This PDF file contains the front matter associated with SPIE Proceedings Volume 10799, including the Title Page, Copyright information, Table of Contents, Author and Conference Committee lists.

Ranging and imaging in low light level conditions are a key application of active imaging systems. Typically, intensified cameras (ICCD, EBCMOS) are used to sense the intensity of reflected laser light pulses used for illumination. Recent developments in single photon avalanche diodes (SPAD) show, that sensors having single photon counting capabilities are about to revolutionize low light level imaging and laser ranging. These sensors have the ability to count detection events caused by single photons with very high timing precision. By application of statistical measurement means, the sensitivity of such devices can be increased far beyond classical sensing devices and the needed photon flux has significant lower intensities. New SPAD devices enable the development of novel sensing methods and technologies, and open laser ranging and imaging to new fields of application. Here, we focus on novel hardware structures which are under development as well as the application of avalanche photo diode detectors for light-in-flight detection and non-line-of-sight imaging.

We report a feasibility study of Time-of-Flight technique in Short- and Mid-Wavelength Infrared spectral region using a Mercury Cadmium Telluride detector. For the demonstration we employed an all-optical modulator operated by optical pumping with 800 nm, 100 femtosecond pulses and measured the broadening of the signal pulses traversing through a few centimetres of silica rod. The measured signal was analysed to reconstruct the pulse broadening and to retrieve the group velocity dispersion of silica. We show that in Time-of-Flight measurements based on all-optical modulation in combination with Mercury Cadmium Telluride detector, the limiting resolution factor is the speed of the modulator rise time governed by the optical pump.

High resolution images are critical for a wide variety of military detection, recognition and identification tasks. Super-resolution reconstruction algorithms aim to enhance the image resolution beyond the capability of the imaging system being used. Until recently, undersampling of the optical signal on the image sensor has been the key factor limiting the attainable resolution of visible and infrared imaging systems. Traditional SR algorithms aim to overcome this undersampling by combining data from multiple frames in a sequence. However, recent advances in manufacturing technologies have led to a steady increase in the number of pixels in an image sensor. Instead, image blur caused by optical diffraction is becoming an important limitation to the attainable image resolution. Here we investigate if image resolutions beyond the limitations posed by optical diffraction may be achieved using deep neural network based single image super-resolution algorithms. These networks learn a mapping from low resolution images to high resolution counterparts from pairs of training images. This could allow them to reconstruct high frequency information beyond the diffraction limit based on prior information about likely scene contents. We find that an average gain in image resolution of over 30% could be achieved by such networks on simulated diffraction limited imagery. In addition we investigate how robust these networks are to the presence of noise in the low resolution input imagery. We show that low noise levels can lead to poor reconstruction results with networks trained on noise free examples, but also that training on multiple noise levels can be used to mitigate this deterioration in performance.

To obtain high ranging resolution and to record full waveform signals, full waveform LiDAR requires short pulse width laser sources, high bandwidth sensors, high bandwidth A/Ds, and large on-board memories. To relax these requirements, temporal super-resolution is studied in this paper. In temporal super-resolution, the reflected beam is split into several branches, and then transpose through different distances before collected by detectors. The minimum distance difference among branches determines the system resolution. To reduce the number of measurements, compressive sensing idea is further used in temporal super-resolution LiDAR.

Single-Photon Avalanche Diode (SPAD) sensors are one of the detectors of choice in LIDAR applications, due to their high sensitivity and time resolution. Traditionally, single-point SPAD detectors have been used, necessitating optical scanning, and hence leading to slower acquisition times. However, recent advances in SPAD technology have yielded high pixel count imagers. In these sensors, high sensitivity is ensured by maximising the photo-sensitive area of the device, whilst time-resolved capability is offered by the time stamping of photon detections and/or a programmable timegate synced to the laser source. The resulting sensors show an exciting promise for LIDAR, especially in challenging, low-light, high-speed applications.

