Iet Radar Sonar and Navigation最新文献

{"title":"Deep Reinforcement Learning for Adaptive Search-Beam Scheduling in Missile-Borne AESA Radar Seekers Under Time-Constrained Terminal Engagements","authors":"Slobodan Pajic,&nbsp;Burak Tuysuz,&nbsp;Caglayan Yuksel,&nbsp;Gurcan Kirik","doi":"10.1049/rsn2.70203","DOIUrl":"https://doi.org/10.1049/rsn2.70203","url":null,"abstract":"<p>Modern interceptor missiles increasingly rely on active electronically scanned array (AESA) seekers because rapid electronic steering supports flexible resource allocation within short terminal engagement windows. Under rapidly changing terminal geometry, conventional scan policies can increase beam-pointing error, reduce SNR and lead to intermittent track loss. This work introduces a deep reinforcement learning (DRL) search-beam scheduling policy trained on high-fidelity 6-DOF missile–target trajectories under time-constrained terminal engagements. The agent observes recent beam history and target–sensor kinematics and selects search beams from a discrete azimuth–elevation grid derived from the seeker search volume. In this study, the policy controls only search-beam scheduling; confirm/track scheduling is fixed and evaluation uses ground-truth kinematics with the tracker bypassed to isolate search effects. Reward shaping emphasises rapid detection and sustained time-on-target while penalising drop and reacquisition events. Performance is compared against conventional heuristic scan patterns using beam-pointing error, average SNR, time-on-target, reacquisition delay, drop count and first-detection time. Results show shorter reacquisition delays and higher time-on-target relative to heuristic scan baselines under identical dwell and power budgets. Because the RL evaluation uses ground-truth kinematics and bypasses the tracker, these results should be interpreted as an upper-bound estimate of the value of adaptive search-beam scheduling.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Dual-Channel Virtual Leader GLMB Filter With Hybrid Adaptive Birth for Resolvable Group Target Tracking","authors":"Jiaqi Yao,&nbsp;Qinchen Wu,&nbsp;Jinping Sun,&nbsp;Yanping Wang","doi":"10.1049/rsn2.70207","DOIUrl":"https://doi.org/10.1049/rsn2.70207","url":null,"abstract":"<p>To address resolvable group target tracking (RGTT) in environments with unknown prior birth information, this paper proposes a dual-channel virtual leader generalised labelled multi-Bernoulli (DC-VL-GLMB) filter with hybrid adaptive birth. To reduce false births caused by conventional measurement-driven adaptive birth methods that neglect group spatial compactness and coordinated motion, a dual-channel hybrid adaptive birth method is developed. In Channel A, the robust batch group adaptive birth (RBG-AB) algorithm extracts candidate tracks within a sliding window and converts group trajectories into Bernoulli birth components. The state deduplication step removes components that duplicate existing tracks. In Channel B, the residual measurement adaptive birth (RM-AB) algorithm generates supplementary Bernoulli birth components from measurements that are neither used by Channel A nor associated with surviving tracks. Birth components from both channels are merged to form an adaptive labelled multi-Bernoulli (LMB) birth prior, yielding a dual-channel GLMB (DC-GLMB) filter. The virtual leader (VL) model is incorporated to construct the DC-VL-GLMB filter, and a fast implementation strategy based on maximum a posteriori (MAP) hypothesis extraction and global label mapping is developed to reduce computational complexity. Simulations and drone-swarm radar measurements show that the proposed filter suppresses false births, improves track continuity and achieves robust tracking.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70207","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multi-Scan Possibility GLMB Model for Multi-Target Tracking Under Epistemic Uncertainty","authors":"Keya Fu,&nbsp;Hai Zhu,&nbsp;Cheng Zhang,&nbsp;Ji Zhang,&nbsp;Chenghu Cao","doi":"10.1049/rsn2.70188","DOIUrl":"https://doi.org/10.1049/rsn2.70188","url":null,"abstract":"<p>This work addresses the difficult issue of tracking multiple targets in the presence of epistemic uncertainty. We propose a multiscan possibility-based generalised labelled multiBernoulli (GLMB) smoothing approach designed to prevent track fragmentation and switching when detection profiles are unknown and vary over time. By incorporating a labelled uncertainty finite set (UFS) derived from possibility theory into the multiscan GLMB framework, the estimation of multitarget states is enhanced, yielding a possibility-theoretic counterpart to the standard multiscan GLMB smoothing procedure. These multiscan possibility functions can effectively represent epistemic uncertainties that stem from limited knowledge of the detection profile. The prediction and update steps of these possibility functions are expressed using a Gaussian max-mixture (GMM), which simplifies the execution of the multiscan possibility GLMB recursion. Simulation outcomes indicate that, under epistemic uncertainty, the proposed multiscan possibility GLMB smoothing provides improved estimates of both multitarget trajectories and target cardinality, particularly in practical scenarios.