Active Radar Research Articles

ANTI-DRONE TECHNOLOGY

This work provides an overview of the growing use of drones in both civilian and military domains, highlighting the associated risks to public safety and privacy. It discusses the development of counter-drone systems to mitigate these risks, focusing on detection, tracking, classification, and neutralization technologies. Various sensors such as passive radar, acoustic sensors, electro-optical and infrared sensors, radiofrequency analyzers, active radar, and LiDAR are detailed, along with algorithms for data fusion. Mitigation strategies include soft kill methods like spoofing and jamming, as well as hard kill approaches such as projectiles and directed energy weapons. Keywords: counter-UAS; drone threat; unmanned aircraft system; malicious drone

Devising a method for detecting an aerial object by radar with an additional channel of passive reception

The object of this paper is the process of detecting an aerial object by a radar with active and passive reception channels. The main hypothesis of the study assumed that the introduction of an additional channel of passive reception would increase the conditional probability of correct detection at a fixed value of the conditional probability of false alarms. When detecting an aerial object, it was considered that the signals from aerial object represent a reflected signal after being emitted by the active radar channel elemitted own radio signals. A radar with active and passive reception channels assumes the presence of two channels. The active location channel provides reception of signals reflected from an aerial object, their processing and detection according to the Neumann-Pearson criterion. The passive location channel functions according to the principle of panoramic spectral analysis based on windowed Fourier transforms. The information combining device is intended for the compatible combining of information from active and passive channels of radar reception. At the output of the passive location channel, an output signal is formed, and the coordinates of the aerial object are measured. To ensure the functioning of the radar with active and passive reception channels, it is necessary to ensure the time synchronization of the reception channels. The quality of detection of aerial objects by radar with active and passive signal reception channels was evaluated. The quality indicator defines the conditional probability of correct detection. The dependences of the conditional probability of correct detection are given for a radar with only an active reception channel and a radar with active and passive reception channels. It was established that the introduction of an additional channel of passive reception to the radar increases the conditional probability of correct detection by an average of (20–40) %, depending on the signal-to-noise ratio.

5G‐based passive radar on a moving platform—Detection and imaging

AbstractIn recent times, the development of radar systems for automotive applications has gathered significant interest due to the increasing necessity of vehicle situational awareness for new active protection systems and the intensive development of higher autonomous level driving solutions. Therefore, the number of active radars in automotive applications is growing, causing spectrum sharing and interference between radars operating in the same band. Alternative solutions without dedicated electromagnetic transmissions, such as joint communication and radar systems, or even no transmission at all, such as passive radars, have emerged in recent years and are promising solutions to help mitigate the interference problem. A passive automotive radar based on 5G communication signals is proposed as an alternative to active radars to provide situational awareness. The data downlink transmissions provided by an operative 5G base station were combined with a dual‐channel passive radar (PR) system deployed on a moving platform to provide moving target detection and radar imaging of the vehicle's surroundings. The outcomes show a possibility of commensal utilisation of the new telecommunication standard for automotive radar applications. The idea of mounting the PR receiver on a moving platform was tested using simulated and real‐life data, which shows great potential for joining the new radio (NR) with sensing capabilities using PR. The theory, numerical experiments, and measurement results are dealt with a cooperative 5G base station and PR demonstrator.

Automatic Speckle Noise Reduction in SAR Imagery Using Optimized Kernel Support Vector Machine

Speckle noise (SN) is one of the major types of noise that frequently occurs in different coherent imaging systems such as medical imaging, Synthetic Aperture Radar (SAR) and active Radar images. SAR is a powerful imaging technology that generates fine-resolution images and monitors the earth’s surface in order to identify its physical properties. The satellite images captured by SAR are mainly affected by SN, which reduces the quality of images and complicates the image representation. Therefore, removing SN from SAR images is one of the major challenges and needs significant attention. The proposed study introduces an optimal Machine Learning (ML) classifier named Kernel Support Vector Machine-Improved Aquila Optimization (KSVM-IAO) for reducing SN in SAR images. This study uses a two-step process called filtering and enhanced despeckling to minimize the consequence of speckle suppression. In the first step, different imaging filters, namely Improved Lee Filter (ILF), Improved Frost Filter (IFF), Improved Kuan Filter (IKF) and Improved Boxcar Filter (IBF), are utilized to remove the SN in SAR images. Next, the denoised image is fed to the second stage, which makes use of an optimized KSVM-IAO classifier to obtain an enhanced despeckle image. The hyperparameters of KSVM are tuned using the IAO algorithm, which reduces overfitting issues and increases accuracy. MATLAB is the simulation tool used for the analysis of SAR images. The simulation outcomes reveal that the proposed KSVM-IAO method obtained excellent SN removal while preserving the edges and fine details with low computational complexity.

