Linear Sensor Array Research Articles

Source Number Detectability by an Acoustic Vector Sensor Linear Array and Performance Analysis

The motivation of this work is to investigate the source number detectability by an oversampled or undersampled linear acoustic vector sensor (AVS) array. Sufficient conditions that ensure the extension of existing source number estimators and beamforming techniques from the acoustic pressure sensor (APS) array to the AVS array are established based on the linear independence of steering vectors of the AVS array, an issue closely related to the number of sources whose parameters [e.g., the direction of arrival (DOA)] can be uniquely determinable. The upper bound on the detectable number of sources with distinct DOAs under oversampled and undersampled array configurations is derived, where the difference of definitions of the distinct DOAs between the APS array and the AVS array is clarified. The number constraint on detectable sources with distinct spatial aliasing DOAs using the undersampled AVS array is also investigated. Under these conditions, advantages of eigenvalue-based source number estimators using AVS arrays are demonstrated, and the minimum description length (MDL) estimator is extended to the AVS array as an illustration to verify the established theories.

Properties of ambiguity function of frequency diverse array radar

Frequency Diverse Array (FDA) radar has recently gained substantial interest among the researchers due to its unique range-angle-dependent beampattern in contrast to angle-dependent beampattern of phased-array radar. In the simplest form of FDA radar, a uniform inter-element frequency offset is applied across the aperture of uniform linear array of sensors. This offset may be small as compared to the carrier frequency or large, giving rise to different advantages. To investigate the range and Doppler resolution of a radar system, ambiguity function has been a traditional and effective tool. In this letter, the ambiguity function of FDA radar with small frequency offset has been formulated, and some important properties of the ambiguity function have been derived. These properties can help compare its performance with the other forms of radar.

Particle velocity gradient based acoustic mode beamforming for short linear vector sensor arrays.

In this paper, a subtractive beamforming algorithm for short linear arrays of two-dimensional particle velocity sensors is described. The proposed method extracts the highly directional acoustic modes from the spatial gradients of the particle velocity field measured at closely spaced sensors along the array. The number of sensors in the array limits the highest order of modes that can be extracted. Theoretical analysis and numerical simulations indicate that the acoustic mode beamformer achieves directivity comparable to the maximum directivity that can be obtained with differential microphone arrays of equivalent aperture. When compared to conventional delay-and-sum beamformers for pressure sensor arrays, the proposed method achieves comparable directivity with 70%-85% shorter apertures. Moreover, the proposed method has additional capabilities such as high front-back (port-starboard) discrimination, frequency and steer direction independent response, and robustness to correlated ambient noise. Small inter-sensor spacing that results in very compact apertures makes the proposed beamformer suitable for space constrained applications such as hearing aids and short towed arrays for autonomous underwater platforms.

MLAOS: a multi-point linear array of optical sensors for coniferous foliage clumping index measurement.

The canopy foliage clumping effect is primarily caused by the non-random distribution of canopy foliage. Currently, measurements of clumping index (CI) by handheld instruments is typically time- and labor-intensive. We propose a low-cost and low-power automatic measurement system called Multi-point Linear Array of Optical Sensors (MLAOS), which consists of three above-canopy and nine below-canopy optical sensors that capture plant transmittance at different times of the day. Data communication between the MLAOS node is facilitated by using a ZigBee network, and the data are transmitted from the field MLAOS to a remote data server using the Internet. The choice of the electronic element and design of the MLAOS software is aimed at reducing costs and power consumption. A power consumption test showed that, when a 4000 mAH Li-ion battery is used, a maximum of 8–10 months of work can be achieved. A field experiment on a coniferous forest revealed that the CI of MLAOS may reveal a clumping effect that occurs within the canopy. In further work, measurement of the multi-scale clumping effect can be achieved by utilizing a greater number of MLAOS devices to capture the heterogeneity of the plant canopy.