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70188","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overview of SWALIS, KaRADOC and HOMARDS: A Suite of Airborne Radars to Support Satellite Earth Observation Missions. SWOT Calibration/Validation Campaign in South Rhine","authors":"Stéphane Méric,&nbsp;Jean-Claude Koumi,&nbsp;Erwan Rahault,&nbsp;Pottier Éric,&nbsp;Jordi Chinaud,&nbsp;Louis Marié,&nbsp;Guy Grunfelder,&nbsp;Cécile Leconte,&nbsp;Stéphane Avrillon,&nbsp;Mohamed Himdi,&nbsp;María García-Vigueras,&nbsp;Paul Leroy","doi":"10.1049/rsn2.70194","DOIUrl":"10.1049/rsn2.70194","url":null,"abstract":"<p>This paper presents the different airborne radar systems which are developed at IETR (Institut d’Électronique et des Technologies du numéRique). In close collaboration with CNES (Centre National des Études Spatiales) and IFREMER (Institut Français de Recherche pour l’Exploitation de la MER), IETR has been designing airborne radar sensors to support satellite missions, both in the upstream phase and in the calibration/validation phase. These sensors are both tested and became operational with the PIMA platform, an airborne platform managed by the University of Rennes. Thus, this paper describes the SWALIS, KaRADOC and HOMARDS radars and the corresponding satellite observation missions. In our case, these missions are especially dedicated to the oceans and continental waters management. Finally, the obtained results are presented in relation to the aims of these satellite missions.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70194","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148467003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recursive Radar Signal Deinterleaving by Semantic Segmentation Using Recurrent Neural Networks","authors":"Louis Lesieur,&nbsp;Jean-Marc Le Caillec,&nbsp;Abdelmalek Toumi,&nbsp;Ali Khenchaf,&nbsp;Vincent Guardia","doi":"10.1049/rsn2.70191","DOIUrl":"https://doi.org/10.1049/rsn2.70191","url":null,"abstract":"<p>We propose two methods for radar signal deinterleaving. They are recursive deinterleaving methods, consisting of extracting the waveforms one after another. The problem mostly comes down to pulse selection: One must find pulses corresponding to a waveform. The R-U segmentation method uses a neural network (NN) to segment the pulse vector in an observed scene. The R-W hybrid method aims to reproduce the behaviour of a human operator in the task of labelling pulses. It is a combination of two models, the first proposing a set of pulse selections by a cognitive approach, and the second being a NN estimating the relevance of each of these selections to choose the best one. Although they have a different role and do not belong to the same method, the two NNs have a similar architecture. In addition to these two methods, we propose lobe detection algorithms to include the pulse amplitude within the feature set that describes an observed radar waveform along its frequency, pulse width and direction of arrival. To train NNs, we designed a data augmentation process with waveforms derived from real-world recordings. We also defined metrics for the evaluation of emitter identification and pulse deinterleaving.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70191","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148466716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Precision Localisation of Coherent Emitters via Iterative SDF-DPD on Mobile Platforms","authors":"Shijie He,&nbsp;Bowen Ding,&nbsp;Dan Song,&nbsp;Wei Wang","doi":"10.1049/rsn2.70182","DOIUrl":"10.1049/rsn2.70182","url":null,"abstract":"<p>The proliferation of illegal radiation sources significantly threatens reliable communication and stable operation of industrial facilities. This paper addresses the simultaneous localisation of multiple unknown emitters using large-scale UAV-collected monitoring data. Conventional direct position determination (DPD) methods suffer from non-uniform observation errors and are highly sensitive to environmental variations. Additionally, most traditional subspace-based approaches require subarray-based spatial smoothing for source localisation. To overcome these limitations, this work proposes an iterative direct localisation algorithm. This algorithm does not require subarray-based spatial smoothing and works in both partially and fully coherent signal environments. It operates by iteratively removing coherent components from the reconstructed signal covariance matrix without requiring subarray-based spatial smoothing, thus preserving full array aperture. A key advantage of this approach is its larger effective aperture than those of the conventional subarray-based spatial smoothing methods, which significantly enhances localisation accuracy. Numerical simulations demonstrate its superiority, showing higher localisation accuracy and resolution than conventional two-step methods and subspace data fusion-based DPD approaches.