Single photon counting and timing are powerful tools in many applications. In recent years, there has been a fast trend towards the development of multichannel systems. Parallelism, indeed, can speed up the measurement and it allows advanced measurements based on the simultaneous acquisition of multiple wavelengths or multiple spots of the same sample at the same time. However, there currently is a tradeoff between number of channels and performance mainly because systems with hundreds of pixels have been developed so far relying on the exploitation of the standard CMOS technology to integrate both the detector and the electronics on the same chip. A breakthrough in this field would be the exploitation of different technologies, each one specifically selected to optimize a different part of the acquisition chain. In particular, we present fast fully integrated electronics able to operate external custom technology SPAD detectors to achieve high performance.

In recent years, communication has become in something common thanks to the use of the Internet. The exchange of information occurs between users around the world with great ease, leaving vulnerable the security, confidentiality, integrity and veracity characteristics of what is exchanged, due to this it has become a necessity to have tools that facilitate exchange of information of interest through non-secure digital media, but allowing only the parties involved to understand what is being exchanged. One of the techniques most used today to achieve this goal is steganography, this allows you to hide data or objects inside others, called carriers, in such a way that you ignore the presence of what you want to transmit. Currently, different types of carrier objects are used, such as audio files, images or videos. When using images as carrier objects, various techniques are used according to the domain (spatial or frequency) in which the concealment is made. By combining both domains it is possible to obtain an adaptive concealment process according to the nature of the carrier image. To perform steganography in images it is necessary to recognize the specific regions in which the new information can be added, also known as the Possible Insertion Region (PIR). In the present work the use of a new steganographic algorithm based on the use of the wavelet transform for the concealment of information in images is addressed.

The article considers the use of holographic interferometer to overwrite the holograms for distortion correction. Each optical system contains some deviations of the beam path, called aberrations of the optical system. They are considered in the resulting interference figure as a distortion of the bands. While increasing the sensitivity of the interference pattern, new aberrations caused by re-registration of the installation in addition to the aberrations already presented on the interferogram caused by the initial record, also multiplied by N times, are introduced N times. In this experiment we decided to use a modified setup with spatially combined interferograms with use of reflective SLM (spatial light modulator) LETO and digital image handling of the interferograms recorded by CCD or CMOS camera.

An increasing demand for high-performance and lower-cost LiDAR has led to a wealth of new research and commercial technologies utilizing photon-counting detection and image reconstruction techniques. In this work we demonstrate results from a compact and portable photon-counting LiDAR prototype, consisting of a high-speed digital-micromirror-device, short-pulsed infrared laser, photon-counting photomultiplier and FPGA-based TCSPC electronics. We evaluate the system performance when operating at ranges of up to 20m, using different scanning and reconstruction techniques which employ compressed sensing to increase the frame rate. Deep neural networks are computational models for learning representations of data with multiple levels of abstraction. Recently, there has been interest in using deep neural networks as a promising alternative to traditional compressive sensing techniques. In this work we will demonstrate progress made in using a deep convolutional auto-encoder network for recovering 3D images from a photon-counting LiDAR, which provides a computationally-efficient pipeline for solving underdetermined problems with better quality, in real-time. We anticipate that low-cost photon-counting LiDAR, enriched by deep-learning, will play an important role in many commercial sensing applications such as autonomous vehicles.

Technology at the quantum limit promises significant advances in computing, communication, sensing and metrology, and imaging.    The UK and many other countries around the world have recently provided significant investment in the development and realisation of such quantum technologies.  In this talk, I will highlight recent activities in applied and fundamental quantum science, specifically focussing on advances in imaging, and metrology.    Much of our work relies on the detection of single photons via single-photons detectors, either in single-point or array formats.   Single-photon sensitive detector (SPAD) arrays offer unprecedented sensitivity to light and picosecond temporal resolution, with the main advantage that they provide instantaneous data across their many pixels. I will discuss recent measurements that demonstrate sub-centimeter depth measurements with a visible CMOS SPAD sensor at long ranges. The system is based on a visible pulsed illumination system at 670 nm and a 320 by 240 pixel SPAD array sensor. The camera operates in a gated detection mode, and depth information is gained by taking multiple images at different gate delays. After processing, we are able to achieve sub-centimeter resolution in all three spatial dimensions at a distance of 150 meters. This work demonstrates the capability of such sensors at measuring depth at long distances and illustrates the potential for extremely high resolution imaging at distance.

