Emotion modeling and recognition has drawn extensive attention from disciplines such as psychology, cognitive science, and, lately, engineering. Although a significant amount of research has been done on behavioral modalities, less explored characteristics include the physiological signals. This work brings to the table the ECG signal and presents a thorough analysis of its psychological properties. The fact that this signal has been established as a biometric characteristic calls for subject-dependent emotion recognizers that capture the instantaneous variability of the signal from its homeostatic baseline. A solution based on the empirical mode decomposition is proposed for the detection of dynamically evolving emotion patterns on ECG. Classification features are based on the instantaneous frequency (Hilbert-Huang transform) and the local oscillation within every mode. Two experimental setups are presented for the elicitation of active arousal and passive arousal/valence. The results support the expectations for subject specificity, as well as demonstrating the feasibility of determining valence out of the ECG morphology (up to 89 percent for 44 subjects). In addition, this work differentiates for the first time between active and passive arousal, and advocates that there are higher chances of ECG reactivity to emotion when the induction method is active for the subject.

ECG Pattern Analysis for Emotion Detection

Internet of Things (IoT) connects sensing devices to the Internet for the purpose of exchanging information. Location information is one of the most crucial pieces of information required to achieve intelligent and context-aware IoT systems. Recently, positioning and localization functions have been realized in a large amount of IoT systems. However, security and privacy threats related to positioning in IoT have not been sufficiently addressed so far. In this paper, we survey solutions for improving the robustness, security, and privacy of location-based services in IoT systems. First, we provide an in-depth evaluation of the threats and solutions related to both global navigation satellite system (GNSS) and non-GNSS-based solutions. Second, we describe certain cryptographic solutions for security and privacy of positioning and location-based services in IoT. Finally, we discuss the state-of-the-art of policy regulations regarding security of positioning solutions and legal instruments to location data privacy in detail. This survey paper addresses a broad range of security and privacy aspects in IoT-based positioning and localization from both technical and legal points of view and aims to give insight and recommendations for future IoT systems providing more robust, secure, and privacy-preserving location-based services.

Robustness, Security and Privacy in Location-Based Services for Future IoT: A Survey

Indoor location based services challenges, requirements and usability of current solutions

This paper presents the utilization of empirical mode decomposition (EMD) of hyperspectral images to increase the classification accuracy using support vector machine (SVM)-based classification. EMD has been shown in the literature to be particularly suitable for nonlinear and nonstationary signals and is used in this paper to decompose hyperspectral image bands into several intrinsic mode functions (IMFs) and a final residue. EMD is utilized in this paper to improve hyperspectral-image-classification accuracy by effectively exploiting the feature that EMD performs a decomposition that is spatially adaptive with respect to intrinsic features. This paper presents two different approaches for improved hyperspectral image classification making use of EMD. In the first approach, IMFs corresponding to each hyperspectral image band are obtained and the sums of lower order IMFs are used as new features for classification with SVM. In the second approach, the pieces of information contained in the first and second IMFs of each hyperspectral image band are combined using composite kernels for SVM classification with higher accuracy.

Empirical Mode Decomposition of Hyperspectral Images for Support Vector Machine Classification

Jamming is the act of intentionally directing powerful electromagnetic waves toward a victim receiver with the ultimate goal of denying its operations. This paper describes the main types of Global Navigation Satellite System (GNSS) jammers and reviews their impact on GNSS receivers. A survey of state-of-the-art methods for jamming detection is also provided. Different detection approaches are investigated with respect to the receiver stage where they can be implemented.

/pdf/impact-and-detection-of-gnss-jammers-on-consumer-grade-589qxlw98s.pdf

Impact and Detection of GNSS Jammers on Consumer Grade Satellite Navigation Receivers

The ever-increasing public interest in location and positioning services has originated a demand for higher performance global navigation satellite systems (GNSSs). In order to achieve this incremental performance, the estimation of line-of-sight (LOS) delay with high accuracy is a prerequisite for all GNSSs. The delay lock loops (DLLs) and their enhanced variants (i.e., feedback code tracking loops) are the structures of choice for the commercial GNSS receivers, but their performance in severe multipath scenarios is still rather limited. In addition, the new satellite positioning system proposals specify the use of a new modulation, the binary offset carrier (BOC) modulation, which triggers a new challenge in the code tracking stage. Therefore, in order to meet this emerging challenge and to improve the accuracy of the delay estimation in severe multipath scenarios, this paper analyzes feedback as well as feedforward code tracking algorithms and proposes the peak tracking (PT) methods, which are combinations of both feedback and feedforward structures and utilize the inherent advantages of both structures. We propose and analyze here two variants of PT algorithm: PT with second-order differentiation (Diff2), and PT with Teager Kaiser (TK) operator, which will be denoted herein as PT(Diff2) and PT(TK), respectively. In addition to the proposal of the PT methods, the authors propose also an improved early-late-slope (IELS) multipath elimination technique which is shown to provide very good mean-time-to-lose-lock (MTLL) performance. An implementation of a noncoherent multipath estimating delay locked loop (MEDLL) structure is also presented. We also incorporate here an extensive review of the existing feedback and feedforward delay estimation algorithms for direct sequence code division multiple access (DS-CDMA) signals in satellite fading channels, by taking into account the impact of binary phase shift keying (BPSK) as well as the newly proposed BOC modulation, more specifically, sine-BOC(1,1) (SinBOC(1,1)), selected for Galileo open service (OS) signal. The state-of-art algorithms are compared, via simulations, with the proposed algorithms. The main focus in the performance comparison of the algorithms is on the closely spaced multipath scenario, since this situation is the most challenging for estimating LOS component with high accuracy in positioning applications.

