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The discrete Fourier transform (DFT) is the most commonly used signal processing method in modern digital sensor design for signal study and analysis. It is often implemented in hardware, such as a field programmable gate array (FPGA), using the fast Fourier transform (FFT) algorithm. The frequency resolution (i.e., frequency bin size) is determined by the number of time samples used in the DFT, when the digital sensor's bandwidth is fixed. One can vary the sensitivity of a radio frequency receiver by changing the number of time samples used in the DFT. As the number of samples increases, the frequency bin width decreases, and the digital receiver sensitivity increases. In some applications, it is useful to compute an ensemble of FFT lengths; e.g., 2 P − j for j = 0 ,   1 ,   2 ,   ... ,   J , where j is defined as the spectrum level with frequency resolution   2 j · Δ f . Here Δ f is the frequency resolution at j = 0 . However, calculating all of these spectra one by one using the conventional FFT method would be prohibitively time-consuming, even on a modern FPGA. This is especially true for large values of P ; e.g., P ≥ 20 . The goal of this communication is to introduce a new method that can produce multi-resolution spectrum lines corresponding to sample lengths   2 P − j for all J + 1 levels, concurrently, while one long 2 P -length FFT is being calculated. That is, the lower resolution spectra are generated naturally as by-products during the computation of the 2 P -length FFT, so there is no need to perform additional calculations in order to obtain them. [ABSTRACT FROM AUTHOR]

The hardware-accelerated time–frequency distribution calculation is one of the commonly used methods to analyze and present the information from intercepted radio frequency signals in modern ultra-wideband digital receiver (DRX) designs. In this paper, we introduce the piecewise constant window blocking FFT (PCW-BFFT) method. The purpose of this work is to show the generation of spectrograms (formed by a number of spectrum lines) using a very large number of samples (N) in an FFT frame for each spectrum line calculation. In the PCW-BFFT, the N samples are grouped into K consecutive time slots, and each slot has M number of samples. As soon as the M samples in the current time slot are available from a high-speed analog-to-digital convertor (ADC), the frequency information will be obtained using K M-point FFTs. Since each time the FFT frame hops one time slot for the next spectrum line calculation, the frequency information obtained from a time slot will be reused in many spectrum line calculations, as long as these spectrum lines share those samples in the time slot. Although the use of the time domain PCW introduces spikes in the frequency spectrum of the window, the levels of those spikes are still much lower than the first side lobe level of a rectangular window. Using a Gaussian window as an example, the highest spike level can be lower than the main lobe level by at least 38 dB. The PCW-BFFT method allows a DRX to produce multiple spectrograms concurrently with different analysis window widths when the time domain samples become available continuously from the ADC. This paper presents the detailed derivation process of the PCW-BFFT method and demonstrates the use of the method with simulation results. The hardware implementation process will be reported in another paper. The computer simulation results show that long signals with slowly changing frequencies over time can be depicted on the spectrograms with wide analysis windows, and short pulses and signals with rapidly changing instantaneous frequencies can be captured in the narrow analysis window spectrograms. [ABSTRACT FROM AUTHOR]

The objective of this study is to design the hull-mounted sonar dome of a ship. The goal is to reduce the ship total resistance and improve the flow field around the sonar dome for the ship design speed. OpenFOAM 6 was applied to analyze the viscous flow around the ship bow and then optimize the sonar dome geometry. The length, width and depth of the original geometry were maintained. Only the local geometry was fine-tuned considering the back slope and front tip by using Rhinoceros 6. The verification and validation was performed for the original hull form against towing tank resistance data. The grid independence was checked for the optimal design in different design stages. To ensure less influence on the interior equipment installation and to be able to re-use the non-steel dome part, the best resistance reduction is almost 2%. With a larger allowance of shape deformation, the maximal reduction could reach slightly higher than 3%. The flow field is improved for smaller flow separation and vortex, and less fluid nose in sonar detection is expected. The main reason of the resistance reduction is the decrease of the pressure component. In conclusion, a sonar dome design procedure is proposed, and an optimal geometry is suggested. [ABSTRACT FROM AUTHOR]

The uniaxial piezoelectric sensor was developed to overcome the problem of reflecting the output charge of the piezoelectric element as a combination of vectors in the three stress directions. The work performance of the uniaxial piezoelectric sensor under varying load patterns and load rates was investigated. The sensor was embedded in concrete to monitor stress, and its elastic modulus was used as the intermediate bridge to establish the correlation between the embedded sensor and the external sensor. Furthermore, a correction factor for the charge transformation strain was suggested to overcome the mismatching of the sensor's medium and the concrete. Considering related circumstances, a new stress monitoring method based on a uniaxial piezoelectric sensor was proposed, which can achieve stress whole-process monitoring in concrete and confining stress monitoring in the reinforced concrete column. The results reveal that through the proposed method, the output charge curve of the sensor has a substantial overlap with the stress waveform and high fitting linearity. The work performance of the sensor was stable, and its sensitivity was not affected by loading rate and load pattern. The sensor was embedded in concrete and can coordinate with the concrete deformation. The correction factor of strain obtained by the sensor embedded in concrete was 1.07. The relationship between the charge produced by the embedded sensor and its external calibration sensitivity may be used to implement the whole process of stress monitoring in concrete. [ABSTRACT FROM AUTHOR]

