Radar Tracking Research Articles

The Future of Radar Space Observation in Europe—Major Upgrade of the Tracking and Imaging Radar (TIRA)

The use of near-Earth space has grown dramatically during the last decades, resulting in thousands of active and inactive satellites and a huge amount of space debris. To observe and monitor the near-Earth space environment, radar systems play a major role as they can be operated at any time and under any weather conditions. The Tracking and Imaging Radar (TIRA) is one of the largest space observation radars in the world. It consists of a 34m Cassegrain antenna, a precise tracking radar, and a high-resolution imaging radar. Since the 1990s, TIRA contributes to the field of space domain awareness by tracking and imaging space objects and by monitoring the debris population. Due to new technologies, modern satellites become smaller, and satellite extensions become more compact. Thus, sensitive high-resolution space observation systems are needed to detect, track, and image these space objects. To fulfill these requirements, TIRA is undergoing a major upgrade. The current imaging radar in the Ku band will be replaced by a new radar with improved geometrical and radiometric resolution operating in the Ka band. Due to its wideband fully polarimetric capability, the new imaging radar will increase the analysis and characterization of space objects. In addition, the tracking radar in the L band is also being currently refurbished. Through its novel modular structure and open design, highly flexible radar modes and precise tracking concepts can be efficiently implemented for enhanced space domain awareness. The new TIRA system will mark the start of a new era for space observation with radar in Europe.

Deriving the Ionospheric Electric Field From the Bulk Motion of Radar Aurora in the E‐Region

AbstractIn the auroral E‐region strong electric fields can create an environment characterized by fast plasma drifts. These fields lead to strong Hall currents which trigger small‐scale plasma instabilities that evolve into turbulence. Radio waves transmitted by radars are scattered off of this turbulence, giving rise to the ‘radar aurora’. However, the Doppler shift from the scattered signal does not describe the F‐region plasma flow, the drift imposed by the magnetosphere. Instead, the radar aurora Doppler shift is typically limited by nonlinear processes to not exceed the local ion‐acoustic speed of the E‐region. This being stated, recent advances in radar interferometry enable the tracking of the bulk motion of the radar aurora, which can be quite different and is typically larger than the motion inferred from the Doppler shift retrieved from turbulence scatter. We argue that the bulk motion inferred from the radar aurora tracks the motion of turbulent source regions (provided by auroras). This allows us to retrieve the electric field responsible for the motion of field tubes involved in auroral particle precipitation, since the precipitating electrons must drift. Through a number of case studies, as well as a statistical analysis, we demonstrate that, as a result, the radar aurora bulk motion is closely associated with the high‐latitude convection electric field. We conclude that, while still in need of further refinement, the method of tracking structures in the radar aurora has the potential to provide reliable estimates of the ionospheric electric field that are consistent with nature.

Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method

Abstract. The grounding line position of glaciers and ice shelves is an essential observation for the study of the Earth's ice sheets. However, in some locations, such as the Antarctic Peninsula, where many grounding lines have not been mapped since the 1990s, remote sensing of grounding line position remains challenging. Here we present a tidal motion offset correlation (TMOC) method for measuring the grounding line position of tidewater glaciers and ice shelves, based on the correlation between tide amplitude and synthetic aperture radar offset tracking measurements. We apply this method to the Antarctic Peninsula Ice Sheet to automatically delineate a new grounding line position for 2019–2020, with near complete coverage along 9300 km of coastline, updating the 20-year-old record. A comparison of the TMOC grounding line to contemporaneous interferometrically measured grounding line position shows the method has a mean seaward offset compared to interferometry of 185 m and a standard deviation of 295 m. Our results show that over the last 24 years there has been grounding line retreat at a number of fast-flowing ice streams on the Antarctic Peninsula, with the most retreat concentrated in the north-eastern sector, where grounding lines have retreated following the collapse of ice shelves. We observe a maximum grounding line retreat since 1996 of 16.3 ± 0.5 km on Hektoria Glacier, with other notable glaciers retreating by 9.3 ± 0.5, 9.1 ± 0.5 and 3.6 ± 0.5 km. Our results document dynamic change on Antarctic Peninsula glaciers and show the importance of using an updated grounding line location to delineate the boundary between floating and grounded ice.