Feasibility Study of Using 5G Signals for Illumination Purposes in Passive Radar

Feasibility Study of Using 5G Signals for Illumination Purposes in Passive Radar

Agricultural Application Prospect of Fully Polarimetric and Quantification S-Band SAR Subsystem in Chinese High-Resolution Aerial Remote Sensing System.

The synthetic aperture radar (SAR) is a type of active radar that can obtain polarization scattering information of ground objects, which is an important supplement to optical remote sensing. This paper designs a high-precision quantitative SAR system that combines radiation and polarization calibration processing to achieve a subtle perception of the changes in soil moisture and straw coverage. In Yushu, Jilin, we conducted the first S-band agricultural remote sensing application experiment. The backscattering coefficient was measured under different water content and straw coverage conditions, and the results showed that the backscattering coefficient increased by about 2 dB and 6 dB, respectively. We estimated that the soil water content increased by about 0.01 cm3/cm3, which was consistent with the theoretical analysis. The polarization scattering characteristics also showed significant differences under different straw coverage. The results indicated that S-band quantitative SAR had an excellent response ability to water content and straw coverage, which provided a technical basis for further radar agricultural applications in the future.

Multi-passive coherent location radar system for detection range and range-doppler resolution in Tarakan

The presence of many radio frequency illuminators in an area provides an opportunity to be used as a transmission source for a passive radar system called a passive coherent locator (PCL). Unlike the active radar, the passive radar provides advantages such as low cost without an active transmitter, potential for broad range measurements, portable in construction, anti-detectable by active radar or electronic counter measures (ECM), etc. Just like other areas where there are many PCL in Tarakan such as FM radio transmission (RRI), many base-stations (BTS) from 4G-LTE network, digital TV transmission, access-point (AP) from wireless fidelity (WiFi), and so on. This paper will present and analyze all of these PCLs which include predictions of performance and ambiguity function (AF). Performance prediction is related to range detection which provides information about target detection range, radar cross section, and range-velocity resolution. While AF analyzes the transmit waveform of all PCL which gives a limit of resolution to the range and Doppler of adjacent targets. The results of the evaluation and analysis of performance predictions show that FM radio transmission (RRI) has a range and velocity resolution of 1 km and 12 m/s, respectively and the detection range at a maximum SNR of 15 dB is around 4 km. While the results of the AF evaluation on the PCL obtained range and Doppler resolution of around 2.73 km and 500 Hz, respectively.

Research on radial velocity and airspace position calculations of target in airborne active radar simulation

The detection of the target in the airborne active radar simulation is simplified to the calculations of the radial velocity, the maximum detecting range of the airborne active radar corresponding to the RCS, and the airspace position of the target. However, the coordinate transformations related to the calculations of the radial velocity and the airspace position are usually bewildering due to the different referenced coordinate systems. This paper introduces the radial velocity and airspace position calculations of the target in the airborne active radar simulation to illuminate the transformation process containing the specific rotation matrices, suggesting the unifying transformation to the north-up-east (NUE) rectangular coordinate system of the aircraft for both the radial velocity calculation and airspace position calculation of the target.

On-orbit monitoring flying aircraft day and night based on SDGSAT-1 thermal infrared dataset

Aerial moving target detection is an important technology to ensure the safety of civil flight and airspace. Different from ground-based active radar and space-based visible imager, on-orbit thermal infrared sensor (TIS), which records the temperature difference between background and targets, is proved to be a stable means of monitoring the aircraft throughout the day. Limited by low spatial resolution and dataset scarcity, there are few existing the research of space-based aircraft detection based on TIS. In this paper, a new multi-model joint method to detect on-orbit flying aircrafts with only 1 × 1 to 2 × 2 pixels is proposed and validated. And the first three-band thermal infrared flying aircrafts dataset (TIFAD) with 30 m spacial resolution is produced from SDGSAT-1 thermal infrared images, including the analysis of its infrared feature. Since the point target cannot by distinguished by the shape, all samples are selected by an improved aircraft contrails detection algorithm based on progressive probabilistic Hough transform, from more than 325GB SDGSAT-1 TIS remote sensing images (RSIs). And training by TIFAD, state-of-the-art YOLOv8 algorithm is applied to more than 17,767 medium spatial resolution thermal infrared images, and the potential aircrafts (with contrails or non-contrails) in RSIs are effectively detected. Moreover, the giga floating point operations (GFLOPs) of detecting flying targets from RSIs with 300 km width range is only 8.9. This paper is believed to provide a technical support of detecting aircraft targets around the globe throughout the day, and supplement on-orbit flying targets dataset of TIS images.

