Blind Detection Research Articles

Blind-spot monitoring system using Lidar

Background: Most of the mishaps withs vehicles takes place because driver is unable to see objects around a vehicle in the blind spot zone. Any vehicle travelling in the blind spot is under serious threat as its presence is completely unknown to the driver. Objective: This research paper proposes a blind-spot monitoring and alert system that is devised to provide an early warning with regard to the proximity of surrounding vehicles to the driver. Methods: First, the significance of blind-spot monitoring is described. Then, the different blind-spot detection technologies compiled during research are presented. Electronics system along with software in the form of mobile Conclusion: Our contributions in this paper are (1) A detailed study for blind spot detection using Lidar. (2) Design and development of a retrofittable wireless blind-spot detection system with high accuracy. Additionally, alarm system that alerts the driver avoiding mishap has been successfully tested.

Study the Effect of eHMI Projection Distance and Contrast on People Acceptance in Blind-Spot Detection Scenario

External human-machine interaction (eHMI) road projections are a new feature for automotive lighting to improve vehicle communication with other road users. These modalities are used to draw users’ attention and awareness to specific situations. However, such advanced capabilities are still being debated to be used on the road in the context of whether or not such road projections can provide a clear and understandable message to road users in a specific scenario or lead to anticipation and change in the driving behavior. Therefore, it is necessary to investigate human factors aspects, such as the feeling of safety, useability, understanding, acceptability, and driver behavior. This study investigates the change in distance and luminance contrast and its effect on human driving behavior and acceptability in blind spot detection scenarios on the highway. A lab experiment with 12 participants is performed to analyze: understanding, satisfaction, usability, visibility, safety, workload, and driving behavior towards eHMI projection while varying projecting distance and luminance contrast. Video recordings and a designed questionnaire were used during the whole process. Results show that ego vehicle drivers prefer a projection distance between 5 to 10 m. However, a distance of 5 m is preferred by overtaking vehicle drivers in terms of visibility and safety. Luminance contrasts have no significant effect on the symbol’s visibility in 5 m and 10 m projection distances. In contrast, participants in overtaking vehicles feel difficult to understand the situation for 15 m condition, which increases their overall workload significantly (p < 0.019). No significant effect is recorded in terms of change in driving behavior.

Significance-Test Based Blind Detection for 5G

The internet of vehicles needs mobile communication systems for efficient communications. On the physical downlink control channel (PDCCH) of 5G, blind detection is performed to identify the downlink control information (DCI). Due to the uncertainty of DCI formats and PDCCH formats, the existing two-stage blind detection schemes separately decode every PDCCH code block under different DCI formats, leading to a high decoding complexity in the first stage. To reduce the detection complexity, this paper proposes an efficient DCI detection method, where a significance-test strategy is designed to detect the DCI formats. The significance-test strategy can forecast the DCI lengths without separately decoding the whole codeword, thus reducing the decoding complexity by several times. Moreover, the accuracy of the DCI detection is analyzed, with which the test scope of the test statistic is optimized for minimizing the decoding complexity on condition of meeting the detection accuracy requirements. Simulation results show that the proposed method significantly reduces the decoding complexity relatively to the existing two-stage detection schemes.

Legislation Supports Autonomous Vehicles But Not Connected Ones [Connected and Automated Vehicles

It is inspiring to notice that legislation that helps incorporate autonomous vehicles on our roads in the near future is moving forward. The National Highway Traffic Safety Administration (NHTSA), which is part of the U.S. Department of Transportation (USDoT), has integrated automated vehicles into the existing safety standards such that the text in the standards do not rely on the existence of steering wheels and driver’s seats, which may not exist in fully autonomous vehicles. In addition, the NHTSA has incorporated lane-keeping support, pedestrian automatic emergency braking, blind spot detection, and blind spot intervention into its Five-Star Safety Ratings program. Such driver-assistance technologies are the first steps toward fully autonomous vehicles but, more importantly, toward safer ones. Developing safer vehicles requires significant investments, so it is important that the legislation provide a framework that is predictable, reducing the risk of long-term commitment.

