Radar Detection System Research Articles

Design of RADAR Detection System Management with MATLAB

Abstract: Radio detection and ranging, that is, RADAR is a radio wave technique to determine the range, altitude, direction of objects. The radar dish or antenna transmits pulses of radio waves or microwaves which bounces off any object in their path. It works by launching a short pulse at the ear audible frequency, after that microcontroller listens for echoes. The information about the distance to the object is given at the time elapsed during transmission to the echo reception. The object returns a tiny part of the wave’s energy to a dish or antenna which is usually located at same site as the transmitter. High tech radar systems are associated with digital signal processing and are capable of extracting useful information from very high noise levels.

Isolation Improvement in Reflectarray Antenna-Based FMCW Radar Systems.

This paper presents an optimization of reflectarray-based RF sensors for detecting UAV and human presence. Our previous human detection radar system adapted a center-fed reflectarray antenna to a commercially available radar system, successfully increasing the gains of the transmit (TX) and receive (RX) antennas by 21.18 dB and the range for detecting human targets 3.4 times. However, because the TX and RX antennas were placed in the focal point of the reflectarray, the TX signal reflected by the reflectarray was directly propagated into the RX antenna, causing desensitization or damage to the receiving circuit if high powers were used. To reduce this direct reflection, we propose a novel radar antenna configuration in which the TX and RX antennas are placed back-to-back with each other. In this configuration, the RX antenna does not directly face the reflectarray, thus direct path between the TX to RX through the reflectarray is removed. The results demonstrate that this approach achieves the optimum isolation level of 51.3 dB. With the reflectarray, the TX antenna gain increases to 30.6 dBi, but the RX antenna gain remains at 16 dBi since the RX antenna does not utilize the reflectarray. The TX and RX gain difference (14.6 dB) is a trade-off for good isolation and may be reduced by utilizing a high-gain receiver amplifier.

Using Virtual Reality for Training to Identify Cyber Threats in the Bridge of a Ship

Seventeen college ROTC Navy midshipmen were recruited for an 8-week course that met twice weekly for lectures and training to identify cyber security threats in a virtual reality (VR) application. This VR trainer, the Cybersecurity Virtual Reality Trainer (CyVR-T) is an immersive application of a U.S. Navy destroyer. During the training scenarios one of the three designated systems (Voyage Management System, Radar Detection System, and Automatic Identification System) was hacked, showing erroneous information for a ship in the vicinity. In addition to the role of Trainee in the CyVR-T, participants observed their peers, held discussions after each scenario, and played the role of instructor. The trained midshipmen showed significant improvement in knowledge and cyber threat performance compared to a control group. Improved performance was noticed early in the program. CyVR-T showed to be a great tool for identifying cyber threats and has potential to be beneficial in more complex situations.

Using Classify-While-Scan (CWS) Technology to Enhance Unmanned Air Traffic Management (UTM)

Drone detection radar systems have been verified for supporting unmanned air traffic management (UTM). Here, we propose the concept of classify while scan (CWS) technology to improve the detection performance of drone detection radar systems and then to enhance UTM application. The CWS recognizes the radar data of each radar cell in the radar beam using advanced automatic target recognition (ATR) algorithm and then integrates the recognized results into the tracking unit to obtain the real-time situational awareness results of the whole surveillance area. Real X-band radar data collected in a coastal environment demonstrate significant advancement in a powerful situational awareness scenario in which birds were chasing a ship to feed on fish. CWS technology turns a drone detection radar into a sense-and-alert planform that revolutionizes UTM systems by reducing the Detection Response Time (DRT) in the detection unit.