Three-dimensional localization of multiple acoustic sources in shallow ocean with non-Gaussian noise

In this paper, a low-complexity algorithm SAGE-USL is presented for 3-dimensional (3-D) localization of multiple acoustic sources in a shallow ocean with non-Gaussian ambient noise, using a vertical and a horizontal linear array of sensors. In the proposed method, noise is modeled as a Gaussian mixture. Initial estimates of the unknown parameters (source coordinates, signal waveforms and noise parameters) are obtained by known/conventional methods, and a generalized expectation maximization algorithm is used to update the initial estimates iteratively. Simulation results indicate that convergence is reached in a small number of (≤10) iterations. Initialization requires one 2-D search and one 1-D search, and the iterative updates require a sequence of 1-D searches. Therefore the computational complexity of the SAGE-USL algorithm is lower than that of conventional techniques such as 3-D MUSIC by several orders of magnitude. We also derive the Cramér–Rao Bound (CRB) for 3-D localization of multiple sources in a range-independent ocean. Simulation results are presented to show that the root-mean-square localization errors of SAGE-USL are close to the corresponding CRBs and significantly lower than those of 3-D MUSIC.

Toward a Detector/Readout Architecture for the Background-Limited Far-IR/Submm Spectrograph (BLISS)

We have built and tested 32-element linear arrays of absorber-coupled transition-edge sensors (TESs) read out with a time-division SQUID multiplexer. This detector/readout architecture is designed for the background-limited far-IR/submm spectrograph (BLISS) which is a broadband (35–433 \(\upmu \)m), grating spectrometer consisting of six wavebands each with a modest resolution of R \(\sim \) 700. Since BLISS requires the effective noise equivalent power (NEP) of the TESs to equal 1 \(\times \) 10\(^{-19}\) W/Hz\(^{1/2}\), our detectors consist of very long (1–2 mm), narrow (0.4 \(\upmu \)m), and thin (0.25 \(\upmu \)m) Si\(_{x}\)N\(_{y}\) support beams that reduce the thermal conductance G between the substrate and the optical absorber. The thermistors of our lowest noise TESs consist of iridium with \(T_{c}=130\) mK. We have measured the electrical properties of arrays of these Ir TESs with various meander and straight support beams and absorber shapes and found that G is \(\sim \)30 fW/K (meander) and \(\sim \)110 fW/K (straight), the electrical NEP is 2–3 \(\times \) 10\(^{-19}\) W/Hz\(^{1/2}\) (meander and straight), and the response time \(\tau \) is 10–30 ms (meander) and 2–5 ms (straight). To reduce spurious or “dark” power from heating the arrays, we mounted the arrays into light-tight niobium boxes and added custom L/R and L/C low-pass chip filters into these boxes to intercept dark power from the bias and readout circuit. We found the average dark power equals 1.3 and 4.6 fW for the boxes with L/R and L/C chip filters, respectively. We have built arrays with \(T_{c}= 70\) mK using molybdenum/copper bilayers and are working to lower the dark power by an order of magnitude so we can demonstrate NEP\(~=~1~\times \) 10\(^{-19}\) W/Hz\(^{1/2}\) with these arrays. PACS numbers: 85.25.Pb; 95.85.Gn; 95.85.Fm; 63.22.\(+\)m

Design and Implementation of 3D Focus Stabilization for Fluorescence Microscopy

Focus stabilization is critical for many imaging modalities like TIRF, PALM and STORM. The focus stabilization device presented here, named pgFocus, is an open source and open hardware solution that can be integrated into microscopes with an existing objective positioner. pgFocus is a programmable and inexpensive circuit board consisting of a micro-controller, linear sensor array, DAC and an ADC. While pgFocus can stabilize on a single focal plane within ±3nM at 30Hz, it can also follow and correct 3D focus changes when imaging multiple Z positions. pgFocus works by monitoring the reflection of an 808nm laser beam that is internally reflected at a glass/water interface. The translation of the reflected laser beam is converted into Δ distance change between the objective and the glass/water interface. The relationship between movement of the objective and the translation of the return laser beam is determined through an calibration procedure. This Δ distance change measurement is used to modify and adjust a pass-through voltage signal that is directed to a piezo objective positioner. The pass-through voltage is continually adjusted to move the reflected laser beam back to the original focus position.View Large Image | View Hi-Res Image | Download PowerPoint Slide

Precise Positioning Based on Pixel Differential in Linear Optical Sensor Array

Abstract Precision farming emphasis on the efficient use of resources for optimizing the output. In the production of paddy, measurement of water level and the rate of rising are important factors. Sensing techniques suffer from some restrictions which restrict obtaining high accuracy and high resolution measurements such as noise of electrical sensor, sensing clear response, potential error, and environmental effects. This paper presents a non-contact method to measure position in linear motion. Moreover, this work is going to be background and concept for water level measuring system.