Adaptive interacting multiple model particle filter based on a dual-pattern bat algorithm for maneuvering target tracking

The interacting multiple model particle filter (IMM-PF) is a filtering method commonly used for nonlinear non-Gaussian radar systems. Its transfer probabilities are usually fixed and dependent on prior information. When tracking maneuvering targets, the IMM-PF may cause excessive tracking errors due to the model switching lag. In addition, the particle impoverishment caused by the resampling of the particle filter seriously affects the filtering accuracy. Therefore, the IMM-PF has difficulty meeting the accuracy and speed requirements of modern high-performance radar target tracking systems. To address these problems, an adaptive interacting multiple model particle filter based on the dual-pattern bat algorithm (ADIMM-DPBA-PF) is proposed for tracking maneuvering targets under nonlinear and non-Gaussian conditions. First, the adaptive model switching mechanism is established to adjust the transition probabilities using the model probability posterior information at consecutive times, improving the model switching efficiency. Second, a particle filter based on the dual-pattern bat algorithm (DPBA-PF) is proposed. The filter exploits global search and local search strategies to optimize the particles and intelligently move the particles to the high likelihood region. Finally, a particle filter based on the dual-pattern bat algorithm is used to form the adaptive interacting multiple model method. The experimental results show that the proposed algorithm has better comprehensive performance than the IMM-PF.

Lost in space and time: robust demography and enhanced resilience buffer adverse environmental effects in a highly isolated and sedentary pre-pleistocene landscape vertebrate

BackgroundFew animal populations have been studied under the framework of the OCBIL theory, which addresses the ecology and evolution of biodiversity on old climatically buffered infertile landscapes. Available genetic data challenge the low connectivity and high genetic differentiation predicted for isolated tepui-summit vertebrate communities, suggesting potential dispersal among summits. However, the OCBIL theory posits reduced dispersibility, enhanced resilience to habitat fragmentation and inbreeding due to small populations. We tested these hypotheses by conducting the first analytic evaluation of the spatial ecology and population biology of a tepui-summit vertebrate at multiple spatial scales.ResultsWe used harmonic radar tracking (100 individuals/448 points of contact) and capture-mark-recapture data (596 individuals captured/52 recaptured) to reveal the temporal niche, microhabitat use, population size, and dispersal abilities of the tepui-summit endemic toad Oreophrynella quelchii on Roraima-tepui. Abundance was determined using a closed population model incorporating sources of variation in capture probability. We tested the relative influence of biotic and abiotic variables on distances moved through model selection. Our data indicate that the population size of O. quelchii is remarkably large (ca. 12 million individuals), with strong seasonal demographic fluctuations. Ecology and observed limited spatial movements challenge the likelihood of active dispersal among tepui tops in this species. Our results are counter to those predicted by the available genetic data but support two hypotheses of the OCBIL theory: reduced dispersibility and enhanced resilience. However, they do not support the expectation of a small refugial population size.ConclusionWe postulate that the insular, hostile tepui-summit environment tends to produce robust demographic populations, likely to buffer stochastic adverse environmental effects, rather than diversity, as observed in much younger post-Pleistocene Neotropical landscapes. Our results draw attention to the value of faunal studies using an OCBIL framework to better understand the ecology and evolution of this unique biota worldwide.

Shedding light with harmonic radar: Unveiling the hidden impacts of streetlights on moth flight behavior

One of the most dramatic changes occurring on our planet is the ever-increasing extensive use of artificial light at night, which drastically altered the environment to which nocturnal animals are adapted. Such light pollution has been identified as a driver in the dramatic insect decline of the past years. One nocturnal species group experiencing marked declines are moths, which play a key role in food webs and ecosystem services such as plant pollination. Moths can be easily monitored within the illuminated area of a streetlight, where they typically exhibit disoriented behavior. Yet, little is known about their behavior beyond the illuminated area. Harmonic radar tracking enabled us to close this knowledge gap. We found a significant change in flight behavior beyond the illuminated area of a streetlight. A detailed analysis of the recorded trajectories revealed a barrier effect of streetlights on lappet moths whenever the moon was not available as a natural celestial cue. Furthermore, streetlights increased the tortuosity of flights for both hawk moths and lappet moths. Surprisingly, we had to reject our fundamental hypothesis that most individuals would fly toward a streetlight. Instead, this was true for only 4% of the tested individuals, indicating that the impact of light pollution might be more severe than assumed to date. Our results provide experimental evidence for the fragmentation of landscapes by streetlights and demonstrate that light pollution affects movement patterns of moths beyond what was previously assumed, potentially affecting their reproductive success and hampering a vital ecosystem service.