Experimental Study of Maritime Moving Target Detection Using Hitchhiking Bistatic Radar

Hitchhiking bistatic radar system takes the direct wave signal that is transmitted by the non-cooperative radar emitter as the reference to detect and analyze the target echo signal, so as to realize the positioning and tracking of the target. This radar system has the advantages of low cost and strong survivability. Aiming at the problem of passive radar to covert the detection of maritime targets, this paper develops a hitchhiking bistatic radar system for maritime target detection, which uses the shore-based radar as the non-cooperative radar emitter. By continuously collecting the direct wave and target echo data of the non-cooperative radar, the direct wave reference signal reconstruction, pulse compression, interference suppression and synchronization processing, non-coherent integration, MTI (moving target indication), clutter map processing, and adaptive CFAR (constant false alarm rate) detection are completed to obtain the azimuth, bistatic range, and Doppler frequency of the target, and finally realize the positioning of non-cooperative maritime targets. This paper first introduces and demonstrates the composition principle of the system, introduces the signal processing implementation method of the system in detail, and tests and analyzes the key algorithms. The experimental results show that the system can realize the passive coherent detection of maritime moving targets and locate multiple targets at the same time. The experiment obtains a very clear PPI (plane position indicator) display picture of the hitchhiking bistatic radar system, and the radar detection data of the experimental system is in good agreement with the AIS (automatic identification system) data.

Fast copula-based fusion of correlated decisions for distributed radar detection

Distributed sensor networks with multiple antenna arrays are widely utilized for radar detection systems. When observations of network nodes are correlated, an optimal copula-based fusion (termed CBF) rule is designed for correlated binary decisions under the Neyman–Pearson (NP) framework. However, the CBF rule needs to determine the weights of all decisions in combination. Therefore, the high computational complexity of the CBF rule is unavoidable as the number of nodes increases. In this paper, we propose a fast copula-based fusion (F-CBF) algorithm for a multi-node radar system. The correlation between node decisions is simplified at the fusion center (FC) by taking logarithms of the weighted sum of node decisions. Specifically, the node decisions are weighted by a constant associated with the number of nodes. Thus the proposed method does not need to exhaust the weights of all combinations. Simulation results demonstrate that the proposed algorithm can efficiently reduce computational complexity. The detection performance of the proposed F-CBF method is significantly better than the independent detection method, although it is slightly inferior to the CBF method.

Modeling of Cavities Detection in The Tree Stemsection Using Radar Vector Network Analyzer (VNA) Elaborating Radon Transform

Trees are one of the most useful plants for life on earth. However, trees can be harmful due to cavities in the stem sections. Rapid detection is needed to prevent several losses that may arise due to fallen trees. This research identified a hollow and non-hollow tree stem section of flamboyant tree with a sub-surface detection radar system. The sub surface detection radar system was modeled using a Vector Network Analyzer (VNA) connected to a Vivaldi antenna. VNA emitted electromagnetic waves to the tree stem section and subsequently propagated and penetrated hollow tree stem section. The propagation wave met the boundary plane between the wood and the cavity which reflected the electromagnetic waves. The reflected wave was caught by antenna and was display by the VNA as S-Parameter. This research used a Vivaldi antenna with a working frequency of 1 GHz – 10 GHz and a VNA with working frequency 300KHz - 8GHz. The difference in the amplitude of the signal could be seen from the results of cavity measurements made at one point. By implementing circular scanning method with inverse radon transformation, this research could identify a 19 cm diameter wood with a hole of 6 cm and 9.5 cm diameter filled with water, respectively. It was observed that the optimal detection was obtained by placing object between the antennas. This research has signified the application of radar modeled with VNA for detecting the cavities in tree stem section.

Programmable Manipulations of Terahertz Beams by Graphene-Based Metasurface With Both Amplitude and Phase Modulations

Terahertz metasurface with digital, programmable control recently gained considerable attention for its potential applications in high-speed imaging, nondestructive sensing, and wireless communication. With elaborate design, the metasurface can perform amplitude, phase, and polarization modulations of electromagnetic waves. Most digital programmable metasurfaces focus on only one of the three dimensions. Here, we propose a graphene-based THz metasurface with both phase and amplitude modulations, which consists of an artificially constructed metal-insulator-metal structure and two-dimensional graphene material. Each meta-atom of the metasurface is divided into two sub-atoms, and the two sub-atoms can reflect terahertz waves with a phase difference of 180°. Meanwhile, the amplitude of the sub-atom can be effectively modulated or even switched off by applying different gate voltages to the graphene. By independently controlling the amplitude response of the two sub-atoms, the whole meta-atom can dynamically control both amplitude and phase responses of the cross-polarization waves. By carefully designing the coding patterns, the digital metasurface can control both beam direction and intensity, which may lead to various advanced applications in beam shaping, radar detection systems, and high-quality holography.