In the absence of technically mature quantum repeaters, losses in optical fibers limit the distance for ground-bound quantum key distribution. One way to overcome these losses is via optical links to satellites, which has been demonstrated in course of the Chinese-Austrian QUESS mission. Though its findings were impressive, such a large-scale project requires massive financial and time resources. We propose a 32x10x10cm³ nanosatellite orders of magnitude cheaper which is able to perform quantum key distribution (QKD) in a trusted-node scenario, using only commercially available components. We have performed a detailed analysis of such a CubeSat mission (“Q³Sat”), finding that cost and complexity can be reduced by sending the photons from ground to satellite, i.e. using an uplink. Calculations have been done for a prepare-and-send protocol (BB84 with decoy pulses) and for a protocol exploiting quantum entanglement (E91), both using polarization as information carrier. We specified the minimum requirements for the sender stations for these two different protocols. Possible orbits have been assessed, regarding both height and ellipticity to maximize link time and minimize losses. Using long-term weather data, we developed a beam model taking into account absorption, turbulence-induced beam divergence and pointing stability of sender and receiver telescope. Using light pollution measurements from space and their spectra, we arrive at maximum expectable noise count rates. We also specify the requirements for clock stability, classical communication speed and computing requirements. Incorporating all these parameters into our model, we arrive at a link budget which we can use to calculate the expected quantum secure key rates. We have also created a preliminary design of such a 3U CubeSat including a detailed size, weight and power budget and a CAD to account for the assembly of the components. Deploying a 10 cm long mirror telescope covering the small surface of the satellite leaves enough space for a polarization analysis module and housekeeping, communication and computing electronics. Polarization analysis can be done via a polarizing beam splitter and single-photon detectors with a cross section small enough to rule out radiation damage. Pointing stability and detumbling is crucial especially for such a small satellite and can be achieved via spinning wheels, achieving a precision in the tilt and yaw axis of 40 mrad. For one such CubeSat, we estimate the quantum secure key to be acquired between two ground stations during one year to be about 13 Mbit when deploying a decoy protocol. A Bell test between ground and satellite would also be feasible. The uplink design allows to keep the more sensitive, computation-intensive and expensive devices on ground. The experiment proposed by us therefore poses a comparably low-threshold quantum space mission. For a two-year lifetime of the satellite, the price per kilobit would amount to about 20 Euro. In large constellations, Q³Sats could be used to establish a global quantum network, which would further lower the cost. Summarizing, our detailed design and feasibility study can be readily used as a template for global-scale quantum communication.

The distribution of quantum entanglement between distant parties is a key challenge in the pursuit of a worldwide quantum network. Quantum repeaters and optical satellite links have both been proposed to overcome the distance limitations of fiber-based quantum networks. In order to test the viability of a world spanning quantum satellite network, several proof-of-concept studies have already demonstrated high-fidelity transmission of photonic entanglement via terrestrial long-distance free-space links. With the recent launch of the Micius quantum satellite by the Chinese Academy of Sciences, the technological challenge of implementing this scheme in situ was overcome. All of these free-space experiments utilized entanglement in a two-dimensional state space, which in most cases was encoded in the polarization of photons. However, high-dimensional entanglement can yield significant benefits in quantum key distribution by increasing the secure key rate and enhancing the resilience to eavesdropping attacks. Energy-time entanglement is an established photonic degree of freedom (DOF); it is routinely used for the distribution of entanglement in fiber-based quantum cryptography networks but has only recently been considered as a viable option for atmospheric free-space quantum communications. The dimensionality can be further increased by exploiting simultaneous entanglement in several DOF. This so-called hyperentanglement has previously been used in various quantum protocols, but not yet been demonstrated outside a protected laboratory environment. For our proof-of-concept experiment (doi:10.1038/ncomms15971), we use energy-time and polarization hyperentanglement to distribute, for the first time, 4-dimensional entanglement via a 1.2-km-long intra-city free-space link. A source of hyperentangled photons and a detection module (Alice) were located in our lab and a receiver station (Bob) was located at a different university building. The source produced polarization entangled photon pairs via type-0 down-conversion in a Sagnac loop configuration. The emission time of a photon pair is uncertain within the significantly longer coherence time of the pump laser, thus resulting in an energy-time and polarization hyperentangled state. One photon was guided to a local measurement module and the partner photon was guided to a transmitter telescope on the roof of the institute. After transmission over the 1.2-km-long free-space link, the photons were received by a telescope and detected in Bob’s measurement module. The measurement modules for Alice and Bob each featured a polarization and an energy-time analyzer. We observe high-visibility two-photon interference in both polarization and energy-time subspaces. The measured visibilities certify entanglement in both subspaces individually. Additionally, they establish a lower bound on the Bell-state fidelity of the hyperentangled state of 0.94, thus certifying genuine 4-dimensional entanglement and 1.47 ebits of entanglement of formation. We have thus successfully distributed hyperentangled photon pairs via an intra-city free-space link under conditions of strong atmospheric turbulence. The transmission of quantum information embedded in a genuine high-dimensional state space under real-world link conditions is a first important step towards real-world implementations of advanced quantum information processing protocols in the future. In particular, it enables the implementation of high-dimensional QKD protocols over long-distance free-space links, and, ultimately, over satellite links with only minor changes to existing mission proposals.

