Laser Based Altimetry for Unmanned Aerial Vehicle Hovering Over a Snow Surface

A microwave radar for non-invasive snow stratigraphy measurements has been developed. Results were promising, but it failed to detect light powder snow in the air-snowpack interface. The aim of this thesis is to find and verify a system for estimating altitude on centimeter scale over a snow surface, independent of snow conditions. Also, relative pitch and roll angle estimation between the UAV and local surface should be resolved, to help directing the radar beam perpendicularly to the surface. After a variety of technical solutions were examined, we propose a system of three time-of-flight near-infrared altimeters pointing at different directions towards the surface. Experimental results showed RMS error of 1.39 cm for range estimation averaged over the most common snow types, and 2.81 cm for wet snow, which was the least reflective medium. An experiment conducted for an array of two altimeters scanning over a snow surface, showed that the local, relative surface tilt was found to be accurate within ±2° given that it was sufficiently planar. Further, the altitude RMS error was estimated to 1.57 cm. We conclude that the chosen altimeter was within the requirements, and that an array of three altimeters would give acceptable relative tilt estimation in to planes on the snow surface. The system should be subject to flight testing and implemented on UAV platform such that it can aid the microwave radar system during snow scanning

Recent Advances in mmWave-Radar-Based Sensing, Its Applications, and Machine Learning Techniques: A Review

Human gesture detection, obstacle detection, collision avoidance, parking aids, automotive driving, medical, meteorological, industrial, agriculture, defense, space, and other relevant fields have all benefited from recent advancements in mmWave radar sensor technology. A mmWave radar has several advantages that set it apart from other types of sensors. A mmWave radar can operate in bright, dazzling, or no-light conditions. A mmWave radar has better antenna miniaturization than other traditional radars, and it has better range resolution. However, as more data sets have been made available, there has been a significant increase in the potential for incorporating radar data into different machine learning methods for various applications. This review focuses on key performance metrics in mmWave-radar-based sensing, detailed applications, and machine learning techniques used with mmWave radar for a variety of tasks. This article starts out with a discussion of the various working bands of mmWave radars, then moves on to various types of mmWave radars and their key specifications, mmWave radar data interpretation, vast applications in various domains, and, in the end, a discussion of machine learning algorithms applied with radar data for various applications. Our review serves as a practical reference for beginners developing mmWave-radar-based applications by utilizing machine learning techniques.publishedVersio

Dynamic Radar Network of UAVs: A Joint Navigation and Tracking Approach

Nowadays there is a growing research interest on the possibility of enriching small flying robots with autonomous sensing and online navigation capabilities. This will enable a large number of applications spanning from remote surveillance to logistics, smarter cities and emergency aid in hazardous environments. In this context, an emerging problem is to track unauthorized small unmanned aerial vehicles (UAVs) hiding behind buildings or concealing in large UAV networks. In contrast with current solutions mainly based on static and on-ground radars, this paper proposes the idea of a dynamic radar network of UAVs for real-time and high-accuracy tracking of malicious targets. To this end, we describe a solution for real-time navigation of UAVs to track a dynamic target using heterogeneously sensed information. Such information is shared by the UAVs with their neighbors via multi-hops, allowing tracking the target by a local Bayesian estimator running at each agent. Since not all the paths are equal in terms of information gathering point-of-view, the UAVs plan their own trajectory by minimizing the posterior covariance matrix of the target state under UAV kinematic and anti-collision constraints. Our results show how a dynamic network of radars attains better localization results compared to a fixed configuration and how the on-board sensor technology impacts the accuracy in tracking a target with different radar cross sections, especially in non line-of-sight (NLOS) situations

