Angle Resolution Research Articles

Multi-Tone Phase Coding of Interaural Time Difference for Sound Source Localization With Spiking Neural Networks

Mammals exhibit remarkable capability of detecting and localizing sound sources in complex acoustic environments by using binaural cues in the spiking manner. Emulating the auditory process for sound source localization (SSL) by mammals, we propose a computational model for accurate and robust SSL under the neuromorphic spiking neural network (SNN) framework. The center of this model is a Multi-Tone Phase Coding (MTPC) scheme, which encodes the interaural time difference (ITD) between binaural pure tones into discriminative spike patterns that can be directly classified by SNNs. As such, SSL can be implemented as an event-driven task on highly efficient, neuromorphic parallel processors. We evaluate the proposed computational model on a directional audio dataset recorded from a microphone array in a realistic acoustic environment with background noise, obstruction, reflection, and other interferences. We report superior localization capability with a mean absolute error (MAE) of 1.02 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> or 100% classification accuracy with an angle resolution of 5 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> , which surpasses other SNN-based biologically plausible neuromorphic approaches by a relatively large margin and on par with human performance in similar tasks. This study opens up many application opportunities in human-robot interaction where energy efficiency is crucial. As a case study, we successfully deploy the proposed SSL system in a robotic platform to track the speaker and orient the robot's attention.

Parameter Estimation and Target Detection of Phased-MIMO Radar Using Capon Estimator

Phased-Multiple Input Multiple Output (PMIMO) radar is multi-antenna radar that combines the main advantages of the phased array (PA) and the MIMO radars. The advantage of the PA radar is that it has a high directional coherent gain making it suitable for detecting distant and small radar cross-section (RCS) targets. Meanwhile, the main advantage of the MIMO radar is its high waveform diversity gain which makes it suitable for detecting multiple targets. The combination of these advantages is manifested by the use of overlapping subarrays in the transmit (Tx) array to improve the performance of parameters such as angle resolution and detection accuracy at amplitude and phase proportional to the maximum number of detectable targets. This paper derives a parameter estimation formula with Capon's adaptive estimator and evaluates it for the performance of these parameters. Likewise, derivation for expressions of detection performance such as the probability of false alarm and the probability of detection is also given. The effectiveness and validation of its performance are compared to conventional estimator for other types of radars in terms of the effect of the number of target angles, the RCS of targets, and variations in the number of subarrays at Tx of this radar. Meanwhile, the detection performance is evaluated based on the effect of Signal to Noise Ratio (SNR) and the number of subarrays at Tx. The evaluation results of the estimator show that it is superior to the conventional estimator for estimating the parameters of this radar as well as the detection performance. Having no sidelobe makes this estimator strong against the influence of interference and jamming so that it is suitable and attractive for the design of radar systems. Root mean square error (RMSE) on magnitude detection from LS and Capon estimators were 0.033 and 0.062, respectively. Meanwhile, the detection performance for this radar has the probability of false alarm above 10-4 and the probability of detection of more than 99%.

Generalized Ambiguity Function for FDA Radar Joint Range, Angle and Doppler Resolution Evaluation

Differs from conventional phased-array, frequency diverse array (FDA) employs a frequency increment across the array elements and thus produces a range-angle-dependent beampattern. This additional range dependence finds applications in target detection/localization, high-resolution synthetic aperture radar (SAR) imaging, and SAR deceptive jamming. To capture the essence behind those applications, we analyze the range, angle, and Doppler resolution capabilities of FDA radar signal via ambiguity function. As conventional ambiguity function is defined for a single-input single-output (SISO) signal, we extend it to the generalized ambiguity function for FDA radar signal, parameterized with the range, angle, and Doppler shifts of a target. Both theoretical analysis and numerical results show that the FDA radar with a large frequency increment has potentials in high-resolution ranging but will suffer from additional range ambiguity within the range bin and Doppler ambiguity. Moreover, the use of frequency increment brings FDA radar a virtual transmit aperture but decreases the directional gain.