Distributed Ultrasonic Zoned Presence Sensing System

We present a zoned presence detection system using multiple ultrasonic array sensors. In active mode, sensors transmit consecutive bursts of sinusoidal pulses over a transmission slot in a time-division multiplexed manner. We present a transmission slot synchronization method to maintain assigned transmission slots of each sensor. The proposed method is distributed and does not rely on a central coordinator or unique identifiers for the sensors. In a transmission slot, the corresponding receiver array uses moving target processing on received echoes to derive range and direction-of-arrival, defining a zone. A tracking algorithm is used to make the zoned presence detection more robust. The presented methods are evaluated using ceiling-installed ultrasonic linear array sensors in an experimental office setup.

Second-Order Statistics-Based Multi-Parameter Estimation of Near-Field Acoustic Sources

In this paper, a new approach based on the second-order statistics (SOS) and acoustic vector sensor (AVS) array is proposed, for localization estimation of near-field acoustic narrowband sources. Firstly, we choose the centrosymmetric uniform linear-array as the AVS arrangement, and the array is consistent with the coordinate axis direction of the acoustic vector-sensor. This estimation method makes good use of the acquisition information from the AVS, such as one-dimensional sound pressure and three-dimensional particle velocity, and has shown preferable performance for the parameter estimation of direction-of-arrival (DOA) and range of target acoustic sources in the near field. The estimation algorithm expands the near-field array manifold of one single acoustic vector sensor to the acoustic vector-sensor’s uniform linear-array, and the near-field acoustic vector sensor linear array output model is deduced. The autocorrelation and cross-correlation function of the velocity field and the pressure field are used to construct the rotational invariance frame, which helps to extract the expected information. Consequently, the closed-form solutions of the incident source’s DOA and range are derived explicitly through the parameter pairing operation. The proposed method reduces the computational burden and has good spatial recognition ability and high resolution in the case of limited array elements. It also has better engineering application prospect. Eventually, the performance of the method is verified by Monte Carlo simulation experiments.

Cost-efficient speckle interferometry with plastic optical fiber for unobtrusive monitoring of human vital signs

A cost-efficient plastic optical fiber (POF) system for unobtrusive monitoring of human vital signs is presented. The system is based on speckle interferometry. A laser diode is butt-coupled to the POF whose exit face projects speckle patterns onto a linear optical sensor array. Sequences of acquired speckle images are transformed into one-dimensional signals by using the phase-shifting method. The signals are analyzed by band-pass filtering and a Morlet-wavelet-based multiresolutional approach for the detection of cardiac and respiratory activities, respectively. The system is tested with 10 healthy nonhospitalized persons, lying supine on a mattress with the embedded POF. Experimental results are assessed statistically: precisions of 98.8% ± 1.5% and 97.9% ± 2.3%, sensitivities of 99.4% ± 0.6% and 95.3% ± 3%, and mean delays between interferometric detections and corresponding referential signals of 116.6 ± 55.5 and 1299.2 ± 437.3 ms for the heartbeat and respiration are obtained, respectively.

Optimal Sensor Arrangements in Angle of Arrival (AoA) and Range Based Localization with Linear Sensor Arrays

This paper investigates the linear separation requirements for Angle-of-Arrival (AoA) and range sensors, in order to achieve the optimal performance in estimating the position of a target from multiple and typically noisy sensor measurements. We analyse the sensor-target geometry in terms of the Cramer–Rao inequality and the corresponding Fisher information matrix, in order to characterize localization performance with respect to the linear spatial distribution of sensors. Here in this paper, we consider both fixed and adjustable linear sensor arrays.

