A high-speed high-resolution sampling system is the crucial part in wideband radar receivers. A 10.4-GS/s 12-bit wideband sampling system based on TIADC technique is designed in this letter. The acquisition function is implemented on a VPX platform. The storage function is implemented on a standard 19-inch rack server. The sampled data is transmitted at high speed through optical fibers between them. A mixed calibration method based on perfect reconstruction is adopted to compensate channel mismatches of wideband TIADC system. For sinusoidal signals from 100MHz to 5000MHz, more than 46-dB SNDR and 56-dB SFDR can be obtained in this sampling system. This letter provides a high-speed and high-resolution acquisition scheme for direct intermediate frequency sampling wideband digital receivers.

An offline sensor gain-phase errors calibration method for a linear array using a source in unknown location is proposed. The proposed method is realized through three steps. First, based on the observed covariance matrix, we construct a function related to direction, and it is proved that when the function takes the minimum value, the corresponding value should be the direction of the calibration source. Second, the direction of calibration source is estimated by locating the valley from the constructed function. Third, the gain-phase errors are obtained based on the estimated direction. The proposed method offers a number of advantages. First, the accurate direction measurement of the calibration source is not required. Second, only one calibration source needs to be arranged. Third, it does not require an iterative procedure or a two-dimensional (2D) spectral search. Fourth, the method is applicable to linear arrays, not only to uniform linear arrays (ULAs). Numerical simulations are presented to verify the efficacy of the proposed method.

This paper reports a large-scale study that aims to understand how mobile application (app) vulnerabilities are associated with software libraries. We analyze both free and paid apps. Studying paid apps was quite meaningful because it helped us understand how differences in app development/maintenance affect the vulnerabilities associated with libraries. We analyzed 30k free and paid apps collected from the official Android marketplace. Our extensive analyses revealed that approximately 70%/50% of vulnerabilities of free/paid apps stem from software libraries, particularly from third-party libraries. Somewhat paradoxically, we found that more expensive/popular paid apps tend to have more vulnerabilities. This comes from the fact that more expensive/popular paid apps tend to have more functionality, i.e., more code and libraries, which increases the probability of vulnerabilities. Based on our findings, we provide suggestions to stakeholders of mobile app distribution ecosystems.

We present an accurate and easy-to-use multi-sensor fusion toolbox for autonomous vehicles. It includes a ‘target-less’ multi-LiDAR (Light Detection and Ranging), and Camera-LiDAR calibration, sensor fusion, and a fast and accurate point cloud ground classifier. Our calibration methods do not require complex setup procedures, and once the sensors are calibrated, our framework eases the fusion of multiple point clouds, and cameras. In addition we present an original real-time ground-obstacle classifier, which runs on the CPU, and is designed to be used with any type and number of LiDARs. Evaluation results on the KITTI dataset confirm that our calibration method has comparable accuracy with other state-of-the-art contenders in the benchmark.

Phase interferometer using baseline composed by uniform linear array (ULA) with stable phase center for estimating the angle of arrival (AOA) is always employed in the direction finding (DF) system. However, the phase center of antenna element could vary with the incident angle, frequency, multipath and so on. To deal with these problems, a novel method is proposed in this paper to calibrate the phase center over ultra-wideband (UWB). Meanwhile, the restrictions of this method are discussed. Numerical simulations reveal that higher accuracy and larger unambiguous angle range can be obtained by the proposed method.

The consistent alignment of point clouds obtained from multiple scanning positions is a crucial step for many 3D modeling systems. This is especially true for environment modeling. In order to observe the full scene, a common approach is to rotate the scanning device around a rotation axis using a turntable. The final alignment of each frame data can be computed from the position and orientation of the rotation axis. However, in practice, the precise mounting of scanning devices is impossible. It is hard to locate the vertical support of the turntable and rotation axis on a common line, particularly for lower cost consumer hardware. Therefore the calibration of the rotation axis of the turntable is an important step for the 3D reconstruction. In this paper we propose a novel calibration method for the rotation axis of the turntable. With the proposed rotation axis calibration method, multiple 3D profiles of the target scene can be aligned precisely. In the experiments, three different evaluation approaches are used to evaluate the calibration accuracy of the rotation axis. The experimental results show that the proposed rotation axis calibration method can achieve a high accuracy.