STAP Based on Toeplitz Covariance Matrix Reconstruction for Airborne Radar

We consider the problem of clutter covariance matrix (CCM) estimation for space-time adaptive processing (STAP) radar in the small sample. In this paper, a fast efficient algorithm for CCM reconstruction is proposed to overcome this shortcoming for the linear structure. Particularly, we present a low-rank matrix recovery (LRMR) question about CCM estimation based on the Toeplitz structure of CCM and the prior knowledge of the noise. The closed-form solution is obtained by relaxing the nonconvex LRMR problem that the trace norm replaces the rank norm. The target can then be efficiently detected by using the recovered CCM according to the STAP theorem. We also analyze the algorithm model under the linear structure in the presence of unknown mutual coupling. It is shown that our method can obtain accurate CCM in the small sample, with even higher accuracy than the traditional algorithms in the same number of samples. It also can reduce the coupling effect and obtain more degrees of freedom (DOF) with limited sensors and pulses by utilizing sparse linear structure (SLS) and improve angle and Doppler resolutions. Finally, numerical simulations have verified the effectiveness of the proposed method in comparison with some of the existing methods.

Parametric Design of a Microwave Radiometer for Land Surface Temperature Retrieval from Moon-Based Earth Observation Platform

Increasing attention is being paid to the monitoring of global change, and remote sensing is an important means for acquiring global observation data. Due to the limitations of the orbital altitude, technological level, observation platform stability and design life of artificial satellites, spaceborne Earth observation platforms cannot quickly obtain global data. The Moon-based Earth observation (MEO) platform has unique advantages, including a wide observation range, short revisit period, large viewing angle and spatial resolution; thus, it provides a new observation method for quickly obtaining global Earth observation data. At present, the MEO platform has not yet entered the actual development stage, and the relevant parameters of the microwave sensors have not been determined. In this work, to explore whether a microwave radiometer is suitable for the MEO platform, the land surface temperature (LST) distribution at different times is estimated and the design parameters of the Moon-based microwave radiometer (MBMR) are analyzed based on the LST retrieval. Results show that the antenna aperture size of a Moon-based microwave radiometer is suitable for 120 m, and the bands include 18.7, 23.8, 36.5 and 89.0 GHz, each with horizontal and vertical polarization. Moreover, the optimal value of other parameters, such as the half-power beam width, spatial resolution, integration time of the radiometer system, temperature sensitivity, scan angle and antenna pattern simulations are also determined.

Research on the Influence of Metamaterials on Single Photon LiDAR

Single photon light detection and ranging (LiDAR) has the advantages of high angle and distance resolution, great concealment, a strong anti-active jamming capability, small volume, and light mass, and has been widely applied in marine reconnaissance, obstacle avoidance, chemical warfare agent detection, and navigation. With the rapid development of metamaterials, the performance of a single photon LiDAR system would be improved by optimizing the core devices in the system. In this paper, we first analyzed the performance index of the single photon LiDAR and discovered the potential of metamaterials in improving the system performance. Then, the influence of metamaterials on the core devices of the single photon LiDAR were discussed, including lasers, scanning devices, optical lenses, and single photon detectors. As a result, we have concluded that through effective light field modulation, metamaterial technology might enhance the performance innovation of the single photon LiDAR.

Clinical Characteristics and Prognosis of Adult Orbital Cellulitis in a Tertiary General Hospital.

Purpose Adult orbital cellulitis (OC) occurs relatively rarely, and comprehensive studies that retrospectively evaluate OC are lacking. Here, we aimed to examine the clinical characteristics and prognosis of OC in a tertiary general hospital. Methods Between October 2010 and May 2019, patients presenting with clinical symptoms of OC in a tertiary general hospital were analyzed in this retrospective study. Twenty-six cases were identified for a detailed review. In these cases, 16 males and 10 females were diagnosed with orbital cellulitis by clinical characteristics and multimodal examinations. We divided patients into three groups: (1) patients secondary to rhinosinusitis, (2) patients secondary to endogenous infection(s) without endophthalmitis, and (3) patients secondary to endophthalmitis. For each group, age, gender, eye type, combined systemic diseases, clinical presentation, leukocyte count, blood culture, diagnostic imaging, therapeutic methods, length of stay, time of postoperation, and patient prognosis were analyzed in detail. Results There were no significant differences regarding age, gender, preoperative leukocyte count, exophthalmia, blood culture, treatment, or visual changes within the three groups (P < 0.05). There were significant differences, however, in postoperative leukocyte count and ophthalmoplegia between the three groups (P < 0.05). The preoperative and postoperative logarithms of the minimum resolution angle scored by the best-corrected visual acuity (LogMAR BCVA) of group 3 were statistically significant compared to group 1 and group 2 (P < 0.05). Conclusion We confirmed that the prognosis of OC patients combined with systemic diseases was poor. Patients with OC secondary to endophthalmitis infrequently experience ophthalmoplegia; however, these patients still have poor visual outcomes. Patients cultured positive for Klebsiella pneumoniae infection may not be associated with liver abscess. The level of leukocytes may indicate the condition of the disease.