Blind Speech Watermarking Method with Frame Self-Synchronization Based on Spread-Spectrum Using Linear Prediction Residue.

State-of-the-art speech watermarking techniques enable speech signals to be authenticated and protected against any malicious attack to ensure secure speech communication. In general, reliable speech watermarking methods must satisfy four requirements: inaudibility, robustness, blind-detectability, and confidentiality. We previously proposed a method of non-blind speech watermarking based on direct spread spectrum (DSS) using a linear prediction (LP) scheme to solve the first two issues (inaudibility and robustness) due to distortion by spread spectrum. This method not only effectively embeds watermarks with small distortion but also has the same robustness as the DSS method. There are, however, two remaining issues with blind-detectability and confidentiality. In this work, we attempt to resolve these issues by developing an approach called the LP-DSS scheme, which takes two forms of data embedding for blind detection and frame synchronization. We incorporate blind detection with frame synchronization into the scheme to satisfy blind-detectability and incorporate two forms of data embedding process, front-side and back-side embedding for blind detection and frame synchronization, to satisfy confidentiality. We evaluated these improved processes by carrying out four objective tests (PESQ, LSD, Bit-error-rate, and accuracy of frame synchronization) to determine whether inaudibility and blind-detectability could be satisfied. We also evaluated all combinations with the two forms of data embedding for blind detection with frame synchronization by carrying out BER tests to determine whether confidentiality could be satisfied. Finally, we comparatively evaluated the proposed method by carrying out ten robustness tests against various processing and attacks. Our findings showed that an inaudible, robust, blindly detectable, and confidential speech watermarking method based on the proposed LP-DSS scheme could be achieved.

Joint Activity and Blind Information Detection for UAV-Assisted Massive IoT Access

Grant-free non-coherent index-modulation (NC-IM) has been recently considered as an efficient massive access scheme for enabling cost- and energy-limited Internet-of-Things (IoT) devices that transmit small data packets. This paper investigates the grant-free NC-IM scheme combined with orthogonal frequency division multiplexing for applicant to unmanned aerial vehicle (UAV)-based massive IoT access. Specifically, each device is assigned a unique non-orthogonal signature sequence codebook. Each active device transmits one of its signature sequences in the given time-frequency resources, by modulating the information in the index of the transmitted signature sequence. For small-scale multiple-input multiple-output (MIMO) deployed at the UAV-based aerial base station (BS), by jointly exploiting the space-time-frequency domain device activity, we propose a computationally efficient space-time-frequency joint activity and blind information detection (JABID) algorithm with significantly improved detection performance. Furthermore, for large-scale MIMO deployed at the aerial BS, by leveraging the sparsity of the virtual angular-domain channels, we propose an angular-domain based JABID algorithm for improving the system performance with reduced access latency. In addition, for the case of high mobility IoT devices and/or UAVs, we introduce a time-frequency spread transmission (TFST) strategy for the proposed JABID algorithms to combat doubly-selective fading channels. Finally, extensive simulation results are illustrated to verify the superiority of the proposed algorithms and the TFST strategy over known state-of-the-art algorithms.

Blind Detection and Identification of Polar Codes Based on the Parity Check Conformity

Polar code is an emerging error-correcting code. The blind detection and identification of polar codes are less studied. This letter proposes an algorithm to determine whether a bitstream is encoded with polar codes. Also, the proposed algorithm identifies the frame synchronization, code block length, rate, and the frozen-bit locations of the polar code by calculating the proposed parity check conformity of the soft-output sequence. Our method has lower computational complexity than the general methods because it does not need a decoding process. Simulation results also indicate that our algorithm performs well under low SNR.

