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During the past few decades, information technologies have been evolving at a tremendous rate, causing profound changes to our world and to our ways of living. Emerging applications have opened u[ new routes and set new trends for antenna sensors. With the advent of the Internet of Things (IoT), the adaptation of antenna technologies for sensor and sensing applications has become more important. Now, the antennas must be reconfigurable, flexible, low profile, and low-cost, for applications from airborne and vehicles, to machine-to-machine, IoT, 5G, etc. This reprint aims to introduce and treat a series of advanced and emerging topics in the field of antenna sensors.

3D printing --- additive manufacturing --- Radio Frequency IDentification (RFID), chipless RFID --- mounted on metal --- unmanned aerial vehicle --- phased array --- frequency reconfiguration --- beam steering --- antioxidation --- frequency-reconfiguration --- liquid metal --- temperature sensor --- antenna sensor --- thermal expansion --- electrolyte-free --- industrial WSN --- ISA100.11a model --- ns-3 --- WSN --- UHF antennas --- ultra wideband antennas --- conformal antennas --- radio frequency identification --- elliptical dipole antenna --- EM/circuit co-simulation --- low-cost --- low-power --- power gating --- RF oscillator --- RTLS --- ultrawide band antennas --- biopotential sensing --- Fabry-Perot resonator --- antenna --- superstrate --- metamaterials --- passive sensing --- sensor array --- sparse array --- nonuniform array --- planar array --- random array --- low discrepancy sequence --- triband antenna --- wireless sensors --- planar patch antenna --- mobile applications --- DCS --- WLAN --- WiMAX --- circular polarization --- flexible --- polymer --- transparent --- wearable --- litz wire --- lateral misalignment --- magnetic field distribution --- mutual inductance --- Neumann integral formula --- planar spiral coil --- Internet of Things (IoT) --- wireless sensor network (WSN) --- switched-beam antenna --- electronically steerable parasitic array radiator (ESPAR) antenna --- received signal strength (RSS) --- direction-of-arrival (DoA) estimation

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In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot.

Technology: general issues --- Energy industries & utilities --- dynamic objects identification and localization --- laser cluster --- radial velocity similarity --- Pearson correlation coefficient --- particle filter --- trilateral indoor positioning --- RSSI filter --- RSSI classification --- stability --- accuracy --- inertial navigation system --- artificial neural network --- motion tracking --- sensor fusion --- indoor navigation system --- indoor positioning --- indoor navigation --- radiating cable --- leaky feeder --- augmented reality --- Bluetooth --- indoor positioning system --- smart hospital --- indoor --- positioning --- visually impaired --- deep learning --- multi-layered perceptron --- inertial sensor --- smartphone --- multi-variational message passing (M-VMP) --- factor graph (FG) --- second-order Taylor expansion --- cooperative localization --- joint estimation of position and clock --- RTLS --- indoor positioning system (IPS) --- position data --- industry 4.0 --- traceability --- product tracking --- fingerprinting localization --- Bluetooth low energy --- Wi-Fi --- performance metrics --- positioning algorithms --- location source optimization --- fuzzy comprehensive evaluation --- DCPCRLB --- UAV --- unmanned aerial vehicles --- NWPS --- indoor positioning systems --- GPS denied --- GNSS denied --- autonomous vehicles --- visible light positioning --- mobile robot --- calibration --- appearance-based localization --- computer vision --- Gaussian processes --- manifold learning --- robot vision systems --- image manifold --- descriptor manifold --- indoor fingerprinting localization --- Gaussian filter --- Kalman filter --- received signal strength indicator --- channel state information --- indoor localization --- visual-inertial SLAM --- constrained optimization --- path loss model --- particle swarm optimization --- beacon --- absolute position system --- cooperative algorithm --- intercepting vehicles --- robot framework --- UWB sensors --- Internet of Things (IoT) --- wireless sensor network (WSN) --- switched-beam antenna --- electronically steerable parasitic array radiator (ESPAR) antenna --- received signal strength (RSS) --- fingerprinting --- down-conversion --- GPS --- navigation --- RF repeaters --- up-conversion --- dynamic objects identification and localization --- laser cluster --- radial velocity similarity --- Pearson correlation coefficient --- particle filter --- trilateral indoor positioning --- RSSI filter --- RSSI classification --- stability --- accuracy --- inertial navigation system --- artificial neural network --- motion tracking --- sensor fusion --- indoor navigation system --- indoor positioning --- indoor navigation --- radiating cable --- leaky feeder --- augmented reality --- Bluetooth --- indoor positioning system --- smart hospital --- indoor --- positioning --- visually impaired --- deep learning --- multi-layered perceptron --- inertial sensor --- smartphone --- multi-variational message passing (M-VMP) --- factor graph (FG) --- second-order Taylor expansion --- cooperative localization --- joint estimation of position and clock --- RTLS --- indoor positioning system (IPS) --- position data --- industry 4.0 --- traceability --- product tracking --- fingerprinting localization --- Bluetooth low energy --- Wi-Fi --- performance metrics --- positioning algorithms --- location source optimization --- fuzzy comprehensive evaluation --- DCPCRLB --- UAV --- unmanned aerial vehicles --- NWPS --- indoor positioning systems --- GPS denied --- GNSS denied --- autonomous vehicles --- visible light positioning --- mobile robot --- calibration --- appearance-based localization --- computer vision --- Gaussian processes --- manifold learning --- robot vision systems --- image manifold --- descriptor manifold --- indoor fingerprinting localization --- Gaussian filter --- Kalman filter --- received signal strength indicator --- channel state information --- indoor localization --- visual-inertial SLAM --- constrained optimization --- path loss model --- particle swarm optimization --- beacon --- absolute position system --- cooperative algorithm --- intercepting vehicles --- robot framework --- UWB sensors --- Internet of Things (IoT) --- wireless sensor network (WSN) --- switched-beam antenna --- electronically steerable parasitic array radiator (ESPAR) antenna --- received signal strength (RSS) --- fingerprinting --- down-conversion --- GPS --- navigation --- RF repeaters --- up-conversion