Object Detection for Unmanned Aerial Vehicle Camera via Convolutional Neural Networks

The object tracking alongside the image segmentation have recently become a particular significance in satellite and aerial imagery. The latest achievements in this field are closely related to the application of the deep-learning algorithms and, particularly, convolutional neural networks (CNNs). Supplemented by the sufficient amount of the training data, CNNs provide the advantageous performance in comparison to the classical methods based on Viola-Jones or support vector machines. However, the application of CNNs for the object detection on the aerial images faces several general issues that cause classification error. The first one is related to the limited camera shooting angle and spatial resolution. The second one arises from the restricted dataset for specific classes of objects that rarely appear in the captured data. This article represents a comparative study on the effectiveness of different deep neural networks for detection of the objects with similar patterns on the images within a limited amount of the pretrained datasets. It has been revealed that YOLO ver. 3 network enables better accuracy and faster analysis than region convolution neural network (R-CNN), Fast R-CNN, Faster R-CNN, and SSD architectures. This has been demonstrated on the example of “Stanford dataset,” “DOTA v-1.5,” and “xView 2018 Detection” datasets. The following metrics on the accuracy have been obtained for the YOLO ver. 3 network: 89.12 mAP (Stanford dataset), 80.20 mAP (DOTA v-1.5), and 78.29 (xView 2018) for testing; and 85.51 mAP (Stanford dataset), 79.28 (DOTA v-1.5), and 79.92 (xView 2018) on validation with the analysis speed of 26.82 frames/s.

Guidance Method on a Target within a Dense Group

The guidance method on a separate target within a dense group for the implementation of trajectory control is proposed. This control technique solves the problem of transition from the typical angle resolution determined by the width of the directional pattern to the Doppler frequency resolution based on the Doppler beam sharpening effect with subsequent minimization of the current miss. The obtained law has been analyzed and the results of simulation are presented.

The InflateSAR Campaign: Evaluating SAR Identification Capabilities of Distressed Refugee Boats

Most of the recent research in the field of marine target detection has been concentrating on ships with large metallic parts. The focus of this work is on much more challenging targets represented by small rubber inflatables. They are of importance, since in recent years they have largely been used by migrants to cross the Mediterranean Sea between Libya and Europe. The motivation of this research is to mitigate the ongoing humanitarian crisis at Europe’s southern borders. These boats, packed with up to 200 people, are in no way suitable to cross the Mediterranean Sea or any other big water body and are in distress from the moment of departure. The establishment of a satellite-based surveillance infrastructure could considerably support search and rescue missions in the Mediterranean Sea, reduce the number of such boats being missed and mitigate the ongoing death in the open ocean. In this work we describe and analyze data from the InflateSAR acquisition campaign, wherein we gathered multiple-platform SAR imagery of an original refugee inflatable. The test site for this campaign is a lake which provides background clutter that is more predictable. The analysis considered a sum of experiments, enabling investigations of a broad range of scene settings, such as the vessel’s orientation, superstructures and speed. We assess their impact on the detectability of the chosen target under different sensor parameters, such as polarimetry, resolution and incidence angle. Results show that TerraSAR-X Spotlight and Stripmap modes offer good capabilities to potentially detect those types of boats in distress. Low incidence angles and cross-polarization decrease the chance of a successful identification, whereas a fully occupied inflatable, orthogonally oriented to the line of sight, seems to be better visible than an empty one. The polarimetric analyses prove the vessel’s different polarimetric behavior in comparison with the water surface, especially when it comes to entropy. The analysis considered state-of-the-art methodologies with single polarization and dual polarization channels. Finally, different metrics are used to discuss whether and to which extent the results are applicable to other open ocean datasets. This paper does not introduce any vessel detection or classification algorithm from SAR images. Rather, its results aim at paving the way to the design and the development of a specially tailored detection algorithm for small rubber inflatables.