Data Fusion Network-Based Time–Frequency Enhancement Algorithm for Doppler Through-Wall Radar Tracking

Data Fusion Network-Based Time–Frequency Enhancement Algorithm for Doppler Through-Wall Radar Tracking

Personalized federated learning for improving radar based precipitation nowcasting on heterogeneous areas

AbstractThe increasing generation of data in different areas of life, such as the environment, highlights the need to explore new techniques for processing and exploiting data for useful purposes. In this context, artificial intelligence techniques, especially through deep learning models, are key tools to be used on the large amount of data that can be obtained, for example, from weather radars. In many cases, the information collected by these radars is not open, or belongs to different institutions, thus needing to deal with the distributed nature of this data. In this work, the applicability of a personalized federated learning architecture, which has been called adapFL, on distributed weather radar images is addressed. To this end, given a single available radar covering 400 km in diameter, the captured images are divided in such a way that they are disjointly distributed into four different federated clients. The results obtained with adapFL are analyzed in each zone, as well as in a central area covering part of the surface of each of the previously distributed areas. The ultimate goal of this work is to study the generalization capability of this type of learning technique for its extrapolation to use cases in which a representative number of radars is available, whose data can not be centralized due to technical, legal or administrative concerns. The results of this preliminary study indicate that the performance obtained in each zone with the adapFL approach allows improving the results of the federated learning approach, the individual deep learning models and the classical Continuity Tracking Radar Echoes by Correlation approach.

3D detection of flying insects from a millimeter-wave radar imaging system

Studying the movement patterns of small flying insects, such as pollinators, is a major challenge in biology. Here we introduce an original approach to track the 3D motion of flying insects using a millimeter-wave radar imaging system. 3D images are obtained from the beam scanning of a Frequency-Modulated Continuous-Wave and Single-Input Multiple-Output radar operating at 77 GHz. We derive the flight trajectory of insects and mitigate the electromagnetic clutter from the 3D radar images. To illustrate our approach, 3D flights of isolated bumblebees are radar tracked in a limited volume during 5.2 minutes with a time resolution of 60ms. The radar tracks are compared with video recordings for validation purpose. The tracking volume of an insect using a single radar is estimated at 5.3m3, and we show that the volume can be tripled when three radar imaging systems are deployed. Finally, we discuss how our new radar-based technique can be extended to track a broad diversity of small flying animals at different spatial scales and simultaneously in the lab and in the field.

Power Allocation Scheme for Multi-Static Radar to Stably Track Self-Defense Jammers

Due to suppression jamming by jammers, the signal-to-interference-plus-noise ratio (SINR) during tracking tasks is significantly reduced, thereby decreasing the target detection probability of radar systems. This may result in the interruption of the target track. To address this issue, we propose a multi-static radar power allocation algorithm that enhances the detection and tracking performance of multiple radars in relation to their targets by optimizing power resource allocation. Initially, the echo signal model and measurement model of multi-static radar are formulated, followed by the derivation of the Bayesian Cramér–Rao lower bound (BCRLB). The multi-objective optimization method is utilized to establish the objective function for joint tracking and detection, with dynamic adjustment of the weight coefficient to balance the tracking and detection performance of multiple radars. This ensures the reliability and anti-jamming capability of the multi-static radar system. Simulation results indicate that the proposed algorithm can prevent the interruption of jammer tracking and maintain robust tracking performance.

Exploring Markov Decision Processes: A Comprehensive Survey of Optimization Applications and Techniques

Markov decision process is a dynamic programming algorithm that can be used to solve an optimization problem. It was used in applications like robotics, radar tracking, medical treatments, and decision-making. In the existing literature, the researcher only targets a few applications area of MDP. However, this work surveyed the Markov decision process’s application in various regions for solving optimization problems. In a survey, we compared optimization techniques based on MDP. We performed a comparative analysis of past work of other researchers in the last few years based on a few parameters. These parameters are focused on the proposed problem, the proposed methodology for solving an optimization problem, and the results and outcomes of the optimization technique in solving a specific problem. Reinforcement learning is an emerging machine learning domain based on the Markov decision process. In this work, we conclude that the MDP-based approach is most widely used when deciding on the current state in some environments to move to the next state.