A Deep Learning Data Fusion Model Using Sentinel-1/2, SoilGrids, SMAP, and GLDAS for Soil Moisture Retrieval

Abstract We develop a deep learning–based convolutional-regression model that estimates the volumetric soil moisture content in the top ∼5 cm of soil. Input predictors include Sentinel-1 (active radar) and Sentinel-2 (multispectral imagery), as well as geophysical variables from SoilGrids and modeled soil moisture fields from SMAP and GLDAS. The model was trained and evaluated on data from ∼1000 in situ sensors globally over the period 2015–21 and obtained an average per-sensor correlation of 0.707 and ubRMSE of 0.055 m3 m−3, and it can be used to produce a soil moisture map at a nominal 320-m resolution. These results are benchmarked against 14 other soil moisture evaluation research works at different locations, and an ablation study was used to identify important predictors. Significance Statement Soil moisture is a key variable in various agriculture and water management systems. Accurate and high-resolution estimates of soil moisture have multiple downstream benefits such as reduced water wastage by better understanding and managing the consumption of water, utilizing smarter irrigation methods and effective canal water management. We develop a deep learning–based model that estimates the volumetric soil moisture content in the top ∼5 cm of soil at a nominal 320-m resolution. Our results demonstrate that machine learning is a useful tool for fusing different modalities with ease, while producing high-resolution models that are not location specific. Future work could explore the possibility of using temporal input sources to further improve model performance.

Interference Analysis for UAV Radar Networks With Guard Zones Based on Stochastic Geometry

Due to the increasing number of aerial radars and joint communication/sensing technologies, interference from uncoordinated radars will limit the target detection and ranging performance in the future. In this paper, we investigate the interference behavior in an aerial radar network for sensing ground targets. We consider that the radars mounted on unmanned aerial vehicles (UAVs) that fly at a certain altitude are randomly distributed according to a two-dimensional homogeneous Poisson point process (HPPP), and that the propagation is modeled using a probabilistic line-of-sight (LoS) channel model. For such a sensing network, we derive the distribution of the radar interference using a stochastic geometry based analysis. In particular, when Swerling I model is considered for radar cross-section area (RCS) for the target, we derive the Laplace transform of the radar interference. To avoid a strong interference between neighboring radars, a guard zone is introduced within which the UAV radar transmission around the permitted active radar is inhibited. As the radar performance metric, we derive the successful ranging probability (SRP) of a given radar by exploiting the Laplace transform of radar interference. Using the analytic SRP, we show that we can optimize the radar network parameters such as the radius of the guard zone and the density of the active radars. In addition, we also discuss how the analytic SRP gives an insight into the spectrum utilization strategy for the UAV radar networks with the guard zones.

A Ku-Band GaN-on-Si MMIC Power Amplifier with an Asymmetrical Output Combiner.

In this paper, a microwave monolithic integrated circuit (MMIC) high-power amplifier (HPA) for Ku-band active radar applications based on gallium nitride on silicon (GaN-on-Si) is presented. The design is based on a three-stage architecture and was implemented using the D01GH technology provided by OMMIC foundry. Details on the architecture definition and design process to maximize delivered power are provided along with stability and thermal analyses. To optimize the amplifier performance, an asymmetry was included at the output combiner. Experimental results show that the HPA achieves a 39.5 dBm pulsed-mode output power, a peak linear gain of 23 dB, a drain efficiency of 27%, and good input/output matching in the 16-19 GHz frequency range. The chip area is 5 × 3.5 mm2 and for the measurements was mounted on a custom-made module. These results demonstrate that GaN-on-Si-based Solid-State Power Amplifiers (SSPAs) can be used for the implementation of Ku-band active radars.

Natural Intelligence as the Brain of Intelligent Systems

This article discusses the concept and applications of cognitive dynamic systems (CDS), which are a type of intelligent system inspired by the brain. There are two branches of CDS, one for linear and Gaussian environments (LGEs), such as cognitive radio and cognitive radar, and another one for non-Gaussian and nonlinear environments (NGNLEs), such as cyber processing in smart systems. Both branches use the same principle, called the perception action cycle (PAC), to make decisions. The focus of this review is on the applications of CDS, including cognitive radios, cognitive radar, cognitive control, cyber security, self-driving cars, and smart grids for LGEs. For NGNLEs, the article reviews the use of CDS in smart e-healthcare applications and software-defined optical communication systems (SDOCS), such as smart fiber optic links. The results of implementing CDS in these systems are very promising, with improved accuracy, performance, and lower computational costs. For example, CDS implementation in cognitive radars achieved a range estimation error that is as good as 0.47 (m) and a velocity estimation error of 3.30 (m/s), outperforming traditional active radars. Similarly, CDS implementation in smart fiber optic links improved the quality factor by 7 dB and the maximum achievable data rate by 43% compared to those of other mitigation techniques.