All digital phased arrays generate multiple beams concurrently through the digital beam forming technique, which features digital processing with multiple identical receiving/transmitting channels in RF or microwave frequencies. However, the performance of this process strongly depends on accurately matching the amplitude and phase of the channels, as mismatching is likely to degrade radar performance. In this paper, we present a method to calibrate receiving array by using NCO phase increasing algorithm, which simplifies array system by removing the external far-field calibration signals often needed in array systems. Both analysis and simulation results suggest that the proposed method attains better calibration performance than existing approaches, even with a low SNR input signal. Experiments also varify that the proposed calibration method is effective and achieves a desired radiation pattern. We can further boost calibration accuracy and reduce calibration time by programming NCO phase width and NCO phase resolution.

In the library, recognizing the activity of the reader can better uncover the reading habit of the reader and make book management more convenient. In this study, we present the design and implementation of a reading activity recognition approach based on passive RFID tags. By collecting and analyzing the phase profiling distribution feature, our approach can trace the reader's trajectory, recognize which book is picked up, and detect the book misplacement. We give a detailed analysis of the factors that can affect phase profiling in theory and combine these factors with relevant activities. The proposed approach recognizes the activities based on the amplitude of the variation of phase profiling, so that the activities can be inferred in real time through the phase monitoring of tags. We then implement our approach with off-the-shelf RFID equipment, and the experiments show that our approach can achieve high accuracy and efficiency in activity recognition in a real-world situation. We conclude our work and further discuss the necessity of a personalized book recommendation system in future libraries.

Background: The applying of third-party libraries is an integral part of many applications. But the libraries choosing is time-consuming even for experienced developers. The automated recommendation system for libraries recommendation is widely researched to help developers to choose libraries. Aim: from software engineering aspect, our research aims to give developers a reliable recommended list of third-party libraries at the early phase of software development lifecycle to help them build their development environment faster; and from technical aspect, our research aims to build a generalizable recommendation system framework which combines collaborative filtering and topic modeling techniques, in order to improve the performance of libraries recommendation significantly. Our works on this research: 1) we design a hybrid methodology to combine collaborative filtering and LDA text mining technology; 2) we build a recommendation system framework successfully based on the above hybrid methodology; 3) we make a well-designed experiment to validate the methodology and framework which use the data of 1,013 mobile application projects; 4) we do the evaluation for the result of the experiment. Conclusions: 1) hybrid methodology with collaborative filtering and LDA can improve the performance of libraries recommendation significantly; 2) based on the hybrid methodology, the framework works very well on the libraries recommendation for helping developers' libraries choosing. Further research is necessary to improve the performance of the libraries recommendation including: 1) use more accurate NLP technologies improve the correlation analysis; 2) try other similarity calculation methodology for collaborative filtering to rise the accuracy; 3) on this research, we just bring the time-series approach to the framework and make an experiment as comparative trial, the result shows that the performance improves continuously, so in further research we plan to use time-series data-mining as the basic methodology to update the framework.

In this paper, we propose a novel method to extrinsically calibrate a camera to a 3D reference object that is not directly visible from the camera. We use a human cornea as a spherical mirror and calibrate the extrinsic parameters from the reflections of the reference points. The main contribution of this paper is to present a cornea-reflection-based calibration algorithm with a simple configuration: five reference points on a single plane and one mirror pose. In this paper, we derive a linear equation and obtain a closed-form solution of extrinsic calibration by introducing two ideas. The first is to model the cornea as a virtual sphere, which enables us to estimate the center of the cornea sphere from its projection. The second is to use basis vectors to represent the position of the reference points, which enables us to deal with 3D information of reference points compactly. We demonstrate the performance of the proposed method with qualitative and quantitative evaluations using synthesized and real data.

This paper describes a broadband low phase noise VCO implemented in 0.13 µm CMOS process. A 1-bit switched varactor and a 4-bit capacitor array are adopted in cooperation with the automatic frequency calibration (AFC) circuit to lower the VCO tuning gain (KVCO), with a measured AFC time of 6 µs. Several noise reduction techniques are exploited to minimize the phase noise of the VCO. Measurement results show the VCO generates a high frequency range from 11.37 GHz to 14.8 GHz with a KVCO of less than 270 MHz/V. The prototype exhibits a phase noise of -114.6 dBc/Hz @ 1 MHz at 14.67 GHz carrier frequency and draws 10.5 mA current from a 1.2 V supply. The achieved figure-of-merits (FoM=-186.9dBc/Hz, FoMT=-195.3dBc/Hz) favorably compares with the state-of-the-art.