One’s position has become an important piece of information for our everyday lives in a smart city. Currently, a position can be obtained easily using smartphones that is equipped with low-cost Global Navigation Satellite System (GNSS) chipsets with accuracy varying from 5 m to 10 m. Differential GNSS (DGNSS) is an efficient technology that removes the majority of GNSS errors with the aid of reference stations installed at known locations. The sub-meter accuracy can be achieved when applying the DGNSS technology on the advanced receivers. In 2016, Android has opened the accesses of raw GNSS measurements to developers. However, most of the mid and low-end smartphones only provide the data using the National Marine Electronics Association (NMEA) protocol. They do not provide the raw measurements, and thus do not support the DGNSS operation either. We proposed a DGNSS infrastructure that correct the standalone GNSS position of smartphones using the corrections from the reference station. In the infrastructure, the position correction is generated considering the GNSS satellite IDs that contribute to the standalone solution in smartphones, and the position obtained is equivalent to the solution of using the range-domain correction directly. To serve a large number of smartphone users, a Client/Server architecture is developed to cope with a mass of DGNSS positioning requests efficiently. The comparison of the proposed infrastructure against the ground truth, for all field tests in open areas, showed that the infrastructure achieves the horizontal positioning accuracy better than 2 m. The improvement in accuracy can reach more than 50% for the test in the afternoon. The infrastructure brings benefits to applications that require more accuracy without requiring any hardware modifications. [ABSTRACT FROM AUTHOR]

In this paper, a novel range compression algorithm for enhancing range resolutions of a passive Global Navigation Satellite System-based Synthetic Aperture Radar (GNSS-SAR) is proposed. In the proposed algorithm, within each azimuth bin, firstly range compression is carried out by correlating a reflected GNSS intermediate frequency (IF) signal with a synchronized direct GNSS base-band signal in the range domain. Thereafter, spectrum equalization is applied to the compressed results for suppressing side lobes to obtain a final range-compressed signal. Both theoretical analysis and simulation results have demonstrated that significant range resolution improvement in GNSS-SAR images can be achieved by the proposed range compression algorithm, compared to the conventional range compression algorithm. [ABSTRACT FROM AUTHOR]

Commercial RGB-D sensors such as Kinect and Structure Sensors have been widely used in the game industry, where geometric fidelity is not of utmost importance. For applications in which high quality 3D is required, i.e., 3D building models of centimeter-level accuracy, accurate and reliable calibrations of these sensors are required. This paper presents a new model for calibrating the depth measurements of RGB-D sensors based on the structured light concept. Additionally, a new automatic method is proposed for the calibration of all RGB-D parameters, including internal calibration parameters for all cameras, the baseline between the infrared and RGB cameras, and the depth error model. When compared with traditional calibration methods, this new model shows a significant improvement in depth precision for both near and far ranges. [ABSTRACT FROM AUTHOR]

RGB-D sensors (sensors with RGB camera and Depth camera) are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks including limited measurement ranges (e.g., within 3 m) and errors in depth measurement increase with distance from the sensor with respect to 3D dense mapping. In this paper, we present a novel approach to geometrically integrate the depth scene and RGB scene to enlarge the measurement distance of RGB-D sensors and enrich the details of model generated from depth images. First, precise calibration for RGB-D Sensors is introduced. In addition to the calibration of internal and external parameters for both, IR camera and RGB camera, the relative pose between RGB camera and IR camera is also calibrated. Second, to ensure poses accuracy of RGB images, a refined false features matches rejection method is introduced by combining the depth information and initial camera poses between frames of the RGB-D sensor. Then, a global optimization model is used to improve the accuracy of the camera pose, decreasing the inconsistencies between the depth frames in advance. In order to eliminate the geometric inconsistencies between RGB scene and depth scene, the scale ambiguity problem encountered during the pose estimation with RGB image sequences can be resolved by integrating the depth and visual information and a robust rigid-transformation recovery method is developed to register RGB scene to depth scene. The benefit of the proposed joint optimization method is firstly evaluated with the publicly available benchmark datasets collected with Kinect. Then, the proposed method is examined by tests with two sets of datasets collected in both outside and inside environments. The experimental results demonstrate the feasibility and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

The pseudolite system is a good alternative for indoor positioning systems due to its large coverage area and accurate positioning solution. However, for common Global Positioning System (GPS) receivers, the pseudolite system requires some modifications of the user terminals. To solve the problem, this paper proposes a new pseudolite-based indoor positioning system architecture. The main idea is to receive real-world GPS signals, repeat each satellite signal and transmit those using indoor transmitting antennas. The transmitted GPS-like signal can be processed (signal acquisition and tracking, navigation data decoding) by the general receiver and thus no hardware-level modification on the receiver is required. In addition, all Tx can be synchronized with each other since one single clock is used in Rx/Tx. The proposed system is simulated using a software GPS receiver. The simulation results show the indoor positioning system is able to provide high accurate horizontal positioning in both static and dynamic situations. [ABSTRACT FROM AUTHOR]