The Methods for Improving the Quality of Detection of Inconspicuous Aerial Objects Through the Use of External Radiation Sources

The article focuses on the methods for improving the quality of detection of inconspicuous aerial objects through the use of external radiation sources. It has been established that the existing methods for improving the quality of detection of airborne objects do not meet modern requirements for detection indicators. The energy potential of modern radars is limited. Therefore, the article proposes detection methods that combine active radar and nontraditional principles for detecting airborne objects. In the article, we will focus only on two main methods for improving the quality of detection of small airborne objects. This is the use of energy from digital television receivers (external radiation source) and the use of information from ADS-B receivers. Technically, this means introducing an additional receiving channel into the radar. The gain in the conditional probability of correct detection for bistatic signal reception (compared to monostatic) is due to the properties of the bistatic effective scattering surface. It is shown that with the additional use of digital television signals, the quality of detection of airborne objects is improved. It is shown that the additional use of information from the ADS-B receivers makes it possible to increase the accuracy of determining the coordinates of an air object up to 40-50%, depending on the parameters of the movement of an air object. The subject of advanced research is the development of methods for suppressing the penetrating signal when using digital television and the development of methods for detecting airborne objects not equipped with the ADS B system. Keywords— aerial object, detection, quality, third-party source, ADS-B, digital TV, radar

Highly Accurate Radar Cross-Section and Transfer Function Measurement of a Digital Calibration Transponder without Known Reference—Part I: Measurement and Results

Active Radar Calibrators (ARC), also called calibration transponders, are often used as reference targets for absolute radiometric calibration of radar systems due to their large achievable Radar Cross-Section (RCS). However, before using a transponder as a reference target, the hardware itself has to be calibrated. A novel method, called the three-transponder method, was proposed some years ago and allows for RCS calibration of digital transponders without using any RCS targets as reference. In this paper, this technique is further refined and applied to a setup utilizing only one digital transponder. The accurate measurement design is described and a novel, elaborated data processing scheme is developed to minimize remaining noise and clutter effects in the data. A comprehensive error analysis is presented in the second part of this paper.

Consensus based target tracking against deception jamming in distributed radar networks

AbstractIn this study, an anti‐deception jamming target tracking algorithm based on the data‐level fusion is proposed in a distributed radar network. First, the consensus covariance intersection (CCI) algorithm is proposed to improve tracking performance by introducing the consensus theory to the field of covariance intersection fusion. Second, unscented Kalman filter is utilised to implement the preprocessing of distributed filtering. Then, two distributed target discrimination schemes are developed for non‐collaborative and collaborative false targets respectively. For non‐collaborative false targets, according to the characteristics that estimated spatial locations of the false target from different radars are relatively scattered, a false target elimination method based on nearest neighbour algorithm is proposed. For collaborative false targets, after equipped with passive radars that are less vulnerable to interference, the consensus algorithm is introduced to convey the real target information to the unconnected active radars, thus achieving an effect of global anti‐deception jamming. Finally, the CCI algorithm is deployed for distributed fusion of physical target tracking, so as to improve the overall estimation performance.

Відновлення працездатності радіоелектронних пристроїв шляхом реінжинірингу

Domestic radio-electronics, which is still incorporated in many electronic devices, has practically exhausted its technical resource. The longer modernization is postponed and the radio-electronic equipment based on outdated elements remains in use, the more its efficiency declines and operating costs increase. This paper analyzes the problems of maintaining the operational efficiency of radio-electronics that has exhausted its technical resource and the production of its elemental base has been discontinued. The authors substantiate the approach to extending the life cycle of technical products by updating the target functions of modules and cells through reengineering. The reengineering was performed for the functional control system 4PK, which is part of the radar 5N86 (“Hen House”), which has been in operation since 1975. To check the possibility of preserving the existing operating principles, simulations of cells and modules on the new elemental base and existing modules were carried out using Tina-Ti software simulation tools (Texas Instruments), Electronics Workbench, Micro Cap. The results of the reengineering of the 2TM modules indicated the problem of choosing a new element base — they use negative logic, which complicates the using a series of modern elemental base, the vast majority of elements of which are designed on positive logic and positive supply voltage. In order not to disturb the power supply architecture of the active radar, a way was found to coordinate different levels. Testing the model showed a positive result, and a number of cells showed the possibility to build a universal cell using reconfigurable electronic microcircuits in its composition.

