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The subarray-level multibeam structure is advantageous for minimizing system complexity and enhancing multi-target detection and estimation performance. Furthermore, the subarray configuration plays a major role in determining the multibeam antenna pattern parameters. Therefore, we propose a subarray partition technique based on the tournament algorithm to enable spatial multibeam synthesis. In this paper, subarray configuration and excitation are alternately optimized through multiple rounds of tournament iterations. Each iteration calculates subarray excitations using convex optimization methods to fulfill requirements for the main radiation direction and low sidelobes, among other performance criteria. At the same time, excitations for each unassigned array element are calculated within each subarray separately. Simulation results for linear arrays demonstrate the proposed algorithm is not only suitable for linear arrays but also applicable to other array configurations, such as circular ring arrays and cylindrical arrays. And the proposed algorithm is effective in subarray periodicity, suppressing sidelobe levels, and allocating resources based on priority.

A promising solution for massive Multiple-Input Multiple-Output (m-MIMO) systems is Hybrid digital-analogue (HDA) beamforming as it offers a balanced trade-off between energy efficiency (EE) and spectral efficiency (SE). The lack of practical demonstrations in the open literature is primarily because those most existing works require a large number of phase shifters (PSs), radio frequency (RF) switches, power dividers (PDs), and power combiners which contribute to high hardware complexity and energy consumption (due to insertion loss). In this paper, we introduce a practical dynamic subarray m-MIMO structure that is based on reconfigurable power dividers (RPDs). The extensive system simulation results, considering hardware imperfection extracted from a practical RPD implementation, indicate that the proposed RPD-based dynamic HDA m-MIMO outperforms the fixed subarray counterpart.

Future broadband satellite communication (SatCom) systems require a high throughput of data transmission, which calls for operation at higher frequency bands. Adaptive coding and modulation (ACM) technology has been considered as a means to obtain improved performance further at these frequencies. However, the ACM protocols in current DVB-S2 and DVB-S2(X) standards do not take the effects that arise from the non-linear link with memory into account, which is generated by the cascade of a high-power amplifier (HPA) and digital root raised cosine (RRC) filters. This paper first reveals the non-linear characteristics of the SatCom link, and transfers this into an equivalent full-linear link with an additive noise source thanks to the pre-distortion algorithm. Using this equivalent modeling, an approach of selecting/adapting the optimum coding, modulation scheme and associated system configurations for a given channel fading level is proposed. Both simulations and experimental test-bed performance are presented to validate the proposed method.

This paper addresses backscatter communications as a new paradigm for Internet of Things (IoT) sensor wireless solutions. The paper clearly presents the history background of the technology and then makes a summary of the more recent developments form several groups around the world, with emphasis in US and Europe groups. The analysis done in this paper will address circuit and physical layer approaches for such a solution and its real implementations, having in mind IoT sensors for long range high speed communications.

This paper provides a comprehensive study of the harmonics generated by a frequency shifted backscatter communication system. The suppression and the manipulability of different harmonics are of importance to avoid detrimental inter-user interference when a number of backscattering nodes (and perhaps also other active wireless users) operate simultaneously in a network. In this paper the harmonics generated by a widely adopted open-short backscatter tag architecture is firstly presented. Then the ideal backscatter system which generates no unwanted harmonics is discussed, which inspires various harmonic suppression strategies. In particular, practical constraints of the backscatter tag hardware capabilities are applied, e.g., the number of discrete reflection coefficients that can be synthesized, and the dimension of the reflection coefficients (real-valued or complex-valued). Furthermore, the dual-transistor based IQ backscatter modulator is found useful to suppress all mirror harmonics and any specified higher order harmonics. The applicability of these proposed harmonic suppression approaches are demonstrated by an exemplar backscatter network consisting of multiple nodes performing binary frequency shifted keying (2FSK) modulated backscatter communications simultaneously.

In this paper, the concept and recent development of exploiting frequency diverse array (FDA) and its variants for the physical-layer wireless security have been revisited and carefully examined. Following rigorous analytical derivation and illustrative simulations, the authors realize that the investigations performed in some recent works overlooked one critical issue facing the real-world applications, and system models established and used before were based on a limited assumption, i.e. that the legitimate and eavesdropping users at different ranges sample the signal waveforms at the same time instant. The limitation of this assumption results in their studies inconclusive. The authors aim to take the first step to divert research efforts and rectify the previous incomplete analyses. The authors argue that in the current technology base the FDA cannot secure a free-space wireless transmission in range domain, because the previously claimed `secure reception region' propagates in range domain as time elapses.

