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As unmanned ground and aerial vehicles become more accessible and their usage covers a wider area of application, including for threatening purposes which can cause connected catastrophe, a surveillance system for the public places is being considered more essential to respond to those possible threats. We propose an inexpensive, lighter, safer, an...
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... cut-off frequency is 1.758 GHz which lower than the operating frequency of the system, which is 2.30 GHz to 2.40 GHz. The specifications of can-cantennas that we used in version zero radar are shown in Table 1. This system does not support real-time processing at this moment because no further computation is attached to the output of the system. ...Citations
... In [11], the authors presented a new system for detecting and tracking UAVs through a single camera mounted on various UAVs. This approach can detect and track small UAVs efficiently with limited computing resources. ...
... This approach can detect and track small UAVs efficiently with limited computing resources. Moreover, they propose a lighter, inexpensive, safer, and miniaturized radar system [11]. Different types of anomalies were accurately detected by the intrusion detection system proposed for drone communication networks in [12]. ...
Recently, the number of drones has increased, and drones' illegal and malicious use has become prevalent. The dangerous and wasteful effects are substantial, and the probability of attacks is very high. Therefore, an anomaly detection and protection system are needed. This paper aims to design and implement an intelligent anomaly detection system for the security of unmanned aerial vehicles (UAVs)/drones. The proposed system is heavily based on utilizing ICMetric technology to exploit low-level device features for detection. This technology extracts the accelerometer and gyroscope sensors' bias to create a unique number known as the ICMetric number. Hence, ICMetric numbers represent additional features integrated into the dataset used to detect drones. This study performs the classification using a deep neural network (DNN). The experimental results prove that the proposed system achieves high levels of detection and performance metrics.
... Tracking radars, which could include the search radar, provide high-accuracy location and frequent updates so that the weapon can engage the target with high precision. Surveillance radars are Doppler radars that can detect objects moving on the ground, such as synthetic aperture radars, moving target indicators, and low-probability-of-intercept radars [29]. ...
The deployment of a drone swarm from carrier aircraft can support critical operations in which target aircraft should be protected by ground-based radar detection. To be successful as a countermeasure, the drones that are involved in the swarm must be equipped with proper payload systems and the geometry among the swarm units must be well designed. This paper describes the development of a scaled drone swarm geometry that can electromagnetically obscure a target from radar detection. Different drone swarm configurations were analyzed to select a feasible solution to develop ground and in-flight tests. During the tests, a compact software radar was used to detect a target drone. Several ground tests were executed to characterize the radar echo response of the target drone installed on a wooden tripod. Different geometries of corner reflectors were tested on tripods to select the swarm geometry that better obscured the target drone. Flight tests were executed involving decoy drones equipped with a corner reflector and a target drone to validate the proposed drone swarm geometry. The presented design of a drone swarm geometry allowed us to characterize the scaled distances among the swarm units and between the swarm and the target that must be protected against a ground-based radar detection.
... Therefore, there is a serious need for innovative solutions which are more resistant to interference, with more reliable threat detection in the field of border protection. Standard existing solutions are, in most cases, based on the combination of a radar detector with video camera surveillance in the optical and thermal spectrum [3,4]. In addition, vibrational and seismic detectors and touch barriers can be added for systems that demand an even higher detection reliability [5]. ...
The goal of this paper is to design a broadband acoustic camera using micro-electromechanical system (MEMS) microphones. The paper describes how an optimization of the microphone array has been carried out. Furthermore, the final goal of the described optimization is that the gain in the desired direction and the attenuation of side lobes is maximized at a frequency up to 4 kHz.
Throughout the research, various shapes of microphone arrays and their directivity patterns have been considered and analyzed using newly developed algorithms implemented in Matlab. A hemisphere algorithm, genetic algorithm, and genetic square algorithm were used to find the optimal position and number of microphones placed on an acoustic camera. The proposed acoustic camera design uses a large number of microphones for high directional selectivity, while a field programmable gate array system on a chip (FPGA SoC) is selected as the processing element of the system. According to
the obtained results, three different acoustic camera prototypes were developed. This paper presents simulations of their characteristics, compares the obtained measurements, and discusses the positive and negative sides of each acoustic camera prototype.