IMPLEMENTATION OF THE COINCIDENCE FREQUENCY METER ON FPGA

Means of measuring various parameters and technical characteristics of radio equipment have always occupied leading positions in science and technology. Without an accurate definition of the relevant values, it is impossible to build modern high-quality radio communication systems, radar, navigation ground and satellite systems. In ultrasound diagnostics, which are used in medicine, the speed of blood flow in vessels is studied by determining the frequency of the reflected signal. At the same time, it is necessary to use high-speed frequency measurement tools in systems with active sensors used in telecommunication networks based on Internet of Things technology. For example, in active radar, using the frequency of the reflected signal, it is possible to calculate not only the coordinates, but also the circular speed of the moving target. Modern research is aimed at improving the metrological and technical indicators of existing measuring devices, in particular at developing new methods for correcting the characteristics of the transformation of the measuring channel, which is their main component. At the same time, most digital frequency meters are built on the method of counting the number of pulses N with an unknown period Tx that arrive at the input of the device during a calibrated time interval. All this leads to an increase in measurement time and requires additional hardware costs for fast processing of measurement results. The coincidence method belongs to vernier methods and is promising for use when measuring the frequency of periodic signals. This paper points out the shortcomings of known methods of measuring the frequency of a periodic signal. On the basis of the well-known method of coincidence, a functional scheme of a 16-bit device for measuring frequency, which is implemented on the basis of a FPGA from Intel (Altera), has been developed. The developed coincidence frequency meter has a dynamic range of 96dB. Representation of time diagrams obtained in the Quartus Prime 18.0 automated design environment and confirming the operability of the developed functional scheme of the 16-bit device for frequency measurement by the coincidence method. An analytical dependence for determining the frequency of a periodic signal during frequency measurement by the coincidence method is presented.

A Controllable Suppression Jamming Method against SAR Based on Active Radar Transponder

A chirp-mismatch echo signal can be generated by exchanging the I and Q baseband signals of a received SAR signal. In this paper, the basic generation principles of a chirp-mismatch echo signal are analyzed. Then, a suppression jamming method with controllable jamming position and coverage area is proposed. This method firstly performs chirp-mismatch processing on the received SAR signals, then controls the range jamming coverage and center position through range shift-frequency modulation and time delay, and controls the azimuth jamming coverage and center position through motion modulation and azimuth shift-frequency modulation. Theoretical analysis and simulation results show that this method can effectively control the location and coverage of a jamming result without convolution modulation, and it is easy to implement in engineering. The simulation results verify the correctness of the theoretical model, which can provide a basis for the implementation and application of SAR jamming based on the active radar transponder.

Adaptive Tracking of High-Maneuvering Targets Based on Multi-Feature Fusion Trajectory Clustering: LPI's Purpose.

Since the passive sensor has the property that it does not radiate signals, the use of passive sensors for target tracking is beneficial to improve the low probability of intercept (LPI) performance of the combat platform. However, for the high-maneuvering targets, its motion mode is unknown in advance, so the passive target tracking algorithm using a fixed motion model or interactive multi-model cannot match the actual motion mode of the maneuvering target. In order to solve the problem of low tracking accuracy caused by the unknown motion model of high-maneuvering targets, this paper firstly proposes a state transition matrix update-based extended Kalman filter (STMU-EKF) passive tracking algorithm. In this algorithm, the multi-feature fusion-based trajectory clustering is proposed to estimate the target state, and the state transition matrix is updated according to the estimated value of the motion model and the observation value of multi-station passive sensors. On this basis, considering that only using passive sensors for target tracking cannot often meet the requirements of high target tracking accuracy, this paper introduces active radar for indirect radiation and proposes a multi-sensor collaborative management model based on trajectory clustering. The model performs the optimal allocation of active radar and passive sensors by judging the accumulated errors of the eigenvalue of the error covariance matrix and makes the decision to update the state transition matrix according to the magnitude of the fluctuation parameter of the error difference between the prediction value and the observation value. The simulation results verify that the proposed multi-sensor collaborative target tracking algorithm can effectively improve the high-maneuvering target tracking accuracy to satisfy the radar’s LPI performance.