Evaluación de un protocolo automatizado para la obtención de medidas morfométricas de huevos de aves a partir de fotografías digitales

Evaluation of a protocol for automated extraction of morphometric measurements from avian eggs using digital photography As many ecomorphological studies are limited by the time required to gather manual measurement data, automatizing the process is an important focus of methodological innovations. We developed, implemented and validated a protocol for the semi–automated extraction of a set of morphometric variables of egg size and shape from digital pictures. The protocol was implemented in R language as a web app called OvometriK. After binarizing and calibrating images, this protocol uses geometric and trigonometric functions to calculate eleven egg variables. We tested calculations in several ways, assuming contour continuity or using voxel counts. Application was validated with geometric shapes and 30 manually–measured chicken eggs. Mathematical validation with spheres showed that the algorithm provided high precision diameter measures, with a correlation of 99.9 %. Average estimation error was 1.4 %. The mathematical volume estimation was underestimated by 27 %, while voxels were underestimated by only 6 %. Differences between manual egg measurements of diameters and those obtained from images was less than 3 mm (4 %). Correlation between estimated volume and measured by silica gel filling was higher than 90 % using the voxel count method. Neither inclination angle or picture resolution had significant effects on precision (3.2 % maximum difference). Measures showed high repeatability and represent a significant saving in processing time. This new protocol represents an improvement on previous programs regarding limitations of platform, accessibility and number of variables. Furthermore, its flexibility and openness means it can be adapted to other specific applications.

Determination of singular value truncation threshold for regularization in ill-posed problems

Appropriate regularization parameter specification is the linchpin for solving ill-posed inverse problems when regularization method is applied. This paper presents a novel technique to determine cut off singular values in the truncated singular value decomposition (TSVD) methods. Simple formulae are presented to calculate the index number of the singular value, beyond which all the smaller singular values and the corresponding vectors are truncated. The determination method of optimal truncation threshold is firstly theoretically inferred. Two-dimensional inverse problems processing Radon transform are then exemplified. Formulae to solve the problem with insufficient image resolution and projection angle number are derived by the currently proposed method. The results show that accuracy of the current method is similar to that of TSVD but with much superior efficiency. On the other hand, insufficiency in input data affects the output accuracy of the inverse solution, a least square method can be engaged to establish formulae calculating the truncation threshold. For an insufficient set of input data, the percentage difference between inversely reconstructed signal and TSVD reconstructed signal is about 3%. The current formulae offer reliable and more efficient approach to calculate the truncation threshold when TSVD is applied to solve inverse problems with known system characteristics.

Visual performance after bilateral toric extended depth-of-focus IOL exchange targeted for micromonovision.

To evaluate overall patient satisfaction, spectacle independence, binocular visual acuity, rotational stability, prevalence of optical phenomena, and decentration and tilt after bilateral toric extended depth-of-focus intraocular lens (EDOF IOL) implantation targeted for micromonovision. Department of Ophthalmology, Hanusch Hospital, Vienna, Austria. Prospective case series. The study included 52 eyes of 26 patients with regular corneal astigmatism from 0.75 to 2.60 diopters (D) that were implanted bilaterally with a toric EDOF IOL targeted for micromonovision. Postoperative visual acuity, astigmatism reduction, rotation, tilt, decentration, spectacle independence, patient satisfaction, and photic phenomena were assessed. For the 52 eyes studied, binocular means expressed in logarithm of the minimum angle resolution for postoperative corrected distance, uncorrected distance, uncorrected intermediate, and uncorrected near visual acuities were -0.10 (±0.12), -0.01 (±0.13), 0.01 (±0.14), and 0.13 (±0.14), respectively. Mean refractive astigmatism reduction was 1.31 ± 0.67 D resulting in a mean refractive cylinder of 0.47 ± 0.46 D at the 3-month visit. Mean postoperative rotation was 3.5 ± 3.5 degrees, at the 3-month time point. Most prevalent dysphotopsia were halos, starburst, and glare affecting 6 (23%), 6 (23%), and 5 (19%) of 26 patients, respectively; 20 (77%) of 26 patients reported spectacle independence, with 19 (95%), 19 (95%), and 14 (70%) of 20 patients questioned being satisfied with distance, intermediate, and near vision, respectively. Toric EDOF IOL implantation targeted for micromonovision resulted in reliable reduction of preoperative astigmatism with a high degree of postoperative rotational predictability and centration, enabling functional distance, intermediate, and near vision, which manifested itself in high patient satisfaction.