Ultralight Radar Sensor for Autonomous Operations by Mini- and Micro-UAS

In recent years the boost in operations by mini- and micro-UAS (Unmanned Aircraft Systems, also known as Remotely Piloted Aircraft Systems - RPAS - or simply drones) and the successful miniaturization of electronic components were experienced. Radar sensors demonstrated to have favorable features for these operations. However, despite their ability to provide meaningful information for navigation, sense-and-avoid, and imaging tasks, currently very few radar sensors are exploited onboard or developed for autonomous operations with mini- and micro-UAS. Exploration of indoor complex, dangerous, and not easily accessible environments represents a possible application for mini-UAS based on radar technology. In this scenario, the objective of the thesis is to develop design strategies and processing approaches for a novel ultralight radar sensor able to provide the miniaturized platform with Simultaneous Localization and Mapping (SLAM) capabilities, mainly but not exclusively indoors. Millimeter-wave Interferometric Synthetic Aperture Radar (mmw InSAR) technology has been identified as a key asset. At the same time, testing of commercial lightweight radar is carried out to assess potentialities towards autonomous navigation, sense-and-avoid, and imaging. The two main research lines can be outlined as follows: - Long-term scenario: Development of very compact and ultralight Synthetic Aperture Radar able to provide mini- or micro-UAS with very accurate 3D awareness in indoor or GPS-denied complex and harsh environments. - Short-term scenario: Assessment of true potentialities of current commercial radar sensors in a UAS-oriented scenario. Within the framework of long-term scenario, after a review of state-of-art SAR sensors, Frequency-Modulated Continuous Wave (FMCW) SAR technology has been selected as preferred candidate. Design procedure tailored to this technology and software simulator for operations have been developed in MATLAB environment. Software simulator accounts for the analysis of ambiguous areas in a three-dimensional environment, different SAR focusing algorithms, and a Ray-Tracing algorithm specifically designed for indoor operations. The simulations provided relevant information on actual feasibility of the sensor, as well as mission design characteristics. Additionally, field tests have been carried out at Fraunhofer Institute FHR with a mmw SAR. Processing approaches developed from simulations proved to be effective when dealing with field tests. A very lightweight FMCW radar sensor manifactured by IMST GmbH has been tested for short-term scenario operations. The codes for data acquisition were developed in Python language both for Windows-based and GNU/Linux-based operative systems. The radar provided information on range and angle of targets in the scene, thus being interesting for radar-aided UAS navigation. Multiple-target tracking and radar odometry algorithms have been developed and tested on actual field data. Radar-only odometry provided to be effective under specific circumstances

Design and Performance Analysis of Wireless Legitimate Surveillance Systems with Radar Function

Integrated sensing and communication (ISAC) has recently been considered as a promising approach to save spectrum resources and reduce hardware cost. Meanwhile, as information security becomes increasingly more critical issue, government agencies urgently need to legitimately monitor suspicious communications via proactive eavesdropping. Thus, in this paper, we investigate a wireless legitimate surveillance system with radar function. We seek to jointly optimize the receive and transmit beamforming vectors to maximize the eavesdropping success probability which is transformed into the difference of signal-to-interference-plus-noise ratios (SINRs) subject to the performance requirements of radar and surveillance. The formulated problem is challenging to solve. By employing the Rayleigh quotient and fully exploiting the structure of the problem, we apply the divide-and-conquer principle to divide the formulated problem into two subproblems for two different cases. For the first case, we aim at minimizing the total transmit power, and for the second case we focus on maximizing the jamming power. For both subproblems, with the aid of orthogonal decomposition, we obtain the optimal solution of the receive and transmit beamforming vectors in closed-form. Performance analysis and discussion of some insightful results are also carried out. Finally, extensive simulation results demonstrate the effectiveness of our proposed algorithm in terms of eavesdropping success probability

Antennas and Propagation Aspects for Emerging Wireless Communication Technologies

The increasing demand for high data rate applications and the delivery of zero-latency multimedia content drives technological evolutions towards the design and implementation of next-generation broadband wireless networks. In this context, various novel technologies have been introduced, such as millimeter wave (mmWave) transmission, massive multiple input multiple output (MIMO) systems, and non-orthogonal multiple access (NOMA) schemes in order to support the vision of fifth generation (5G) wireless cellular networks. The introduction of these technologies, however, is inextricably connected with a holistic redesign of the current transceiver structures, as well as the network architecture reconfiguration. To this end, ultra-dense network deployment along with distributed massive MIMO technologies and intermediate relay nodes have been proposed, among others, in order to ensure an improved quality of services to all mobile users. In the same framework, the design and evaluation of novel antenna configurations able to support wideband applications is of utmost importance for 5G context support. Furthermore, in order to design reliable 5G systems, the channel characterization in these frequencies and in the complex propagation environments cannot be ignored because it plays a significant role. In this Special Issue, fourteen papers are published, covering various aspects of novel antenna designs for broadband applications, propagation models at mmWave bands, the deployment of NOMA techniques, radio network planning for 5G networks, and multi-beam antenna technologies for 5G wireless communications