Scientists continually seek to improve atmospheric turbulence models. Employing Fourier telescopy techniques, we have assessed the effect of humidity, temperature, atmospheric pressure, and airflow velocity on horizontal-path, ground-level turbulence. The measurements were made at different times of day. Turbulence parameters investigated include C_n², the scintillation index σ²_I, and the inner scale l₀ . The results showed temporal movement patterns of the turbulence to be consistent with Taylor’s frozen turbulence theory. We plan to compare the results of these outdoor measurements with measurements conducted indoors with an optical turbulence generator. Fourier telescopy measurements rely on the distant interference of two mutually-coherent and frequency-offset laser beams, the resulting moving interference fringe pattern “beating” against a fixed grating, such as a Ronchi ruling, and yielding a photo-detected signal that can be analyzed statistically to infer turbulence parameters. Preliminary study suggests that the Fourier telescopy-based measurements can provide more information on turbulence parameters than can measurements made with single laser beams. The basic experimental setup will be described, along with results of the experiments.

Quantum technologies containing key GaN laser components will enable a new generation of precision sensors, optical atomic clocks and secure communication systems for defence applications such as next generation navigation, gravity mapping and timing since the AlGaInN material system allows for laser diodes to be fabricated over a wide range of wavelengths from the u.v. to the visible.

We report our latest results on a range of AlGaInN diode-lasers targeted to meet the linewidth, wavelength and power requirements suitable for optical clocks and cold-atom interferometry systems. This includes the [5s²S_1/2-5p²P_1/2] cooling transition in strontium+ ion optical clocks at 422 nm, the [5s₂¹S₀-5p¹P1] cooling transition in neutral strontium clocks at 461 nm and the [5s²_s1/2 – 6p²P_3/2] transition in rubidium at 420 nm.

Several approaches are taken to achieve the required linewidth, wavelength and power, including an extended cavity laser diode (ECLD) system and an on-chip grating, distributed feedback (DFB) GaN laser diode.

Defects in efficiency or usability have come into being when using the maximum stress on FBAR structure as the reference stress or using the so called “Calculus-like analysis method” to calculate the sensitivity of FBAR transducer. The former does not consider the influence of the strain in the thickness direction, which overestimates the sensitivity. The latter learns from FEM, but it is too complicate and heavy-workload. In order to eliminate these deficiencies, the improved sensitivity prediction method for FBAR transducer is put forward. The whole calculation process is completed with COMSOL FEM software to avoid the complex data processing. The energy weighted average method is used to calculate the average strain of every single layer in FBAR and the average internal pressure of piezoelectric layer. The average strain is used to modify the thickness of FBAR, and the internal pressure is used to modify the elastic constant of piezoelectric material. Then the eigenfrequency solving method is carried out to solve the eigenfrequency of FBAR. The former improves the speed of solving, and the latter enhance the accuracy of the calculation results. The sensitivity of both circular membrane type FBAR transducer and FBAR micro-accelerometer can be calculated through the improved method. The expected sensitivity of the membrane type FBAR transducer is 46.5 MHz/N, which is close to the experimental result, 50 MHz/N. However, due to unawareness of the actual structure parameters, the expected sensitivity of the micro-accelerometer is 27 kHz/g, which is different from the experimental result, 100 kHz/g. The two calculation cases indicate that the improved sensitivity prediction method for FBAR transducer is both effective and available.