A System to Assess Grain Bag Storage Internal Environment

<abstract><title><italic>Abstract.</italic></title> Alternative grain storage systems have been adopted when traditional bin storage capacity is exceeded or unavailable. One method is grain bag (silo bag) storage systems. This system has been used for silage or high-moisture grain storage, has been employed for dry grain in other regions of the world, and is gaining acceptance in the U.S. Little peer-reviewed research is available to describe the grain bag internal environment and its effect on grain quality. In the reviewed studies, there was no consistency in the approach taken to characterize the grain bag environment. The objectives of this study were to design and fabricate a sensor system to measure the internal environment of a grain bag, to apply this sensor system under field conditions, and describe instrumentation considerations for grain bags. An instrumentation system of linearly mounted thermocouples and relative humidity (RH) sensors was developed. The linear sensor arrays have a sampling interval as low as 30 s. The system RMS error for measuring temperature (T) and RH were 0.6°C and 3.1%, respectively. The system was field tested and recorded internal environmental parameters for corn stored in grain bags. A defined peripheral layer that strongly responded to external ambient conditions was identified, which was expected. Temperatures were stratified within the peripheral region. To characterize the internal temperature of a grain bag, temperature measurements need to be taken at a minimum of three depths: at the internal bag surface, within the peripheral temperature region, and within the core temperature region. Collected T and RH data were used to describe the grain equilibrium moisture content. There were errors associated with both the measurement and calculation of EMC. Errors caused by measurement error were less than 2% for all temperatures between 20% and 80% RH. Researchers, producers, and grain managers could use a similar system to monitor grains stored using this alternative storage system and to make effective management decisions.

고속충돌 시험용 지능형 다중 카메라 시스템 개발

A single-crystal sapphire is used as a transparent bulletproof window material; however, few studies have investigated the dynamic behavior and fracture properties under high-speed impact. High-speed and high-resolution sequential images are required to study the interaction of the bullet with the brittle ceramic materials. In this study, a device is developed to capture the sequence of high-speed impact/penetration phenomena. This system consists of a speed measurement device, a microprocessor-based camera controller, and multiple CCD cameras. By using a linear array sensor, the speed-measuring device can measure a small (diameter: up to 1 2 mm) and fast (speed: up to Mach 3) bullet. Once a bullet is launched, it passes through the speed measurement device where its time and speed is recorded, and then, the camera controller computes the exact time of arrival to the target during flight. Then, it sends the trigger signal to the cameras and flashes with a specific delay to capture the impact images sequentially. It is almost impossible to capture high-speed images without the estimation of the time of arrival. We were able to capture high-speed images using the new system with precise accuracy.

Mixed Near-Field and Far-Field Sources Localization Using the Uniform Linear Sensor Array

Based on the ESPRIT-like and polynomial rooting methods, a high-performance and low computational cost localization algorithm for the mixed near-field sources (NFS) and far-field sources (FFS) is proposed using the uniform linear sensor array. First, we combine the steering vectors of the two subarrays to eliminate the range parameters and then yield a new steering vector, which only contains direction-of-arrival (DOA) information. Second, based on the ESPRIT-like and polynomial rooting methods, the DOAs of all NFSs and FFSs are obtained from the new steering vector. Third, with the DOA estimates, the range parameters are estimated depending on the polynomial rooting method again; and further according to the number of the closest to the unit circle roots, we can determine the number of sources at the same DOA direction. Finally, based on the size of the range parameters, the types (NFS or FFS) of sources can be confirmed. In addition, the proposed algorithm does not require the high-order statistics or any 1- or 2-D search and thus has low computational cost. Meanwhile, it makes full use of the array aperture and obtains outstanding estimation performance for both the DOA and range parameters. Moreover, the proposed algorithm avoids parameter match procedure. Numerical experiments show the performance of the proposed algorithm in this paper.