A deep learning approach to multi-track location and orientation in gaseous drift chambers

Accurate measuring the location and orientation of individual particles in a beam monitoring system is of particular interest to researchers in multiple disciplines. Among feasible methods, gaseous drift chambers with hybrid pixel sensors have the great potential to realize long-term stable measurement with considerable precision. In this paper, we introduce deep learning to analyze patterns in the beam projection image to facilitate three-dimensional reconstruction of particle tracks. We propose an end-to-end neural network based on segmentation and fitting for feature extraction and regression. Two segmentation branches, named binary segmentation and semantic segmentation, perform initial track determination and pixel-track association. Then pixels are assigned to multiple tracks, and a weighted least squares fitting is implemented with full back-propagation. Besides, we introduce a center-angle measure to judge the precision of location and orientation by combining two separate factors. The initial position resolution achieves 8.8 μm for the single track and 11.4 μm (15.2 μm) for the 1–3 tracks (1–5 tracks), and the angle resolution achieves 0.15°and 0.21°(0.29°) respectively. These results show a significant improvement in accuracy and multi-track compatibility compared to traditional methods.

Fiber Bragg grating sensors for in-situ temperature measurement on bending a flexible planar supercapacitor

The state of charge (SoC) in a flexible planar supercapacitor is dependent both on in-situ temperature rise as well as its bending angle. Thus there is a need for measurement of rising in temperature of the supercapacitor on bending conditions. The present work demonstrates the applicability of fiber Bragg grating (FBG) sensors for in-situ temperature measurement on bending in flexible planar supercapacitors. For this purpose, two FBG sensors with diameter 125 μm and 40 μm were inserted into a flexible planar supercapacitor at a location away from the bending axis. The FBG with 40 μm diameter was coated with conductive silver ink to enhance the temperature sensitivity and the diameter of this FBG after coating was found to be 80 μm. The planar supercapacitor consisted of multi-walled carbon nanotube adsorbed on filter paper as electrodes and NH4CN as an electrolyte. The temperature and bend sensitivities for FBG with 125 μm diameter was found to be 10 pm/°C and 17 pm/° respectively whereas for the FBG with 80 μm diameter the temperature and bend sensitivities were 16 pm/°C and 21 pm/° respectively. The measurement resolution for temperature and bending angles were found to be 0.2 °C and 0.4°, respectively. Maximum measurement errors of 0.9 °C and 0.8° in the measurement range 0−70 °C and 0−50° respectively were found. The high sensitivity and resolution, along with low measurement error in in-situ temperature measurement on bending revealed that the proposed method was suitable for monitoring the SoC in flexible planar supercapacitors. The study, conducted on the variation of in-situ temperature rise on bending with specific capacitance and equivalent series resistance, opens up new possibility towards the development of supercapacitor temperature management systems for flexible planar supercapacitor.

P‐63: Measurements of Viewing Angle and Angular Resolution of Electronic Holographic Display

We propose a new measurement scheme for angular characteristics of electronic holographic displays. Specifically, viewing angle and angular resolution are analyzed and quantitatively measured to evaluate the optical characterization and visual quality of holographic display. These angular substances play an essential role that constructs three‐dimensional volume images in space. In this work, we make a use of direction‐selective test pattern hologram to measure its contrast modulation of reconstructed holographic images from different angular direction views. Experimental results are provided to verify the feasibility of our proposed measurement method and to evaluate the objective performance of angular characteristics in holographic display.

A Novel Camera-Free Eye Tracking Sensor for Augmented Reality Based on Laser Scanning

Next generation AR glasses require a highly integrated, high-resolution near-eye display technique such as focus-free retinal projection to enhance usability. Combined with low-power eye-tracking, such glasses enable better user experience and performance. We propose a novel and robust low-power eye-tracking sensor for integration into retinal projection systems. In our approach, a MEMS micro mirror scans an IR laser beam over the eye region and the scattered light is received by a photodiode. The advantages of our approach over typical VOG systems are its high integration capability and low-power consumption, which qualify our approach for next generation AR glasses. Here, we present a mathematical framework to estimate the achievable gaze angle resolution of our approach. We further show the viability of the proposed eye-tracking sensor based on a laboratory setup and discuss power consumption and gaze angle resolution compared to typical eye-tracking techniques.