A Wide-Band Circularly Polarized Euler Spiral Dielectric Resonator Antenna for X/Ku-Band Applications

This paper puts forward a low-profile, circularly polarized (CP), wideband Euler’s Spiral Dielectric Resonator Antenna (ES-DRA) having a footprint of 0.68 λ × 0.68 λ × 0.096 λ and operating in X and Ku-band (8.26–14 GHz). A cross-shaped aperture is used to couple the power from 50 Ω walking stick-shaped microstrip line to the ES-DRA. The antenna generates circular polarization radiation in the frequency band 10.47–11.69 GHz and has a peak gain of 8.1 dBic. There is a good matching between radiation and total efficiency in the operating band. The antenna can be put to use in weather mapping and detecting, long-range tracking radar and missile applications. The prototype has been fabricated and tested for experimental validation and the results are in good coherence with the simulated ones.

Overview of High-Power and Wideband Radar Technology Development at MIT Lincoln Laboratory

This paper summarizes over 60 years of radar system development at MIT Lincoln Laboratory, from early research on satellite tracking and planetary radar to the present ability to perform the centimeter-resolution imaging of resident space objects and future plans to extend this capability to geosynchronous range.

Research on a Sound Source Localization Method for UAV Detection Based on Improved Empirical Mode Decomposition.

To address the challenge of accurately locating unmanned aerial vehicles (UAVs) in situations where radar tracking is not feasible and visual observation is difficult, this paper proposes an innovative acoustic source localization method based on improved Empirical Mode Decomposition (EMD) within an adaptive frequency window. In this study, the collected flight signals of UAVs undergo smoothing filtering. Additionally, Robust Empirical Mode Decomposition (REMD) is applied to decompose the signals into Intrinsic Mode Function (IMF) components for spectrum analysis. We introduce a sliding frequency window with adjustable bandwidth, which is automatically determined using a Grey Wolf Optimizer (GWO) with a sliding index. This window is used to lock and extract specific frequencies from the IMFs. Based on predefined criteria, the extracted IMF components are reconstructed, and trigger signal times are analyzed and recorded from these reconstructed IMFs. The time differences between sensor receptions are then calculated. Furthermore, this study introduces the Chan-Taylor localization algorithm based on weighted least squares. This advanced algorithm takes sensor time delay parameters as input and solves a set of nonlinear equations to determine the target's location. Simulations and real-world signal tests are used to validate the robustness and performance of the proposed method. The results indicate that the localization error remains below 5% within a 15 m × 15 m measurement area. This provides an efficient and real-time method for detecting the location of small UAVs.

Chaff jamming recognition and suppression based on semi‐realistic dataset and Pre‐Decluttering Dual‐Stage UNet

AbstractCountermeasures for chaff jamming have drawn great attention in the field of radar target detection and tracking. Current approaches for chaff jamming recognition and suppression exhibit limitations in practical effect, generalisation ability, and hybrid jamming handling. To address the above problems, the authors first transform the traditional 1D signal processing problem into a 2D semantic segmentation task and then solve it from the perspective of the dataset construction and algorithm design. For the dataset construction, the authors use both measured and simulated data to synthesise a more realistic labelled dataset (semi‐realistic dataset), which is also with good diversity due to its adjustable chaff interference background. For the algorithm design, the authors propose a Pre‐Decluttering Dual‐Stage UNet (D2UNet) to recognise and suppress chaff jamming in two stages successively, where the former provides prior attention masks for the latter. To further improve the performance of D2UNet, the authors also design a multi‐stage loss function to achieve progressive training. Extensive experimental results demonstrate that D2UNet delivers remarkable recognition accuracy (99.305%) and suppression performance (41.326 dB peak signal‐to‐jamming ratio, 0.9952 structure similarity index measure) on the semi‐realistic dataset. Its practical effect is further verified on measured data.

An ultrathin wideband linear-to-circular polarization conversion metasurface for X-band applications

A specialized ultrathin metasurface has been developed to transform a linearly polarized incident wave into a reflected wave with circular polarization across a wide range of frequencies. The unit cell consists of two modified L-shaped structures that convert the incident linearly polarized wave to a circularly polarized wave. The axial ratio bandwidth of the reflected wave ranges from 8.19 to 11.08 GHz, exhibiting a fractional bandwidth of 30%. The dimensions of the unit cell are 7 × 7 ×1.6mm3 (0.225λ×0.225λ×0.051λ) where λ represents the center frequency within the operational frequency band. The proposed design not only provides a wide bandwidth but also is ultrathin as the dimensions are much less than λ/12. Finally, the proposed metasurface is fabricated and tested. The results obtained are in significant concurrence with the simulated results. Hence, it can be used in various applications, including implementation in multi-beam antennas, beam-scanning antennas, wireless systems, weather monitoring, radar tracking, and navigation systems.