In order to predict the thermal behavior of bulk acoustic wave resonator (BAWR) and evaluate the power handling capacity, a BAWR thermal behavior simulation method is proposed. The conductor surface loss in the BAWR electromagnetic model is extracted and used as the heat source for thermal simulation to obtain the temperature distribution of the resonator. Then the signal feeding edge, active area shape and power handling capacity are researched. The simulation results show that in order to moderate the self-heating effect of BAWR, the signal feeding should follow the principle of “feeding in from long edge, feeding out from long edge”; active area shape has little to do with selfheating effect; the power handling capacity of the designed BAWR can reach to 3 W.

Optical resonators of whispering gallery modes are dielectric axially symmetric resonators with smooth edges that support the existence of whispering gallery modes due to full internal reflection from the resonator surface. Centrifugal forces caused by the rotation of material objects can lead to their mechanical deformation. This is true for resonators of the whispering gallery modes, and when this occurs, the variation of the radius of the working section of the cavity takes place. As is known, the frequencies of whispering gallery modes are inversely proportional to the radius of the working section. Thus, under the influence of centrifugal forces, a reciprocal (the same for opposite directions of the cavity circuit bypass by light) shift of the whispering gallery modes frequencies occurs. Optical methods allow to determine this shift with high accuracy. This can be used in practice for measuring angular velocity and create a miniature angular rate sensor. However, the reciprocal nature of the shift does not allow to judge about the sign of the angular rate (clockwise or counterclockwise rotates the object). In this paper, we propose to solve this problem by applying the initial displacement of the output characteristic point (bias). The perspectives of applying both constant and alternating sign initial displacements are considered. Also, this approach should allow to increase sensitivity to low angular velocities and reduce the nonlinearity of the output characteristic.

In order to determine the order of BAW ladder filter, the relationship among out-of-band rejection, area ratio of parallel and series FBAR, and the filter order N are studied by simulating. Based on FBAR Mason model, firstly, one-order to six-order BAW ladder filters are constructed; next, the area ratio of parallel and series FBAR (Cps) is set from 1 to 6, and the six BAW ladder filters are simulated in ADS; finally, the left out-of-band rejections are extracted from the simulation result, and plotted as a graph. In addition, as the filter orders can be set to a half order, the filters with order N (N=1.5… 5.5) are simulated in the same way. Simulation results show that the out-of-band rejection has an equal increase with the filter order in number when Cps remains constant, and that the out-of-band rejection increases as Cps increases when filter order keeps constant. When optimizing the design, the area ratio of parallel and series FBAR (Cps) is usually set from1 to 4, within which the out-of-band rejection will increase by about 10 dB when the filter increases by one order. And when the filter increases half order, the out-of-band rejection will increase by 5 dB, which is about half of the value by increasing an integer order. In addition, the structure of ladder filter is discussed, and the influence of the filter order and capacitance ratio on the passband performance is studied.

Microstrip interdigital filter requires use of grounding via-holes, but the grounding via-holes will influence performance of interdigital filter. The traditional design method does not consider grounding via-holes effect in the initial design process, which will lead to some uncertainties of the grounding via-holes, such as the number, the size and the position. This will make the subsequent optimization face multi-factor and multi-level problems. In addition, when the substrate thickness and the center frequency increase to a certain extent, the external quality factor obtained by using the traditional 50 Ω tapped-line cannot reach the theoretical value. Therefore, the traditional design method is modified, and the grounding via-holes effect is considered in the initial design process by using 3D electromagnetic field simulation software. When the traditional 50 Ω tapped-line do not meet the design requirements, it is improved to a gradual tappedline with the combination of a 50 Ω microstrip line and a narrower microstrip line. Taking a Ka-band filter as an example, 100 μm and 300 μm thick high resistance silicon are used as substrate respectively. The simulation results indicate that the initial design for filter with the modified method is closer to the specifications, which can reduce subsequent iterations. Besides, the insertion loss of filter with gradual tapped-line is 1.91 dB, and return loss is 18.06 dB. What’s more, the stop rejection at 27.00 GHz and 33.40 GHz are 46.91 dB and 59.58 dB, respectively.