The GPM-DPR Blind Zone Effect on Satellite-Based Radar Estimation of Precipitation over the Andes from a Ground-Based Ka-band Profiler Perspective

Abstract A vertically pointing Ka-band radar (Metek MIRA-35C) installed at the Instituto Geofísico del Perú, Atmospheric Microphysics and Radiation Laboratory (LAMAR) Huancayo Observatory, which is located at an elevation of 3.3 km MSL in the Andes Mountains of Peru, is used to investigate the effects of terrain on satellite-based precipitation measurement in the Andes. We compare the vertical structure of precipitation observed by the MIRA-35C with Ka-band radar measurements from the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) mission core satellite using an approach based on Taylor’s hypothesis of frozen turbulence that attempts to reduce the impact of spatiotemporal offsets between these two radar measurements. From 3 April 2014 to 20 May 2018, the DPR measured precipitation near LAMAR during 15 of its 157 coincident overpasses. There were six simultaneous observations with MIRA-35C. We found that the average of the DPR’s lowest clutter-free bin is 1.62 km AGL, but the presence of precipitation worsens the situation, causing a 0.4-km-deeper algorithm-detected blind zone for the DPR at the Huancayo Observatory. In the study area, the depth of the clutter layer observed with DPR often extends above the melting layer but can be highly variable, extending even as high as 5 km AGL. These results suggest that DPR estimates of stratiform precipitation over the Andes Mountains are likely underestimated because of the terrain effects on the satellite measurements and problems in its blind zone detection algorithms, highlighting the difficulty in estimating precipitation in mountainous terrain from spaceborne radar.

Smart Vehicle Monitoring and Accident Prevention System using Arm

Abstract: After drunken driving, mobile phone usage is the leading cause of accidents around the world. Also, at sudden stoppages on cross roads or due to sudden obstructions on road, natural or otherwise the driver cannot anticipate back bumper and side collision. Also, low height railing or pavements in blind spots while parking may damage the vehicle. Costly mobile phone jammers while effective render emergency communication impossible. As alcohol detection and vehicle tracking system are successfully implemented we are proposing an essential vehicle safety kit which is absent in majority of the vehicles on Indian roads. Furthermore, this can be an addition to the developing cognitive driver assistance system. The proposed system provides vehicle with safety features like SMS alert facility, blind spot detection and tail gating detector. The vehicle is equipped with angle sensors and a GSM modem interfaced with NXP ARM 2148 processor. The driver has access to a user interface consisting of LCD and switching ports. The driver may aware two modes of angle sensing with sensors located on centre of the Vehicle. A braking system can be actuated in the parking mode if the distance measured from the sensors crosses the defined threshold. In case of an emergency the driver can send a text or call from the stored numbers in the memory using the keypad. To save time and to maintain the driver’s focus on the road a default text can be sent to a default number by a single key pad entry. Call service from the system eliminates the need of using the phone and prevents driver’s loss of focus. Further the freedom to choose the number and the corresponding message to be sent is available when the vehicle is at rest. The system thus prevents accidental damage to the vehicle and its driver while eliminating the use of phone by the driver. Keywords: PIC Microcontroller, LPC2148, LCD 16*2, GSM Module, ADXL335, GPS Module

Review on Smart Vehicle Monitoring and Accident Prevention System Using Arm

Abstract: After drunken driving, mobile phone usage is the leading cause of accidents around the world. Also, at sudden stoppages on cross roads or due to sudden obstructions on road, natural or otherwise the driver cannot anticipate back bumper and side collision. Also, low height railing or pavements in blind spots while parking may damage the vehicle. Costly mobile phone jammers while effective render emergency communication impossible. As alcohol detection and vehicle tracking system are successfully implemented we are proposing an essential vehicle safety kit which is absent in majority of the vehicles on Indian roads. Furthermore, this can be an addition to the developing cognitive driver assistance system. The proposed system provides vehicle with safety features like SMS alert facility, blind spot detection and tail gating detector. The vehicle is equipped with angle sensors and a GSM modem interfaced with NXP ARM 2148 processor. The driver has access to a user interface consisting of LCD and switching ports. The driver may aware two modes of angle sensing with sensors located on centre of the Vehicle. A braking system can be actuated in the parking mode if the distance measured from the sensors crosses the defined threshold. In case of an emergency the driver can send a text or call from the stored numbers in the memory using the keypad. To save time and to maintain the driver’s focus on the road a default text can be sent to a default number by a single key pad entry. Call service from the system eliminates the need of using the phone and prevents driver’s loss of focus. Further the freedom to choose the number and the corresponding message to be sent is available when the vehicle is at rest. The system thus prevents accidental damage to the vehicle and its driver while eliminating the use of phone by the driver. Keywords: PIC Microcontroller, LPC2148, LCD 16*2, GSM Module, ADXL335, GPS Module