Range-Doppler-Time Tensor Processing for Deep-Space Satellite Characterization Using Narrowband Radar

There is growing demand for the high-fidelity characterization of satellites in Geosynchronous Earth Orbit (GEO) to support Space Domain Awareness (SDA). This is particularly true for newly launched satellites, where it is necessary for satellite providers to ascertain whether components have deployed properly. Conventional wideband radar systems are capable of imaging satellites provided that (i) they have sufficient power aperture and bandwidth, and (ii) they observe enough target aspect change to generate a resolved image. While wideband radars are used routinely for characterizing satellites in Low-Earth Orbit (LEO), powerful radars with sensitivity sufficient for large GEO ranges (36,000 km or greater) are lacking. Thus, researchers often rely on more widely available high-power narrowband tracking radars for GEO characterization. In this paper, we present a novel range-Doppler-time (RDT) tensor processing technique for GEO characterization with narrowband radar. This technique encapsulates the strengths of previously proposed methods for narrowband-radar characterization at GEO, providing a generalized approach that can be applied in a variety of settings. The technique generates fully resolved 2D images of rotating GEO satellites in low-bandwidth scenarios. In cases where aspect change is limited, the technique provides detailed Doppler information for enhanced satellite status monitoring. This work presents a comprehensive quantitative analysis of the technique that considers the impact of key parameters on characterization performance. Simulated radar data, and radar data collected in a compact range on a scaled satellite model, are used to evaluate the technique.

A Method to Track Moving Targets Using a Doppler Radar Based on Converted State Kalman Filtering

Strong nonlinearity between Doppler measurement and target motion in Doppler radar target tracking leads to the inadequate utilization of measurement information and limited tracking accuracy. We solved this problem by combining converted state Kalman filtering and the Interacting Multiple Model. This maneuvering target tracking method is suitable for Doppler measurement. First, we converted the target motion in the Cartesian coordinate to the polar coordinate. Then, we expanded the measurement equation to include Doppler measurement, making target motion linearly related to the Doppler radar observation vectors and allowing efficient utilization of measurement information. Next, we used unscented transformation to calculate the statistical characteristics of the process noise in the polar coordinate. This process helps to reduce the noise error caused by the coordinate system transformation in the original converted state Kalman filter. Finally, the system effectively tracks targets that may perform maneuvers with unknown motion during actual tracking. Using the converted state Kalman filter with Doppler measurement as a sub-filter, an Interacting Multiple Model tracking method can be constructed to adjust the model probabilities without going through nonlinear transformation. Simulation results show that the technique can achieve effective target tracking in Doppler measurement application scenarios and has higher tracking accuracy in non-maneuvering and maneuvering scenarios.

Planar slotted waveguide antenna array for monopulse radar

In monopulse radar, along with mirror and lens antennas, slotted waveguide antenna arrays (SWA) are often used, especially in those cases when it is required to have a flat non-protruding shape and compact dimensions. The design and manufacturing of such antennas have specialties associated with the use of non-standard feeding systems of radiating waveguides, which are considered in this paper as the example of creation of a flat SWA intended for use in a monopulse search and tracking radar. The aim of the article is calculating and modeling a slotted waveguide antenna array based on a hollow metal waveguide with a given level of side lobes and main lobe width of the radiation pattern. The developed SWA contains a radiating and feeding part. The radiating part, with 24 linear resonant waveguide-slot antennas with longitudinal slots on the wide wall of the waveguide, is divided into two subarrays to realize the monopulse mode. Each subarray is fed from the feeding waveguide through slanted slots cut in the wide wall of the waveguide. The antenna design calculation has been carried out in the MathCad, and the modeling has been performed in CAD Ansys HFSS. The energy method has been used to calculate the coordinates of the longitudinal slots on the wide wall of the radiating waveguide as well as the inclined slots on the wide wall of the feeding one. The calculated radiation patterns of the developed antenna array in the E- and H-planes in sum and difference modes have been shown. The paper outlines the methodology for designing a monopulse antenna system using a SWA. The system forms a beam directed perpendicular to the antenna plane. During the design process, the slotted waveguide antenna array based on a hollow waveguide has been modeled and researched to obtain the required characteristics specified in the technical requirements. The proposed approach can be applied to practical antenna design for monopulse radars.

Debiased Linear Measurement Matrix-Based Linear Sequential Filtering for Radar Tracking

Debiased Linear Measurement Matrix-Based Linear Sequential Filtering for Radar Tracking