/pdf/code-tracking-algorithms-for-mitigating-multipath-effects-in-2q7lhzvyww.pdf

Code tracking algorithms for mitigating multipath effects in fading channels for satellite-based positioning

Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS) or the future European satellite navigation system Galileo. Multipath is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function used for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal diversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellite-receiver transit time offset of the Line-Of-Sight (LOS) signal for the receiver's position estimate. Therefore, the multipath problem has been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the development of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely, the Reduced Search Space Maximum Likelihood (RSSML) delay estimator, which is capable of mitigating the multipath effects reasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error contribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal reference correlation functions with certain amplitude(s), phase(s), and delay(s) of the multipath signal. It also incorporates a threshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall of RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of other delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK-) and Sine Binary Offset Carrier- (SinBOC-) modulated signals is also analyzed in closed loop model with the new Composite BOC (CBOC) modulation chosen for Galileo E1 signal. The simulation results show that the RSSML achieves the best multipath mitigation performance in a uniformly distributed two-to-four paths Rayleigh fading channel model for all three modulated signals.

/pdf/advanced-multipath-mitigation-techniques-for-satellite-based-5f10qad8hh.pdf

Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications

Integration of different positioning systems such as wireless local area networks (WLAN) and INS has proven to be the most promising approach for navigation in global navigation satellite system challenging environments. However, the integrated solution suffers from the errors induced by the sensors in the INS and the low availability and infrastructure dependency of the WLAN. Visual aiding is a complementary method for augmenting these systems, because it suffers from errors and availability problems of a different nature. We introduce the concept of a "visual gyroscope" and a "visual odometer," based on recovering user information by tracking the feature motion between consecutive images. All calculations are of sufficiently low complexity to be adoptable for navigation with current smartphones. The camera orientation is observed using the vanishing point locations, and this information is transformed into user heading change information and also used for visual odometer calculations. The visual odometer retrieves the camera translation information based on a special camera configuration and the motion of the matched scale-invariant feature transform features. The performance of both of these tools is evaluated. Experiments in selected environments have proven that visual aiding with a visual gyroscope and visual odometer improves the two-dimensional navigation solution significantly.

/pdf/a-two-dimensional-pedestrian-navigation-solution-aided-with-1xnfein4i4.pdf

A two-dimensional pedestrian navigation solution aided with a visual gyroscope and a visual odometer

Global Navigation Satellite System (GNSS)-based positioning is experiencing rapid changes. The existing GPS and the GLONASS systems are being modernized to better serve the current challenging applications under harsh signal conditions. These modernizations include increasing the number of transmission frequencies and changes to the signal components. In addition, the Chinese BeiDou Navigation Satellite system (BDS) and the European Galileo are currently under development for global operation. Therefore, in view of these new upcoming systems the research and development of GNSS receivers has been experiencing a new upsurge. In this article, the authors discuss the main functionalities of a GNSS receiver in view of BDS. While describing the main functionalities of a software-defined BeiDou receiver, the authors also highlight the similarities and differences between the signal characteristics of the BeiDou B1 open service signal and the legacy GPS L1 C/A signal, as in general they both exhibit similar characteristics. In addition, the authors implement a novel acquisition technique for long coherent integration in the presence of NH code modulation in BeiDou D1 signal. Furthermore, a simple phase-preserved coherent integration based acquisition scheme is implemented for BeiDou GEO satellite acquisition. Apart from the above BeiDou-specific implementations, a novel Carrier-to-Noise-density ratio estimation technique is also implemented in the software receiver, which does not necessarily require bit synchronization prior to estimation. Finally, the authors present a BeiDou-only position fix with the implemented software-defined BeiDou receiver considering all three satellite constellations from BDS. In addition, a true multi-GNSS position fix with GPS and BDS systems is also presented while comparing their performances for a static stand-alone code phase-based positioning.

/pdf/overcoming-the-challenges-of-beidou-receiver-implementation-3w65ta394d.pdf

Overcoming the Challenges of BeiDou Receiver Implementation

This is an open-access article licensed under a Creative Commons Attribution 3.0 Unported License.

/pdf/multipath-mitigation-techniques-for-satellite-based-2kt9ukqufw.pdf

Mohammad Zahidul H. Bhuiyan

Papers

Code tracking algorithms for mitigating multipath effects in fading channels for satellite-based positioning

Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications

A two-dimensional pedestrian navigation solution aided with a visual gyroscope and a visual odometer

Overcoming the Challenges of BeiDou Receiver Implementation

Multipath Mitigation Techniques for Satellite-Based Positioning Applications