This article presents the hardware implementation and a behavioral model-based RF system modeling and simulation (M&S) study of compressive sensing (CS) based 2D angle-of-arrival (AoA) measurement system for 2–18 GHz radar electronic support measures (RESM). A 6-channel ultra-wideband RF digital receiver was first developed using a PXIe-based multi-channel digital receiver paired with a 6-element random-spaced 2D cavity-backed-spiral-antenna array. Then the system was tested in an open lab environment. The measurement results showed that the system can measure AoA of impinging signals from 2–18 (GHz) with overall RMSE of estimation at 3.60, 2.74, 1.16, 0.67 and 0.56 (deg) in L, S, C, X and Ku bands, respectively. After that, using the RF high-fidelity M&S (RF HF-M&S) approach, a 6-channel AoA measurement system behavioral model was also developed and studied using a radar electronic warfare (REW) engagement scenario. The simulation result showed that the airborne AoA measurement system could successfully measure an S-band ground-based target acquisition radar signal in the dynamic REW environment. Using the RF HF-M&S model, the applicability of the system in other frequencies within 2–18 (GHz) was also studied. The simulation results demonstrated that the airborne AoA measurement system can be used for 2–18 GHz RESM applications. [ABSTRACT FROM AUTHOR]

In this paper, a novel signal processing algorithm for mitigating the radar blind speed problem of moving target indication (MTI) for frequency modulated continuous wave (FMCW) multi-target tracking radars is proposed. A two-phase staggered pulse repetition interval (PRI) solution is introduced to the FMCW radar system. It is implemented as a time-varying MTI filter using twice the hardware resources as compared to a uniform PRI MTI filter. The two-phase staggered PRI FMCW waveform is still periodic with a little more than twice the period of the uniform PRI radar. We also propose a slow time signal integration scheme for the radar detector using the post-fast Fourier transformation Doppler tracking loop. This scheme introduces 4.77 dB of extra signal processing gain to the signal before the radar detector compared with the original uniform PRI FMCW radar. The validation of the algorithm is done on the field programmable logic array in the loop test bed, which accurately models and emulates the target movement, line of sight propagation and radar signal processing. A simulation run of tracking 16 s of the target movement near or at the radar blind speed shows that the total degradation from the raw post-fast Fourier transformation received signal to noise ratio is about 2 dB. With a 20 dB post-processing signal to noise ratio of the proposed algorithm for the moving target at around a 20 km range and with about a − 3.5 dB m2 radar cross section at a 1.5 GHz carrier frequency, the tracking errors of the two-dimensional angles with a 4 × 4 digital phased array are less than 0.2 degree. The range tracking error is about 28 m. [ABSTRACT FROM AUTHOR]

Vehicle re-identification plays an important role in cross-camera tracking and vehicle search in surveillance videos. Large variance in the appearance of the same vehicle captured by different cameras and high similarity of different vehicles with the same model poses challenges for vehicle re-identification. Most existing methods use a center proxy to represent a vehicle identity; however, the intra-class variance leads to great difficulty in fitting images of the same identity to one center feature and the images with high similarity belonging to different identities cannot be separated effectively. In this paper, we propose a sampling strategy considering different viewpoints and a multi-proxy constraint loss function which represents a class with multiple proxies to perform different constraints on images of the same vehicle from different viewpoints. Our proposed sampling strategy contributes to better mine samples corresponding to different proxies in a mini-batch using the camera information. The multi-proxy constraint loss function pulls the image towards the furthest proxy of the same class and pushes the image from the nearest proxy of different class further away, resulting in a larger margin between decision boundaries. Extensive experiments on two large-scale vehicle datasets (VeRi and VehicleID) demonstrate that our learned global features using a single-branch network outperforms previous works with more complicated network and those that further re-rank with spatio-temporal information. In addition, our method is easy to plug into other classification methods to improve the performance. [ABSTRACT FROM AUTHOR]

In this study, a head-mounted device was developed to track the gaze of the eyes and estimate the gaze point on the user's visual plane. To provide a cost-effective vision tracking solution, this head-mounted device is combined with a sized endoscope camera, infrared light, and mobile phone; the devices are also implemented via 3D printing to reduce costs. Based on the proposed image pre-processing techniques, the system can efficiently extract and estimate the pupil ellipse from the camera module. A 3D eye model was also developed to effectively locate eye gaze points from extracted eye images. In the experimental results, average accuracy, precision, and recall rates of the proposed system can achieve an average of over 97%, which can demonstrate the efficiency of the proposed system. This study can be widely used in the Internet of Things, virtual reality, assistive devices, and human-computer interaction applications. [ABSTRACT FROM AUTHOR]