Multiple access interference suppression for CDMA systems via [formula omitted]-minimization

A key problem in code-division multiple access (CDMA) system is to mitigate the multiple access interference (MAI) from other users while detecting the desired user. The performance of the conventional minimum output energy (MOE) multiuser detector for CDMA system significantly degrades in the presence of signature waveform distortions induced by multipath propagation or timing asynchronism. In this paper, a robust linear programming (ROLP) algorithm for blind multiuser detection is proposed. Different from the existing MOE-based multiuser detection techniques, the proposed ROLP minimizes the ℓ∞-norm of the output to exploit the non-Gaussianity of the communication signals. To achieve robustness against signature waveform mismatch, the proposed method constrains the magnitude response of any signature vector within a specified uncertainty set to exceed unity. The uncertainty set is modeled as a rhombus, which differs from the spherical uncertainty region widely taken in the existing robust multiuser detectors. The resulting optimization problem is reformulated into a linear programming program and hence can be solved efficiently. The proposed ROLP is computationally simpler than its robust counterparts that requires solving a second-order cone programming. Simulation results demonstrate the superiority of the ROLP over several robust detectors, which indicate that its performance approaches the optimal performance bound.

A new statistical image watermark detector in RHFMs domain using beta-exponential distribution

The detection of watermarks can be achieved by statistical approaches. How to select robust modeling object, appropriate statistical model, and decision rules is one of the major issues in statistical image watermark detection. In this paper, we propose a new image watermark detector in robust fast radial harmonic Fourier moments (FRHFMs) magnitudes domain, wherein the Beta-exponential distribution model and locally most powerful (LMP) decision rule are used. We first investigate the statistical modeling of the robust FRHFMs magnitudes by the Beta-exponential distribution. It is shown that the Beta-exponential distribution model fits the empirical data more accurately than the formerly employed statistical distributions, such as the Cauchy, Weibull, BKF, and Exponential, do. Motivated by the statistical modeling results, we design a blind image watermark detector in FRHFMs magnitudes domain by using Beta-exponential distribution and LMP test. Also, we utilize the Beta-exponential model to derive the closed-form expressions for the watermark detector. We provide comparative experimental results to alternative approaches to demonstrate the advantages of the proposed image watermark detector.

High gain wide band grid array antenna for short range radar and vehicle-to-satellite communications

This paper presents the design of a Grid Array Antenna that covers both Short Range Radar applications at 24 GHz, the spectrum requirement of Ku-band transmit mode for Fixed Satellite Service and Direct Broadcast Service for Vehicle to Satellite communications. The proposed Grid Array Antenna design has vertical short radiating wire segments and long radiating wire segments loaded with parallel reactive disc structures to enhance the bandwidth. Taylor synthesis method of amplitude-tapering reduces the Side Lobe Level to −16.3 dB. The simulation and measurement results are in alignment with each other covering the bandwidth of 12.58 GHz (VSWR ≤ 2), Half Power Beam Width of 7.8° in E-plane, and 101.6° in H-plane at 24 GHz and broadside radiation for Vehicle-to-Satellite communication. The antenna parameters are analyzed for housing effect and mounted on a virtual model of a vehicle. The aforementioned results show that the proposed antenna is well suited for the spectral coverage of Vehicle-to-Satellite communication, Blind Spot Detection, and pre-impact sensing in Short Range Radar automotive communication.