OFDM-NOMA combined with LFM signal for W-band communication and radar detection simultaneously

In this Letter, an effective integrated waveform generation method where an orthogonal frequency division multiplexing (OFDM)-based non-orthogonal multiple access (NOMA) communication signal combined with a linear frequency modulation (LFM) radar signal is proposed and experimentally demonstrated in a W-band communication and radar detection system. The proposed method can generate communication and radar signals simultaneously. In addition, multiple user communication and multi-target radar detection can be realized. Furthermore, for the OFDM-NOMA signal, discrete Fourier transform (DFT) precoding is used to keep the optimal power ratio consistent on different subcarriers, thus, the communication performance can be effectively improved. The experimental results show that the distance estimation error is 1.2 cm for radar signals. Meanwhile, after transmission over 0.8-m free space, the total aggregate rate for two users with the OFDM-NOMA signal is 3.125 Gb/s under the bit error rate of 8.5 × 10-4.

Anti-UAV High-Performance Computing Early Warning Neural Network Based on PSO Algorithm

In order to effectively solve the problem that the radar detection system is difficult to detect the “low, small, slow” UAV, the high-performance computing early warning neural network is used to recognize the air UAV in real time and extract the target category and image space location information; the PSO algorithm is used to optimize the parameters of the anti-UAV to ensure that the anti-UAV not only relies on factors but also fully combines the dependence of the visual field factor to quickly obtain the optimal solution through analyzing the high-performance computing early warning neural network in this paper. This algorithm is used to initialize the anti-UAV resources and improve the global optimization capability of the algorithm proposed in this paper. Finally, the experimental results show that the proposed PSO algorithm has better high-performance computing early warning performance to meet the actual needs of network high-performance computing early-warning neural networks.

Research and Design of Radar System for Respiratory and Heartbeat Signal Detection

The respiratory and heartbeat signals can accurately reflect the health status of the tester, which is of great clinical significance. Compared with the traditional contact detection method, the non-contact radar detection method does not require the tester to wear any sensor equipment and will not cause any discomfort to the tester. The frequency modulated continuous wave (FMCW) radar has the characteristics of simple structure, high resolution, strong stability, and low transmission power and is used for the detection of respiratory and heartbeat signals. This paper designs a low-power, low-cost respiratory, and heartbeat signal detection system based on FMCW radar. In addition, the variational modal decomposition (VMD) method is used to separate respiration and heartbeat signals to obtain accurate respiration and heartbeat rates. The results show that the radar system for detecting respiratory and heartbeat signals has high detection accuracy.

PhysioChair: A Dual-Frequency Radar System for Noninvasive and Continuous Detection of Physiological Signatures

This paper presents PhysioChair which is a novel sensing technique integrated in smart chairs for noninvasive and continuous detection of multiple physiological signatures. A dual-frequency radar system is designed and integrated in the PhysioChair, including a 5.8 GHz single-antenna radar for chest movement detection and a 120 GHz miniaturized radar for pulse detection. The dual-frequency multi-radar sensing system is calibrated to ensure systematic synchronization. Besides the conventional vital signs such as respiration, heartbeat and pulse, this paper proposes techniques and approaches to make it possible for the PhysioChair to estimate additional physiological signatures including heart rate variability (HRV), pulse transit time (PTT), pulse wave velocity (PWV), and blood pressure (BP). Experiments have been launched in an office environment with Photoplethysmography (PPG) and digital sphygmomanometer as reference. The experimental results show a great performance of the proposed PhysioChair in detection of weak physiological signatures. Compared to the ground truth, the estimated physiological signatures such as HRV and BP have mean relative errors below 3%, and 6 out of 7 subjects have an over 90% probability of absolute errors less than 5mmHg. The results reveal the possibility for the PhysioChair to be employed outside the clinic, such as applications in the vast internet-of-things (IoT) and in-home health monitoring.