... The evaluation of these subsystems demonstrates the benefits of integrating them into the robotic interaction system. The work in [7] proposes an inexpensive, lighter, safer, and smaller radar system than military-grade radar systems, while keeping reasonable capability for use in monitoring public places. They presented a compact and cost-effective mobile 2.4 GHz radar system for moving object detection. ...
For several decades, various sensors and sensing systems have been developed for smart cities and civil infrastructure systems [...].
... For comparison, a 10 GHz signal has a wavelength of 2.9 cm and a DJI Phantom 2 is 35x35x18 cm (LxWxH), including the propellers (DJI, n.d.). Park et al. (2020), was made using the detailed specifications for their self-made radar system. The AnyLogic model is given in access point (Cisco, 2009). ...
... Radar Model Based on Parameters ofPark et al. (2020) Using the data provided byPark et al., ...
Counter Unmanned Aerial System (CUAS) security systems have unrealistic
performance expectations hyped on marketing and idealistic testing environments.
By developing an agent-based model to simulate these systems, an average
performance metric can be obtained, thereby providing better representative values
of true system performance.
Due to high cost, excessive risk, and exponentially large parameter
possibilities, it is unrealistic to test a CUAS system for optimal performance in the
real world. Agent-based simulation can provide the necessary variability at a low
cost point and allow for numerous parametric possibilities to provide actionable
output from the CUAS system.
This study describes and documents the Simulation of CUAS Networks and
Sensors (SCANS) Framework in a novel attempt at developing a flexible modeling
framework for CUAS systems based on device parameters. The core of the
framework rests on sensor and communication device agents. These sensors,
including Acoustic, Radar, Passive Radio Frequency (RF), and Camera, use input
parameters, sensor specifications, and UAS specifications to calculate such values as
the sound pressure level, received signal strength, and maximum viewable distance.
The communication devices employ a nearest-neighbor routing protocol to pass
messages from the system which are then logged by a command and control agent.
This framework allows for the flexibility of modeling nearly any CUAS
system and is designed to be easily adjusted. The framework is capable of reporting
true positives, true negatives, and false negatives in terms of UAS detection. For
testing purposes, the SCANS Framework was deployed in AnyLogic and models
were developed based on existing, published, empirical studies of sensors and
detection UAS.
... The choice of the CNN was due to its low value of inference time and high accuracy. According to [52], the highest detection speed was achieved by a detector with the MobileNet [49] backbone network. MobileNetV2 is an improved version of MobileNet that significantly improves its accuracy [51]. ...
With the increasing number of drones, the danger of their illegal use has become relevant. This has necessitated the creation of automatic drone protection systems. One of the important tasks solved by these systems is the reliable detection of drones near guarded objects. This problem can be solved using various methods. From the point of view of the price–quality ratio, the use of video cameras for a drone detection is of great interest. However, drone detection using visual information is hampered by the large similarity of drones to other objects, such as birds or airplanes. In addition, drones can reach very high speeds, so detection should be done in real time. This paper addresses the problem of real-time drone detection with high accuracy. We divided the drone detection task into two separate tasks: the detection of moving objects and the classification of the detected object into drone, bird, and background. The moving object detection is based on background subtraction, while classification is performed using a convolutional neural network (CNN). The experimental results showed that the proposed approach can achieve an accuracy comparable to existing approaches at high processing speed. We also concluded that the main limitation of our detector is the dependence of its performance on the presence of a moving background.
Environment perception, as the essential functional-ity of advanced driving assistance system(ADAS) and autonomous driving(AD) system, should be designed to understand the surrounding environment accurately and efficiently. Automotive radar, as the only sensor has the ability to sense the range information in almost any weather conditions, with comparably low cost, is the key factor to meet such requirements of environment perception. In this paper, we go through every aspect required for designing the automotive radar based environment perception module in detail, summarize the most relevant papers published recently and from years before, and highlight the most significant technologies which provide the fundamental of architecture of environment perception system.