Remote sensing images are primary data sources for land use classification. High spatial resolution images enable more accurate analysis and identification of land cover types. However, a higher spatial resolution also brings new challenges to the existing classification methods. In the low-level feature spaces of remote sensing images, it is difficult to improve classification performance by modifying classifiers. Probabilistic topic models can connect low-level features and high-level semantics of remote sensing images. Latent Dirichlet allocation (LDA) models are representatives of probabilistic topic models. However, at present, probabilistic topic models are mainly adopted for scene classification and image retrieval in remote sensing image analysis only. In this study, multiscale segmentation was employed to construct bag-of-words (BoW) representations of high-resolution images. The segmented patches were then utilized as “image documents.” A structural topic model was used with an LDA model to import spatial information from the image documents at two levels: topical prevalence and topical content in the form of covariates. In this way, latent topic features in image documents can be more accurately deduced. The proposed method showed more satisfactory classification performance than standard LDA models and demonstrated a certain degree of robustness against the changes in the segmentation scale. Acknowledgement for the data support from “Yangtze River Delta Science Data Center, National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://nnu.geodata.cn:8008)”.

Topologies are crucial for the cadastral data model. Considering the development of 3-D cadaster and temporal cadaster, 0-D–4-D multidimensional cadastral objects should be considered in the cadastral data model. There are few data models to support 0-D–4-D multidimensional cadastral objects and their topological relations, and some existing models represent the topological relations using complicated methods. This paper presents a multidimensional cadastral topological data model (MDCTDM). This model represents the topological relations of all cadastral objects simply and efficiently using a single basic element to associate the cadastral objects of each dimension in the same manner. Based on the generalized map, we extend the cell-tuple structure and propose an object-tuple structure for the MDCTDM. We design the data structure for the MDCTDM and implement it in a relational database. In this database, the topological relations of cadastral objects can be easily queried by using simple structured query language (SQL) statements. To verify the operations of the MDCTDM in the database, we describe a case of the insert operation. The case demonstrates that the operation can be implemented easily by SQL statements.

In this paper, we investigate the reliability and security performance of cooperative multi-relay systems, where both source and relay nodes are energy-constrained nonlinear energy harvesters, scavenging energy from a power beacon nearby. Our analysis is based on practical model since residual hardware impairments (RHIs) and channel estimation errors (CEEs) are considered. Aiming at improving the system efficiency, three representative relay selection strategies are considered: 1) random relay selection (RRS); 2) suboptimal relay selection (SRS); and 3) optimal relay selection (ORS). To characterize the security performance of the considered strategies, we derive closed-form analytical expressions of the reliability and security in terms of outage probability (OP) and intercept probability (IP). We further discuss the asymptotic expressions and scaling laws of OP with the number of relays. The IP is analyzed for non-colluding and colluding scenarios. The numerical results illustrate that: 1) There is a tradeoff between reliability and security, that is when the outage constraint is relaxed, the IP can be enhanced, and vice versa; ii) The outage performance of the ORS and SRS schemes outperform RRS, indicating that relay selection can enhance reliability performance; iii) There are error floors for the OP due to the CEEs; iv) Colluding eavesdroppers can enhance eavesdropping attacks by sharing their intercepted information; and v) Although RHIs and CEEs have deleterious effects on the OP, they can protect the information transmission against eavesdropping attacks.

This paper addresses the constrained multi-objective optimization problem of sparse conformal arrays designing. The objective of array synthesis is to find an optimal element arrangement on a conformal surface and its associated excitation strategy, which generate the main radiation beam along a pre-selected spatial direction with maximum gain and, simultaneously, suppress sidelobe levels elsewhere. A hybrid algorithm particle swarm optimization (PSO)-second-order cone programming (SOCP), comprising of PSO and SOCP, each for a dedicated purpose, is proposed to fulfill this task in this paper. More specifically, the PSO algorithm is introduced to optimize sparse conformal array element positions, whereas the SOCP is applied to seek optimal excitation coefficients for each array layout obtained. After extensive simulation with the examples of sparse circular array and sparse conical arrays, we can find that our proposed method can synthesize better radiation patterns with regard to peak sidelobe levels, compared with those obtained through other traditional algorithms.

