, and an expression for the asymptotic variance of the estimator is derived. Numerical simulations validate the theoretical results and show that the estimator has an accuracy very close to the Cramer-Rao bound.

Linear pyroelectric sensor array based on PCLT/P(VDF/TrFE) composite

A linear pyroelectric sensor array with calcium and lanthanum modified lead titanate/vinyli-dene fluoride-trifluoroethylene, [PCLT/P(VDF /TrFE)] composite film as the sensing material was fabricated and tested. The composite film contained 30 volume % of PCLT powder particles. A two-step poling procedure was used to polarize both the ceramic and copolymer phases in order to enhance the pyroelectric coefficient. The pyroelectric and dielectric properties of the PCLT/P(VDF/TrFE) composite film were studied as a function of temperature. The signal from the sensor array was processed by amplifying transistors with multiplexing circuitry, which was mounted alongside the array on the same IC carrier. The current and voltage responsivities were measured over a frequency range of 10 Hz to 4 kHz and found to agree with the predictions based on a one-dimensional heat diffusion model. The noise of the sensor array with the associated electronics decreases with increasing frequency and is dominated by the flicker noise from the electronics.

Computationally Efficient Maximum Likelihood Approach to DOA Estimationof a Scattered Source

The problem of Direction-Of-Arrival (DOA) estimation in the presence of local scatterers using a uniform linear array (ULA) of sensors is addressed. We consider two models depending on whether the form of the azimuthal power distribution is explicitly known or not. For both models, the block-diagonal structure of the associated Fisher Information Matrix (FIM) is exploited to decouple the estimation of the DOA from that of the other model parameters. An asymptotically efficient Maximum Likelihood (ML) DOA estimator is derived which entails solving a 1-D minimization problem only. Furthermore, the 1-D criterion can be expressed as a simple Fourier Transform. A numerical comparison with the Cramer-Rao Bound (CRB) illustrates the fact that our computationally very simple DOA estimators are statistically efficient for a wide range of scenarios.

Optimization of sensor arrays for beam position estimation

A design procedure is presented to optimize linear arrays of sensors for the estimation of the position of an incident beam. The procedure is based on the adjustment of the position and gain of the elements of the array in order to approximate the desired response (in the least squares sense). The optimization takes into account the shape of the beam profile, and provides adequate results for a wide range of beam diameters. An application is made to a linear array of circular sensors illuminated by a beam with a rectangular profile. Optimized designs are given for arrays of 2, 4 and 6 sensors. The experimental results were in good agreement with the calculations. The relative error was found to be less than ±2% and the performance of the system was insensitive to background light.

Pressure dependence of optical emission from DC magnetron sputtering plasma observed with spatial resolution

Optical emission spectroscopy (OES) with a wavelength range of 185–525 nm has been performed for DC planar magnetron sputtering of copper in argon atmosphere. Spatial resolution of the light emission has been achieved by focusing the plasma image on one end of an optical fiber. The other end of the fiber is connected to a “polychromator” with linear CCD array sensors, which enables an uptake of whole spectrum simultaneously. Several emission lines from Cu neutrals, Ar neutrals and Ar ions have been identified in the observed wavelength range. In this study, the emission spectra were measured at positions of 5 and 10 mm above the center of the Cu target. Dependences of emission intensities on discharge pressure and power have been studied, and the excitation process of Cu radicals is discussed.

Modified IQML and weighted subspace fitting without eigendecomposition

This paper deals with direction estimation of signals impinging on a uniform linear sensor array. A well-known algorithm for this problem is IQML. However, estimates computed with IQML are in general biased, especially in noisy scenarios. We propose a modification of IQML (MIQML) that gives consistent estimates at approximately the same computational cost. In addition, an algorithm (WSF-E) with an estimation error covariance which is asymptotically identical to the asymptotic Cramér–Rao lower bound is presented. The WSF-E algorithm resembles weighted subspace fitting (WSF) or MODE, but achieves optimal performance without having to compute an eigendecomposition of the sample covariance matrix.