To detect drones in real-time at large distances, using high-resolution visual(VIS) cameras, requires a careful system design. In our setup we use four 10-bit 25 Megapixels@25fps cameras to detect drones. This means a theoretical raw data throughput of about 33 GB/sec for the system from the VIS cameras alone. We implemented a small-object detection algorithm on two different platforms. The algorithm is based on a point-detector with a subsequent clustering step. One platform is a Xilinx Kintex-7 FPGA, the other a Nvidia GeForce GTX 1080 GPU. We explain, how the small-object detection algorithm, based on a software reference implementation, has been ported to a FPGA version. It is shown, that the FPGA implementation of the point-detector reaches the optimal throughput and we show, that the clustering can be done in a streaming fashion. Using the FPGA implementation, the camera can be used in free-running mode, processing the camera data in real time. The CUDA implementation of the algorithm shows, that the computing capabilities of modern GPGPUs allow an easy port of the algorithm to this platform to reach real-time performance with 68fps. The use of four high-resolution cameras requires a careful overall system design. We present our hardware system design and the central data distribution system. As the small-object detections may be used by different processes like the tracking process or display processes, a fast, safe and robust distribution system must be provided. We describe our approach using the Boost Interprocess library to provide a portable data distribution system.

Unmanned Aerial Systems UAS, i.e. drones, revolutionize the market for mobility based services and enable more efficient defence and security operations. Also this rapidly developing technology, however, proves to be Janus-faced. Despite their unquestionable benefits, UAS increasingly pose serious safety and security threats. Detection, tracking, and classification of small and highly agile drones, however, is one of the most challenging surveillance tasks. Only a properly designed suite of heterogeneous and mutually complementary sensor provides the required sensor data. On this basis, the key technology proves to advanced multiple sensor data fusion that provides situational awareness and the key information for assigning appropriate counter measures. We in particular focus on a novel approach and highly promising approach which has the potential of a paradigm shift in sensor data fusion: tensor decomposition based multiple sensor tracking filters. This new methodology for fusion engines is able to efficiently represent the full informational content of advanced sensors and sophisticated dynamic models for drone motion. Powerful multilinear decomposition methods for tensors are drastically reducing the computational efforts for producing high-quality tracks for dim and agile drones. Moreover, the deterministic performance characteristics of tensor decomposition based fusion have beneficial implications for systems design aspects. These advanced algorithms of multiple sensor data fusion play a key role in designing counter drone systems. In the context of C5ISR systems (Command, Control, Communications, Computer, Cyber, Intelligence, Surveillance and Reconnaissance), the technological challenges can be met, but require close cooperation between the military and police forces, research institutes and the relevant industries. In the protection of stationary equipment and mobile units in urban or open terrain, the integration of drone detection / tracking / classification in decision support systems is crucial.

In this paper integrated radar modules are presented which are suitable for collision avoidance and imaging for small UAVs. A short introduction to electronic beam steering is given and different approaches for angle resolving imaging are shown. Two sensors, a mono-static 80 GHz radar sensor and a polarization resolving bistatic 94 GHz radar module are presented which can be valuable elements of sensor-suites for modern UAV based imaging and surveillance and autonomous operation.

After the revolution of Dignity in Ukraine (November 21, 2013 – February 22, 2014) the political landscape in the Ukrainian society has changed the direction toward the EU and NATO integrations. In the digital era, situational awareness on the modern battle field requires absolutely new solutions. The armory and logistics of the Ukraine Defense Forces was outdated very much at that time. Existing national and international legislation did not allow to export Western modern military supplies from abroad. That gap was quickly fulfilled by the enthusiastic and talented volunteers as domestic so international. One joint project was the development of handheld situational awareness system for field artillery. The key of this successful story used to be open-source IT technologies. Android-based solution fully supports the UAV (Unmanned Aerial Vehicle) which is often used as flying weather station, for video control and reconnaissance, targeting and radio relay. In this paper, we preset the results of multi-year R&D project which turned into commercial.