Enhanced photoemission of field-assisted NEA AlGaN nanoporous array photocathode

With the increasing utilization of ultraviolet detectors, the demand for designing vacuum photoelectron emitting devices with efficient solar blind detection performance is increasing. To alleviate the phenomenon of “secondary absorption” where photoelectrons are absorbed by adjacent materials in general nanoporous arrays, a theoretical model of field-assisted AlGaN nanoporous array photocathode is established. The built-in electric field of AlGaN nanoporous is designed to promote the drift of photoelectrons to the top surface, and the external electric field is expected to increase the probability of electrons being collected by the anode. The results show that the Al0.47Ga0.53N-Al0.6Ga0.4N nanoporous array has a cut-off wavelength of 280 nm. The collection efficiency of field assisted hexagonal arranged AlGaN nanoporous array can reach up to 0.452 when the external electric field is 0.2 V/μm. Therefore, optimizing the external electric field of AlGaN nanopore array photocathode can maximize the photoemission capability of photocathode.

Robust sparse reconstruction of signals with gapped missing samples from multi-sensor recordings

Reconstructing missing samples in multi-sensor recordings is important in many applications including blind source separation, signal detection and direction of arrival estimation problem. This study proposes a method of reconstructing missing samples from multi-sensor recordings of non-stationary amplitude-modulation frequency-modulated signals using a two step procedure. In the first step the instantaneous frequency of a given multi-sensor signal is estimated using a robust and efficient method. Then the instantaneous frequency information is exploited to jointly recover the instantaneous amplitudes of multi-sensor signals. For recovering instantaneous amplitudes, the Fourier series approximation of the instantaneous amplitude is exploited. Experimental results indicate that the proposed method achieves better performance than the existing method including time-frequency filtering method, gradient descent and orthogonal matching pursuit algorithms.

Detecting Central Nodes From Low-Rank Excited Graph Signals via Structured Factor Analysis

This paper treats a blind detection problem to identify the central nodes in a graph from filtered graph signals. Unlike prior works which impose strong restrictions on the data model, we only require the underlying graph filter to satisfy a low pass property with a generic low-rank excitation model. We treat two cases depending on the low pass graph filter's strength. When the graph filter is strong low pass, i.e., it has a frequency response that drops sharply at the high frequencies, we show that the principal component analysis (PCA) method detects central nodes with high accuracy. For general low pass graph filter, we show that the graph signals can be described by a structured factor model featuring the product between a low-rank plus sparse factor and an unstructured factor. We propose a two-stage decomposition algorithm to learn the structured factor model via a judicious combination of the non-negative matrix factorization and robust PCA algorithms. We analyze the identifiability conditions for the model which lead to accurate central nodes detection. Numerical experiments on synthetic and real data are provided to support our findings. We demonstrate significant performance gains over prior works.

Construction of α-Ga2O3-ZnO heterojunction for a promoted performance applied in self-powered solar blind photodetector

Gallium oxide-based photoelectrochemical photodetectors (PEC-PDs) have received extensive attention for their natural self-powered characteristic and detection capability in solar-blind region. In this work, ZnO nanoparticles decorated α-Ga2O3 nanorods heterojunction (α-Ga2O3-ZnO) are synthesized on FTO conductive glass substrates as photoanodes for PEC-PDs. The efficient regulation of performance for α-Ga2O3-ZnO heterojunction PEC-PDs is achieved by varying the ZnO nanoparticles concentration. Experimental results show that all devices exhibit self-powered solar blind detection characteristics and the performance of ZnO nanoparticles decorated devices are all better than that of pristine α-Ga2O3. When the concentration of ZnO nanoparticles reaches to a certain value, the responsivity attains the maximum value as high as 34.2 mA/W, and the response time is as low as 0.25/0.18 s. Combined with first-principles calculations, the mechanism of the improved performance is discussed in detail. The results reveal that that the contact between α-Ga2O3 and ZnO can induce charges transfer, which constitutes a built-in electric field that acts as a driving force to separate the photogenerated carriers into different sections. This process can effectively prevent the recombination of photogenerated carriers and prolong the lifetime of e––h+, thus improve the overall detection performance finally. This work will provide meaningful guidance for the development of novel high-performance self-powered solar-blind deep-UV photodetectors.