Study on Microwave Absorption Performance Enhancement of Metamaterial/Honeycomb Sandwich Composites in the Low Frequency Band.

With the rapid development of electronic technology and modern radar detection system, there is increasingly urgent demand for microwave absorbing composites working efficiently in the low frequency range (e.g., 1–2 GHz). In this work, a type of metamaterial/honeycomb sandwich composite (MHSC) was proposed and fabricated, which exhibited a light weight structure and excellent wave-absorbing performance in the low frequency band. The relationship between the wave-absorbing properties and the design parameters of the composite, such as the thickness of the wave-transmitting skin, the thickness and dielectric properties of the wave-absorbing honeycomb, was systematically investigated. The electromagnetic coupling interference between the honeycomb absorber and metamaterial resonator proved to be a crucial factor that affects synergistic wave-absorbing performance in the low-frequency band. Under the rational design, the incorporation of subwavelength-sized phase-gradient metamaterial units in the composite can significantly improve low-frequency wave-absorbing performance for greater than 5 dB (an increment larger than 100%); and the obtained MHSC exhibits averaged reflectivity (Ra) less than −10 dB in the low frequency band of 1–2 GHz as well as outstanding performance (Ra < −14.6 dB) over an extremely wide frequency range (1–18 GHz). The MHSC reported in this study could be a promising candidate for the key material in high-performance radar stealth and other related applications.

The use of UAV interceptors to increase the detection range of intruder drones

Various threats of terrorist attacks on the social infrastructure arise due to strengthening of terrorist organizations, both in the context of their coming to power in certain countries (Afghanistan), and their association with the drug business, which significantly increases the financing of terrorist structures, allowing them to acquire modern weapons. Unmanned aerial vehicles (UAVs) are cheap, readily available and capable of carrying containers of lethal agents, what make them a common means of terrorist attack. Effective protection of critical industrial facilities from UAV terrorist attacks is an important task for improving systems and means of electronic warfare against terrorism.&#x0D; This paper considers the possibility of detecting an UAV near a critically important industrial facility using small-sized radar stations (SRS) placed on board of UAV-interceptors. Typically, SRS are placed on board drones for radio mapping of the terrain, operational-tactical and reconnaissance combat missions, and rescue operations. The possibility of using SRS on board interceptor drones to detect intruder drones as an additional channel to a remote radar channel has not been considered anywhere before.&#x0D; The paper provides a review of existing small-sized radar stations (SRS) that can be used or are used on-board of UAVs, as well as a review of existing UAV-interceptors. It is shown that UAV-interceptors equipped with SRS can be used to fly around the area about a critical industrial facility, by analogy with overflights performed by multicopters around agricultural areas, with recharging in specially equipped places for this at different distances from the control center and from critical industrial facility.&#x0D; A method is proposed to increase the existing optical and acoustic channel for detecting an intruder drone by an order of magnitude, and the radar channel by 5 km, if not only small-sized radar, but also optoelectronic with the acoustic UAV detection system are installed on the UAV-interceptor with the integrated use of these channels with remote radar UAV detection system.

Simultaneous User Localization and Identification Using Leaky-Wave Antennas and Backscattering Communications

High-speed detection and identification of mobile terminals located in the vicinity of highly directive base stations is essential for future mm-wave communication systems. We propose a novel optoelectronic frequency modulated continuous wave (FMCW) radar system for detection, localization and identification of multiple mobile terminals. The simultaneous localization and identification of multiple mobile terminals is achieved by using frequency scanning mm-wave leaky-wave antennas (LWAs) and backscattering communications. LWAs provide RF-based beam steering for estimating the direction of arrival of the echoes using a FMCW radar signal. Additionally, the implementation of backscattering technology in the mobile terminals allows the identification of users. Hence, simultaneous user localization and identification without the use of any complicated radar signal post-processing algorithms is possible. Finally, the introduced modulated backscattering reflection shifts the signals of the targets at higher frequencies, which exhibit lower noise floor and thus have higher signal to noise ratio (SNR).