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot.

dynamic objects identification and localization --- laser cluster --- radial velocity similarity --- Pearson correlation coefficient --- particle filter --- trilateral indoor positioning --- RSSI filter --- RSSI classification --- stability --- accuracy --- inertial navigation system --- artificial neural network --- motion tracking --- sensor fusion --- indoor navigation system --- indoor positioning --- indoor navigation --- radiating cable --- leaky feeder --- augmented reality --- Bluetooth --- indoor positioning system --- smart hospital --- indoor --- positioning --- visually impaired --- deep learning --- multi-layered perceptron --- inertial sensor --- smartphone --- multi-variational message passing (M-VMP) --- factor graph (FG) --- second-order Taylor expansion --- cooperative localization --- joint estimation of position and clock --- RTLS --- indoor positioning system (IPS) --- position data --- industry 4.0 --- traceability --- product tracking --- fingerprinting localization --- Bluetooth low energy --- Wi-Fi --- performance metrics --- positioning algorithms --- location source optimization --- fuzzy comprehensive evaluation --- DCPCRLB --- UAV --- unmanned aerial vehicles --- NWPS --- indoor positioning systems --- GPS denied --- GNSS denied --- autonomous vehicles --- visible light positioning --- mobile robot --- calibration --- appearance-based localization --- computer vision --- Gaussian processes --- manifold learning --- robot vision systems --- image manifold --- descriptor manifold --- indoor fingerprinting localization --- Gaussian filter --- Kalman filter --- received signal strength indicator --- channel state information --- indoor localization --- visual-inertial SLAM --- constrained optimization --- path loss model --- particle swarm optimization --- beacon --- absolute position system --- cooperative algorithm --- intercepting vehicles --- robot framework --- UWB sensors --- Internet of Things (IoT) --- wireless sensor network (WSN) --- switched-beam antenna --- electronically steerable parasitic array radiator (ESPAR) antenna --- received signal strength (RSS) --- fingerprinting --- down-conversion --- GPS --- navigation --- RF repeaters --- up-conversion --- n/a