An improved radiometric calibration algorithm by extending the Mitsunaga and Nayar least-square minimization based algorithm with two major ideas is presented. First, a noise & outlier removal procedure based on the analysis of brightness transfer function is included for improving the algorithm's capability on handling noise and outlier in least-square estimation. Second, an alternative minimization formulation based on weighted least square is proposed to improve the weakness of least square minimization when dealing with biased distribution observations. The performance of the proposed algorithm with regards to two baseline algorithms is demonstrated, i.e. the classical least square based algorithm proposed by Mitsunaga and Nayar and the state-of-the-art rank minimization based algorithm proposed by Lee et al. From the results, the proposed algorithm outperforms both baseline algorithms on both the synthetic dataset and the dataset of real-world images.

This paper presents a 1024-QAM OFDM signal capable WLAN receiver in 65nm CMOS technology. Thermal noise-based IQ frequency-independent mismatch correction and IQ frequency-dependent mismatch correction with baseband loopback are proposed for the self-calibration in the receiver. The measured image rejection ratio of the self-calibration is -56.3dB. The receiver achieves the extremely low EVM of -37.1dB even with wide channel bandwidth of 80MHz and has the ability to receive the 1024-QAM signal. The result indicates that the receiver is extendable for the 802.11ax compliant receiver that supports a higher density modulation scheme of MIMO.

In this paper, we propose a method to generate a three-dimensional (3D) thermal map and RGB + thermal (RGB-T) images of a scene from thermal-infrared and RGB images. The scene images are acquired by moving both a RGB camera and an thermal-infrared camera mounted on a stereo rig. Before capturing the scene with those cameras, we estimate their respective intrinsic parameters and their relative pose. Then, we reconstruct the 3D structures of the scene by using Direct Sparse Odometry (DSO) using the RGB images. In order to superimpose thermal information onto each point generated from DSO, we propose a method for estimating the scale of the point cloud corresponding to the extrinsic parameters between both cameras by matching depth images recovered from the RGB camera and the thermal-infrared camera based on mutual information. We also generate RGB-T images using the 3D structure of the scene and Delaunay triangulation. We do not rely on depth cameras and, therefore, our technique is not limited to scenes within the measurement range of the depth cameras. To demonstrate this technique, we generate 3D thermal maps and RGB-T images for both indoor and outdoor scenes.

This paper presents a self-calibrating dynamic latched comparator with a stochastic offset voltage detector that can be realized by using simple digital circuitry. An offset voltage of the comparator is compensated by using a statistical calibration scheme, and the offset voltage detector uses the uncertainty in the comparator output. Thanks to the simple offset detection technique, all the calibration circuitry can be synthesized using only standard logic cells. This paper also gives a design methodology that can provide the optimal design parameters for the detector on the basis of fundamental statistics, and the correctness of the design methodology was statistically validated through measurement. The proposed self-calibrating comparator system was fabricated in a 180 nm 1P6M CMOS process. The prototype achieved a 38 times improvement in the three-sigma of the offset voltage from 6.01 mV to 158 µV.

A current mirror circuit is often used in Gm-cells and current amplifiers in order to obtain high linearity and high accurate current gain. However, it is expected that a threshold voltage mismatch between transistors pair in the current mirror affects these performances in recent scaled technologies. In this paper, negative effects caused by the mismatch in the current mirror are considered and a new calibration technique for the mismatch issues is proposed. In the current mirror without the mismatch, the high-linearity operation is provided by distortion canceling under the condition that the transistors have the same operating points. The threshold voltage mismatch disturbs the cancellation, therefore the distortion is appeared. In order to address the issue, a new calibration technique using a backgating effect is considered. This calibration can reduce the threshold voltage mismatch directly by controlling the body bias voltage with DACs. According to simulation results with Monte Carlo sampling in 65nm CMOS process, owing to the proposed calibration, the worst HD2 and HD3 are improved by 18.4dB and 11.6dB, respectively. In addition, the standard deviation of the current gain is reduced from 399mdB to 34mdB.