The Impact of Spin–Orbit Interaction on the Image States of High‐Z Materials

Due to many important technical developments over the past two decades angle‐resolved (inverse) photoemission has become the method of choice to study experimentally the bulk and surface‐related electronic states of solids in the most detailed way. Due to new powerful photon sources as well as efficient analyzers and detectors extremely high energy and angle resolution are achieved nowadays for spin‐integrated and also for spin‐resolved measurements. These developments allow in particular to explore the influence of spin–orbit coupling on image potential states of simple metals like Ir, Pt, or Au with a high atomic number as well as new types of materials as for example topological insulators. Herein, fully relativistic angle‐ and spin‐resolved inverse photoemission calculations are presented that make use of the spin‐density matrix formulation of the one‐step model. This way a quantitative analysis of all occupied and unoccupied electronic features in the vicinity of the Fermi level is achieved for a wide range of excitation energies. Using this approach, in addition, it is possible to deal with arbitrarily ordered but also disordered systems. Because of these features, the one‐step or spectral function approach to photoemission permits detailed theoretical studies on a large variety of interesting solid‐state systems.

Sensitivity analysis of the numerical aspect of the SWAN for the tropical cyclone wave simulations in the Gulf of Oman

The simulating waves nearshore (SWAN) model is designed for the wave simulations of nearshore areas. In the present study, this model has been applied for simulating tropical cyclone–generated waves in the Gulf of Oman. The wind and pressure field of the Gonu cyclone were reproduced by means of the cyclone wind generation (CWG) tool of the Mike DHI within multiple inputs, including the geographical location of the center of the cyclone, the radius of maximum wind speed, the pressure at the center of the cyclone, the neutral pressure, the start time of the cyclone period, and the maximum wind speed. The required specifications of the cyclone were obtained from the Joint US Typhoon Warning Center (JTWC) and introduced into the CWG module. With the purpose of achieving optimal settings of the model, a sensitivity analysis of the time step, grid resolution, and angle resolution has been conducted. Sensitivity analysis demonstrates that effects of time step have a significant impact on the results, while generally speaking angel and grid resolution are less impressive.

A high-resolution area-change-based capacitive MEMS tilt sensor

Tilt sensors have been widely used in many applications, such as instrumentation leveling, oil drilling and structural health monitoring. With the rapid development of the micro-electromechanical system (MEMS) technology, MEMS accelerometer-based high-performance tilt sensors are capable of replacing conventional tilt sensors in most of application fields. High-sensitivity MEMS resonant accelerometers (MRAs) are fully qualified for tilt sensing. However, MRA chips have to be vacuum packaged and require complex circuits; therefore, they are difficult to be miniaturized and commercialized. In this case, this paper introduces a commercial-oriented capacitive MEMS accelerometer for tilt sensing with both high-resolution and compact size. The proposed MEMS sensor utilizes simplified fabrication processes, the area-change-based capacitive displacement transducer and the capacitance-to-voltage conversion application specific integrated circuit (ASIC) for low-cost, high-sensitivity, low power consumption and miniaturization. The developed MEMS sensor has a package dimension of 14 mm × 14 mm × 3.6 mm with a single +5 V power supply and analog voltage output. Several evaluation experiments have been conducted with the results showing that the developed MEMS tilt sensor has a full measurement range of ±180°, a linear measurement range of ±30° with a nonlinearity of ±2.8%, a sensitivity of 33.6 mV/°, a noise floor of 2 × 10−4°/√Hz, a bandwidth of 100 Hz and an angle resolution of 7 × 10−4° with an integral time of 0.5 s. Compared with other commercial MEMS tilt sensors, the proposed sensor has a better resolution, a lower noise floor, a larger bandwidth, a lower power consumption and a smaller package. The simplified fabrication process and high performance suggest the developed MEMS tilt sensor is promising to be competitive in the market.