The detection and tracking of UAV’s is a critical task for public and military security. The main are the low flight height and the small radar cross section (RCS). The problems increase in an urban environment with many high buildings, especially when tall buildings block the line of sight. A new concept of distributed radar sensors was developed to close this gap. To reduce the impact of radar shadows in urban canyons, a surveillance grid of optical and radar sensors is necessary which covers the complete urban environment. The radar sensors build up different security sectors and monitor all access routes for attacking UAVs. Sophisticated cameras which offer night vision capabilities complete the sensor network to reduce the false alarm rate through these regular, declared UAV flights. Cameras allow the integration of a man in the loop which has the final responsibility to define a target as a threat or not. The system supports the operator with a database which based on optical and radar signature of most commercially available UAV’s.

The number of reported incidents caused by small UAVs, intentional as well as accidental, is rising. To avoid such incidents in future, it is essential to be able to detect UAVs. LiDAR sensors (e.g., laser scanners) are well known to be adequate sensors for object detection and tracking.

In this paper, we expand our existing LiDAR-based approach for the tracking and detection of (low) flying small objects like commercial mini/micro UAVs. We show that UAVs can be detected by the proposed methods, as long as the movements of the UAVs correspond to the LiDAR sensor’s capabilities in scanning performance, range and resolution. The trajectory of the tracked object can further be analyzed to support the classification, meaning that UAVs and non- UAV objects can be distinguished by an identification of typical movement patterns. A stable tracking of the UAV is achieved by a precise prediction of its movement. In addition to this precise prediction of the target’s position, the object detection, tracking and classification have to be achieved in real-time.

For the algorithm development and a performance analysis, we analyzed LiDAR data that we acquired during a field trial. Several different mini/micro UAVs were observed by a system of four 360° LiDAR sensors mounted to a car. Using this specific sensor system, the results show that UAVs can be detected and tracked by the proposed methods, allowing a protection of the car against UAV threats within a radius of up to 35 m.

The number of affordable consumer unmanned aerial vehicles (UAVs) available on the market has been growing quickly in recent years. Uncontrolled use of such UAVs in the context of public events like sports events or demonstrations, as well as their use near sensitive areas, such as airports or correctional facilities pose a potential security threat. Automatic early detection of UAVs is thus an important task which can be addressed through multiple modalities, such as visual imagery, radar, audio signals, or UAV control signals. In this work we present an image processing pipeline which is capable of tracking very small point targets in an overview camera, adjusting a tilting unit with a mounted zoom camera (PTZ system) to locations of interest and classifying the spotted object in this more detailed camera view. The overview camera is a high-resolution camera with a wide field of view. Its main purpose is to monitor a wide area and to allow an early detection of candidates, whose motion or appearance warrant a closer investigation. In a subsequent process these candidates are prioritized and successively examined by adapting the orientation of the tilting unit and the zoom level of the attached camera lens, to be able to observe the target in detail and provide appropriate data for the classification stage. The image of the PTZ camera is then used to classify the object into either UAV class or distractor class. For this task we apply the popular SSD detector. Several parameters of the detector have been adapted for the task of UAV detection and classification. We demonstrate the performance of the full pipeline on imagery collected by the system. The data contains actual UAVs as well as distractors, such as birds.

In recent years, with development of computer vision and robotics, a wide variety of localization approaches have been proposed. However, it is still challenging to design a localization algorithm that performs well in both indoor and outdoor environment. In this paper, an algorithm that fuses camera, IMU, GPS, as well as digital compass is proposed to solve this problem. Our algorithm includes two phases: (1) the monocular RGB camera and IMU are fused together as a VIO that estimates the approximate orientation and position; (2) the absolute position and orientation measured by GPS and digital compass are merged with the position and orientation estimated in first phase to get a refined result in the world coordinate. A bag-of-word based algorithm is utilized to realize loop detection and relocalization. We also built a prototype and did two experiments to evaluate the effectiveness and robustness of the localization algorithm in both indoors and outdoors environment.