The rotating element electric field vector (REV) method is a classical measurement technique for phased array calibration. Compared with other calibration methods, it requires only power measurements. Thus, the REV method is more reliable for operating phased array calibration systems. However, since the phase of each element must be rotated from 0 to 2π, the conventional REV method requires a large number of measurements. Moreover, the power of composite electric field vector doesn't vary significantly because only a single element's phase is rotated. Thus, it can be easily degraded by the receiver noise. A simplified REV method combined with Hadamard group division is proposed in this paper. In the proposed method, only power measurements are required. All the array elements are divided into different groups according to the group matrix derived from the normalized Hadamard matrix. The phases of all the elements in the same group are rotated at the same time, and the composite electric field vector of this group is obtained by the simplified REV method. Hence, the relative electric fields of all elements can be obtained by a matrix equation. Compared with the conventional REV method, the proposed method can not only reduce the number of measurements but also improve the measurement accuracy under the particular range of signal to noise ratio(SNR) at the receiver, especially under low and moderate SNRs.

In this letter, a novel on-orbit estimation and calibration method of GPS antenna geometry offsets for attitude determination of LEO satellites is proposed. Both baseline vectors in the NED coordinate system are achieved epoch-by-epoch firstly. Then multiple epochs' baseline vectors are united to compute all the offsets via an UKF for a certain long time. After on-orbit estimation and calibration, instantaneous and accurate attitude can be achieved. Numerical results show that the proposed method can obtain the offsets of each baseline in all directions with high accuracy estimation and small STDs, and effective attitudes can be achieved after antenna geometry calibration using the estimated offsets. The high accuracy give the proposed scheme a strong practical-oriented ability.

An optimal design method for a sub-ranging Analog-to-Digital Converter (ADC) based on stochastic comparator is demonstrated by performing theoretical analysis of random comparator offset voltages. If the Cumulative Distribution Function (CDF) of the comparator offset is defined appropriately, we can calculate the PDFs of the output code and the effective resolution of a stochastic comparator. It is possible to model the analog-to-digital conversion accuracy (defined as yield) of a stochastic comparator by assuming that the correlations among the number of comparator offsets within different analog steps corresponding to the Least Significant Bit (LSB) of the output transfer function are negligible. Comparison with Monte Carlo simulation verifies that the proposed model precisely estimates the yield of the ADC when it is designed for a reasonable target yield of >0.8. By applying this model to a stochastic comparator we reveal that an additional calibration significantly enhances the resolution, i.e., it increases the Number of Bits (NOB) by ∼ 2 bits for the same target yield. Extending the model to a stochastic-comparator-based sub-ranging ADC indicates that the ADC design parameters can be tuned to find the optimal resource distribution between the deterministic coarse stage and the stochastic fine stage.

SAR tomography is one of the methods that can perform 3-dimensional (3-D) imaging with multiple SAR datasets by using the Direction-of-arrival (DOA) estimation technique to estimate the height distribution of scatterers. Several reports on SAR tomography have been issued. However, experimental results of the SAR tomography by the Pi-SAR2-X, Japanese airborne SAR operated by the NICT, have not been reported yet. This paper is the first to report the results of experiments on the Japanese SAR platform. High-resolution 2-dimensional image can be obtained by the X-band SAR. However the image is generated by projecting 3-D objects in to a 2-D image plane, hence the target responses having the same slant-range distance locate at the same image pixel. This is well known as the layover problem. When we employ the X-band SAR tomography, we can obtain 3-D high-resolution images without the layover and also foreshortening problem. It will be useful for disaster damage monitoring, especially in urban areas. The main difficulty of the SAR tomography comes from the phase error caused by inaccurate flight-path data. In many cases, the dataset are preprocessed and compensated so as to parallelize their flight-path to carry out the phase calibration and the DOA estimation easily. However, it is often difficult for common users to obtain such preprocessed datasets. In this paper, we propose a simple calibration method by using a flat-surface area with known altitude. Experiments show that the proposed method is effective for the Pi-SAR2-X standard products without parallelized preprocessing or precise flight-path information.