This paper presents a thorough experimental study on key generation principles, i.e., temporal variation, channel reciprocity, and spatial decorrelation, through a testbed constructed by using wireless open-access research platform. It is the first comprehensive study through: 1) carrying out a number of experiments in different multipath environments, including an anechoic chamber, a reverberation chamber, and an indoor office environment, which represents little, rich, and moderate multipath, respectively; 2) considering static, object moving, and mobile scenarios in these environments, which represents different levels of channel dynamicity; and 3) studying two most popular channel parameters, i.e., channel state information and received signal strength. Through results collected from over a hundred tests, this paper offers insights to the design of a secure and efficient key generation system. We show that multipath is essential and beneficial to key generation as it increases the channel randomness. We also find that the movement of users/objects can help introduce temporal variation/randomness and help users reach an agreement on the keys. This paper complements existing research by experiments constructed by a new hardware platform.

With the high computation efficiency and tracking accuracy, discriminative correlation filters (DCFs) have been applied to unmanned aerial vehicle (UAV) tracking. However, in the scenarios (i.e., complex background and temporary occlusion), DCF-based trackers usually generate low credibility response under the influence of background distractors, which contains multiple side peaks and declines the tracking performance. Motivated by the response consistency in adjacent frames and background information penalization, we propose learning a response interference suppression (RIS) CF to tackle this problem. Specifically, we introduce an RIS regularization into the DCF-based framework, which aims to keep the target area response consistent in adjacent frames and repress distractors’ response in the background. Besides, we adopt a response auxiliary strategy (RAS) to smooth the target response, which intends to obtain the precise location and avoid target drift. Furthermore, extensive experiments on three UAV benchmarks demonstrate the excellent performance of the proposed method against other 19 state-of-the-art trackers. Moreover, the tracking speed of the proposed method can reach $\sim $ 42 frames/s (FPS) on a single CPU. [ABSTRACT FROM AUTHOR]

This paper details a method to improve accuracy of the land vehicle attitude estimation. It employs the vehicle model constraints to enhance the integration of GPS and a low-cost MEMS inertial measurement unit (MIMU) (GPS/MIMU). To improve the yaw angle estimation, we propose a lateral velocity constraint (LVC) aided method based on the observability analysis for the integrated fusion system. The theoretical analysis indicates that the yaw angle will be directly observed if LVC is augmented into the GPS/MIMU fusion algorithm. Furthermore, for LVC/MIMU system without GPS, the roll angle is always well estimated regardless of whether the vehicle is moving or stationary, and, surprisingly, the pitch angle can also be relatively accurately estimated if the vehicle is moving. Thus, when GPS is unavailable, the LVC/MIMU fusion is proposed by replacing the GPS measurement with the virtual measurement LVC. It is an encouraging improvement since the accumulating errors induced by gyro bias can be suppressed using MIMU alone. Moreover, to overcome the shortage that the pitch angle is not observed if the vehicle is stationary, we propose to fuse the gyros with gravity-based angles by Kalman filtering if the vehicle is detected motionless based on a switching rule. The experimental results compare favorably to theoretical analysis, showing that the proposed method can effectively improve the accuracy for land vehicle attitude estimation. [ABSTRACT FROM AUTHOR]

In this article, we develop a novel method to improve the accuracy of the low-cost vehicle attitude estimation using singular spectrum analysis (SSA) and independent component analysis (ICA). The microelectromechanical system (MEMS) accelerometers and the MEMS gyros are fused by the Kalman filtering algorithm to provide a low-cost attitude estimation. The low-frequency vibration noise and the maneuvering acceleration disturbance in the measurements of the MEMS accelerometers introduce large errors to the attitude estimation. To mitigate the low-frequency vibration noise, we propose a method based on SSA to separate the quasi-periodic components in accelerometer measurements and keep the trend remained as the true attitude measurement. SSA is effective in decomposing original signal into trend, periodic or quasi-periodic components, and thus, the low-frequency vibration noise that behaves as a quasi-periodic signal can be well separated. However, the acceleration disturbance still exists in the trend. Thus, a method based on ICA is then proposed to remove the acceleration disturbance by the aid of the turning rate measurement. The proposed method is verified with driving tests under city road and off-road conditions, showing a significant improvement of the attitude accuracy. [ABSTRACT FROM AUTHOR]

This letter is concentrated on the peak sidelobe level (PSLL) suppression problem of equal amplitude concentric ring array (CRA), which is constrained by the array aperture, the minimum element spacing, and the number of elements. Taking the minimum PSLL as the optimization objective, the joint optimization strategy of CRA aperture and ring array spacing is adopted to reduce the computational complexity. A quantum genetic algorithm based on hybrid coding is used to optimize the CRA. The proposed method has the advantages of fast searching speed and powerful searching ability. The simulation results demonstrate the superiority of the algorithm. [ABSTRACT FROM AUTHOR]