The precision farming is a highly advanced industry nowadays. The high-performance system for monitoring agricultural land on the base of Unmanned Aerial Vehicles is presented in the paper. Argumentation of the adopted technical solutions is also announced. Necessity and frequency of monitoring of grain crops depending on phases of development of plants is analyzed. On the basis of these data, the required flight and technical characteristics of Unmanned Aerial Vehicles are determined. The scheme of the system including unmanned aerial vehicles, ground stations and user software is developed.

The UNISA Folded Pendulum technological platform is very promising for the implementation of high sensitivity large broadband miniaturized mechanical seismometers and accelerometers in different materials. In fact, the symmetry of its mechanical architecture allows to take full advantage of one of the most relevant properties of the folded pendulum, that is the scalability. This property is very useful for the design of folded pendulums of small size and weight, provided with a suitable combination of physical and geometrical parameters. Using a Lagrangian simplified model of folded pendulum, we present and discuss this idea, showing different possible approaches that may lead to the miniaturization of a folded pendulum. Finally, we present a prototype of a miniaturized inertial sensor, characterized by a resonance frequency of 0.5Hz, a measurement band of 1mHz ÷ 1 kHz, a weight of 40 g and a size of 5 cm × 5 cm × 1.8 cm, discussing its characteristics and limitations, in connection with scientific ground, marine and space applications.

In submarine environments for the collection of information, wired oceanic positioning devices are used. However, the use of this type of instruments in the investigation of ecosystems, burst into the tranquility of the habitat, putting at risk the veracity of the data that is collected, due to the behavior of some species that, when they feel assaulted or invaded in their natural environment, deploy defense mechanisms. Another alternative for the collection of information in these environments is wireless communications in aqueous media, however, the research related to this type of communication is supported by simulations without performing field tests to check their functionality, the performance of the batteries and the effectiveness of communication between devices in an underwater environment. For this reason, the design of a wireless communication system between a mobile device and a submarine semi-autonomous vehicle is proposed, using a radio beacon, to know the geographical coordinates of the vehicle, through a Global Positioning System (GPS), and in this way know the trajectory path of the vehicle. So that this communication can help in the detailed study of marine ecosystems, where the researcher obtains the tracking of migration trajectory of marine species, without altering the habitat.

The aim of the work is to develop a model of adaptive system of neuro-fuzzy inference based on PI- and PI-FUZZYcontrollers, allowing to simplify, automate and unify the design process of modern automated control systems. To achieve a specific goal, a method for managing a technical object has been developed based on the construction of an adaptive system of neuro-fuzzy inference. As controllers in the system of neuro-fuzzy inference, the classical PI-controller and fuzzy PI-FUZZY-controller were chosen. Interaction between controllers is provided with the help of the hybrid control system developed. The result of interaction of the two models is automatic formation of the basis of fuzzy controller rules based on knowledge of the control object obtained with its control using the classical controller. In the developed adaptive system of neuro-fuzzy inference, error and control signals in the classical model are used as data for building a hybrid network. Error and control signals in the fuzzy model with automatically generated fuzzy inference rules are used as data to verify the hybrid network built in order to detect a fact of its retraining. Thus, during the control of a technical object by means of a hybrid system, the knowledge of an expert in subject domain for adjusting the parameters of the fuzzy controller is completely eliminated, which makes it possible to control difficultly formalizable objects in conditions of uncertainty. To obtain reliable research results, a hybrid control system was developed, consisting of classical and fuzzy models. Numeric values of the error and control signals are obtained at discrete instants of time as a result of interaction of the two models. Special files have been created to build and test a hybrid network in the form of numerical matrices.

Feature matching is at the base of many computer vision algorithms such as SLAM, which is a technology widely used in the area from intelligent vehicles (IV) to assistance for the visually impaired (VI). This article presents an improved detector and a novel semantic-visual descriptor, coined SORB (Semantic ORB), combining binary semantic labels and traditional ORB descriptor. Compared to the original ORB feature, the new SORB performs better in uniformity of distribution and accuracy of matching. We demonstrate it through experiments on some open source datasets and several real-world images obtained by RealSense.