Locating Point of Impact on an Anisotropic Cylindrical Surface Using Acoustic Beamforming Technique

A beamforming array technique with four sensors is applied to a cylindrical geometry for detecting point of impact. A linear array of acoustic sensors attached to the plate record the waveforms of Lamb waves generated at the impact point with individual time delay. A beamforming technique in conjunction with an optimization scheme that incorporates the direction dependent guided Lamb wave speed in cylindrical plates is developed. The optimization is carried out using the experimentally obtained wave speed as a function of propagation direction. The maximum value in the beamforming plot corresponds to the predicted point of impact. The proposed technique is experimentally verified by comparing the predicted points with the exact points of impact on a cylindrical aluminum plate and a cylindrical composite shell. For randomly chosen points of impact the beamforming technique successfully predicts the location of the acoustic source.

DOA estimation for periodically modulated sources

This paper considers the problem of direction-of-arrival estimation for periodically modulated signals using one uniform linear array of sensors. By means of modulating the sources with periodic modulation sequences, we can form a series of linear equations relating the autocorrelation matrices of the received data and the outer products of the scaled steering vectors. Solving these linear equations yields a group of Hermitian matrices formed from the outer products of the scaled steering vectors. Then taking the eigendecomposition of these Hermitian matrices, we can obtain all the scaled steering vectors. By utilizing a special structure of the scaled steering vectors, we can find the directions of signals impinging on the array. We also examine the relation of the modulation sequences and the estimation performance, and a design of the modulation sequences to resist the effect of spatial noise is proposed. One merit of the proposed method is that it can be used in the scenarios of more sources than sensors. The simulation result also shows that it has the capacity to distinguish the closely spaced sources.

GEOMETRIC CORRECTION OF AIRBORNE LINEAR ARRAY IMAGE BASED ON BIAS MATRIX

Abstract. As the linear array sensor has great potential in disaster monitoring, geological survey, the quality of the image geometric correction should be guaranteed. The primary focus of this paper is to present a new method correcting airbone linear image based on the bias matrix,which is bulit by describing and analysing the errors of airbone linear image included the misalignment. The bias matrix was considered as additional observations to the traditional geometric correction model in our method. And by using control points which have both image coordinate and object coordinate, the solving equation from geometric correction model can be established and the bias matrix can be calculated by adjustment strategy. To avoid the singularity problem in the calculating process, this paper uses quaternion to describe the image's attitude and rotation instead of traditional calculating method which is structured by the Euler angle. Finally, geometric correction of airborne linear array image with high accuracy based on bias matrix can be achieved.

Functional demonstration of a compact silicon diffractive sensor for toluene

A compact silicon diffractive sensor detecting toluene in solution is demonstrated. This sensor is fabricated in silicon-on-insulator and utilizes a standard telecommunications wavelength. In-plane diffraction gratings enable micrometer-scale device sizes and intensity-based (as opposed to spectral-based) detection for increased integrability. Precise grating design enables 2-D sensor arrays without the addition of separate optical splitters. Detection of the relative diffracted and transmitted intensities is independent of attenuation and is thus robust. This proof-of-concept sensor is shown to measure toluene concentrations as low as 100 parts per million, corresponding to a refractive index change of 3×10(-4). In addition, a linear sensor array with individual sensor addressability and 2-D array capability is demonstrated. The characteristics of this sensor type make it promising for field-deployable lab-on-a-chip applications.

A new regularization technique for limited-view sound-speed imaging

Reconstructing sound-speed maps from the limited view offered by a linear array of ultrasonic sensors has been a long-standing challenge in medical diagnostics and nondestructive evaluation. Because of the limited range of angles that can be used to interrogate the volume beneath the array, the inverse problem of retrieving sound-speed maps from scattering measurements is highly ill-posed. The missing angles cause significant artifacts that degrade the image by altering the values of sound speed and producing ghost features. This paper introduces the virtual image space component iterative technique (VISCIT), which addresses the limited-view problem by introducing a new regularization technique which iteratively compensates for the missing components by applying an adaptive threshold to the reconstruction. The effectiveness of the method in yielding high-accuracy sound-speed maps is demonstrated using a complex numerical phantom and validated experimentally with an agar phantom. It is shown that sound-speed contrast as low as 1.3% is readily detectable, thus paving the way for more sensitive and selective detection of damage precursors and early stage diseases.