On-Board Flickering Pixel Dynamic Suppression Method Based on Multi-Feature Fusion

The blind pixel suppression is the key preprocess to guarantee the real-time space-based infrared point target (IRPT) detection and tracking. Meanwhile, flickering pixels, as one of the blind pixels, is hard to suppress because of randomness. At present, common methods adopting a single feature generally need to accumulate dozens or hundreds of frames to ensure detection accuracy, which cannot update flickering pixels frequently. However, with low detection frequency, the flickering pixels are easily miss detected. In this paper, we propose an on-board flickering pixel dynamic suppression method based on multi-feature fusion. The visual and motion features of flickering pixels are extracted from the result of IRPT detection and tracking. Then, the confidence of flickering pixel evaluation strategy and selection mechanism of flickering pixel are introduced to fuse the above features, which achieves accurate flickering pixel suppression using a dozen frames. The experimental results evaluated on the real image of four scenarios show that the blind pixel false detection rate of the proposed method is no more than 1.02%. Meanwhile, evaluated on the simulated image, the flickering pixel miss suppression rate is no more than 2.38%, and the flickering pixel false suppression rate is 0. The proposed method could be an addition to most other IRPT detection methods, which guarantees the near-real-time and reliability of on-board IRPT detection applications.

Mirror or camera? Acceptance and valuation of camera-monitor systems

Manufacturers are increasingly considering the replacement of side-mounted rear-view mirrors with camera-monitor systems (CMS). These systems offer advantages that can improve rearward vision and safety, such as image enhancement. However, these systems must also be accepted and valuated by users. We examined acceptance of CMS, the willingness to change from rear-view mirrors to CMS, and the willingness to pay for this replacement, using an online questionnaire. We also explored the relationship between these variables using an adaption of the technology acceptance model. In total, 364 subjects completed the questionnaire. Items were aggregated using confirmatory factor analysis and factors were analyzed using (non-) parametric tests as well as path model analysis. Despite a positive attitude and high intention to use standard CMS, a combination of mirror and blind spot detection system was preferred. Subjects were willing to pay around 300 € for standard CMS, which is comparable to the preferred price of driver assistance systems. Perceived usefulness, perceived ease-of-use, and satisfaction were strong predictors of intention-to-use, but only satisfaction had a direct effect on willingness-to-change, and none of these variables predicted willingness-to-pay. Finally, customization was identified as a promising way to increase acceptance of and preference for CMS.

Joint Blind Channel Estimation, Channel Equalization, and Data Detection for Underwater Visible Light Communication Systems

In this letter, we jointly consider the problems of blind channel estimation (BCE), channel equalization and data detection in underwater visible light communication (UVLC) systems. Specifically, we propose to solve them with a model-driven deep learning (DL) approach. Inspired by the module-based signal processing methodology and communication theory, we devise a new blind receiver architecture called blind detection network (BDNet), which consists of three modules corresponding to BCE, channel equalization, and symbol demapping, respectively. Different from existing BCE schemes, the BDNet does not directly estimate the channel itself, but instead estimates the inverse channel regardless of the scalar ambiguity issue by learning the latent channel features from the received signal only. The UVLC channel effects can then be partially compensated by the zero-forcing equalization module of BDNet. Finally, the symbol demapping module recovers the transmitted symbols with the aid of the learned decision thresholds. Simulation results show the competitive bit error rate performance of BDNet in comparison to conventional pilot-aided schemes.