A Filterless Photonic Approach for DFS and AOA Measurement Using a Push-Pull DPol-MZM

We report a novel simple photonic approach for measuring the Doppler frequency shift (DFS) and the angle of arrival (AOA) of a microwave signal in a radar detection system. The echo signals combined with a reference signal are applied to a dual-polarization Mach-Zehnder modulator (DPol-MZM), and a low-frequency electrical signal is generated after beating between the two signals in a low-speed photodetector. The DFS without direction ambiguity can be calculated by the value of the low-frequency signal. A phase difference is introduced between two echo signals which are sent to two sub-MZMs of the DPol-MZM respectively. The AOA is determined by the peak power of the down-convert signals, and a simple calibration is used to remove the amplitude of the echo signals and the reference signal by switching the output polarization states of the system. Compared with previously reported works, the proposed method carries out a comprehensive and multifunction measurement system based on a filterless and simple structure. Experimental results demonstrate the DFS errors within ± 0.5 Hz for a 15 GHz echo signal with a frequency offset of ± 100 kHz, and AOA measurement errors are within ± 1° for a range of 16° – 82°

Airport Runway Foreign Object Debris Detection System Based on Arc-Scanning SAR Technology

Due to the small size of foreign object debris (FOD) and varied complex weather conditions, the detection of FOD on airport runways is a great challenge. Radar is an important method for detecting FOD targets. However, almost all the existing systems are based on real apertures, which have disadvantages such as low azimuth resolution and susceptibility to rain interference. Here, an innovative FOD detection radar system based on arc-scanning synthetic aperture radar (AS-SAR) technology, the AS-SAR based FOD detection system (AS-FODR), achieves omnidirectional coverage with a very high azimuth resolution and the suppression of flicker clutter, such as rain drops in severe weather. According to the radar imaging simulation of a scene under rainy conditions and the information processing analysis of field experiments, a prototype system was built, and an efficient data process flow was proposed. In short, a one centimeter FOD target was detected on the runway more than 250 m away, proving that the use of AS-FODR is feasible and effective.

Photonics-assisted joint high-speed communication and high-resolution radar detection system.

A photonics-aided dual-functional system that can simultaneously implement high-speed communication and high-resolution radar detection is proposed. In the proposed system, high-speed orthogonal frequency division multiplexing signals and broadband linear frequency modulated signals are simultaneously realized based on photonic heterodyning. Based on this system, a net rate of 46.55 Gbit/s and radar with a 15 GHz bandwidth in the W-band were achieved.

A concurrent X and K dual‐band low noise amplifier for a radar detection system

AbstractThis article presents a concurrent X‐ and K‐bands low noise amplifier (LNA) for a radar detection system. A dual‐band matching and direct current bias circuitry were configured using surface‐mount device lumped capacitors and distributed transmission lines for the compact size. The designed LNA has dual‐pass band operation and a notch between the X‐ and K‐bands. The proposed LNA was implemented in hybrid integrated circuit technique on the microwave substrate. The measurement has showed the gains of 18.6 and 22.4 dB and noise figures of 3.29 and 1.67 dB at 10.525 and 24.1 GHz, respectively.

Classification of Drones Using Edge-Enhanced Micro-Doppler Image Based on CNN

The development of advanced radar system for detection and classification of UAVs is an essential requirement for today’s societal security. Such intelligent system could able to analyze the received radar signal and extract relevant information by utilizing sophisticated algorithm. In this letter, the utilization of micro-Doppler signature (MDS) for classification of drones, using convolutional neural network (CNN) model has been presented. We have generated images of micro-Doppler signatures using W-band radar system and used it for classification purpose. In this work, phase stretch transform (PST) has been utilized for edge detection and enhancement of the micro-Doppler images, to generate the edge-enhanced micro-Doppler image (EMDI). The comparison based on classification performance of CNN with different input datasets shows that the EMDI based CNN model outperformed the micro-Doppler image (MDI) based model.