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70182","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148381105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-Probability-Of-Intercept Point Beam Design for Frequency Diverse Array-Multiple-Input Multiple-Output Radio Detectors Based on Adaptive Weight-Deep Deterministic Policy Gradient Reinforcement Learning","authors":"Jinwei Jia,&nbsp;Min Gao,&nbsp;Yuying Liang,&nbsp;Yuanwei Yin,&nbsp;Zhuangzhi Han","doi":"10.1049/rsn2.70184","DOIUrl":"https://doi.org/10.1049/rsn2.70184","url":null,"abstract":"<p>Radio detectors are widely used in the aerospace field, but they are subject to numerous electronic interferences, especially information interference, which is commonly seen in increasingly complex electromagnetic environments in modern times. Thus, improving information interference resistance is key to ensuring the accurate detection and damage control for radio detectors in such complex electromagnetic environments. Given that jammers intercept the radio detector signal first and then forward the interference, this study focuses on the design of low-probability-of-intercept (LPI) point beams for the radio detector. We construct a new evaluation model to verify the spatial LPI performance. Frequency diverse array-multiple-input multiple-output (FDA-MIMO) beams are employed and key factors influencing beam convergence are determined. A novel FDA-MIMO LPI spot beam design technique based on the adaptive weight-deep deterministic policy gradient (AW-DDPG) algorithm is proposed. A two-stage adaptive weight multi-dimensional reward function is designed for the AW-DDPG algorithm, with the array element frequency offset as the optimization objective. Leveraging the Actor-Critic framework, the gradient ascent method is used to maximise the reward, thereby deriving the array element frequency offset with better beam convergence performance in the current environment. Meanwhile, the AW-DDPG algorithm applies to LPI point beam design across various radio detector fall angles, overcoming the technical bottleneck that the formula method for the array element frequency offset only applies when the radio detector's fall angle is close to vertical. Simulation shows that with the array element frequency offset optimised by the proposed AW-DDPG algorithm, the FDA-MIMO beam exhibits a half-power beam width of 1 m in the distance dimension and 9.9° in the angular dimension. The beam convergence and LPI performance with the proposed method are significantly better than other classical frequency offset calculation methods. Thus, the proposed algorithm represents a new method for array element frequency offset optimization and LPI point beam design, effectively improving the radio detector's LPI performance.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70184","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3-D Micro-Motion Parameters Estimation of Smoothly Precession Cone-Cylinder Targets Based on Monostatic Radar","authors":"Fu-Long Xu,&nbsp;Ying Luo,&nbsp;Hang Yuan,&nbsp;Zhi-hao Wang,&nbsp;Kai-ming Li","doi":"10.1049/rsn2.70181","DOIUrl":"https://doi.org/10.1049/rsn2.70181","url":null,"abstract":"<p>The 3-D micromotion characteristics of radar targets reflect the target's geometric structure and motion properties, which can provide important information for ballistic target recognition. The existing methods for extracting micromotion features of precession cone-cylinder targets based on micro-Doppler effect only estimate partial parameters, and extracting 3-D parameters requires a known precession angle. Therefore, this article proposes a method that a single radar was used for the first time to estimate the micromotion parameters and geometric information of a precession cone-cylinder target with unknown precession angle by utilising the relationship between the curves of each scattering point in high-resolution range profile (HRRP) and time–frequency diagram (TFD). An algorithm based on nonlinear least squares fitting is proposed to accurately determine the type of scattering points corresponding to each curve in HRRP and TFD on conical cylindrical targets. Furthermore, the simplified expressions for the angle between the radar line-of-sight (LOS) direction and the cone rotation axis are derived. By leveraging the sliding scattering characteristics of the cone-cylinder junction and bottom edge as well as the target's geometric relationships, the complexity of solving the micromotion equation is simplified. The matching pursuit algorithm is then employed to further extract the micromotion and geometrical parameters. The electromagnetic experiments have verified the effectiveness of the proposed method.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RadMoist: Physics-Guided Features and Hybrid Edge Inference for mmWave Soil-Moisture Sensing in IoT Systems","authors":"Zubair Sharif,&nbsp;Naveed Imran,&nbsp;Sana Hameed,&nbsp;Alina Abid,&nbsp;Muhammad Shahid","doi":"10.1049/rsn2.70173","DOIUrl":"https://doi.org/10.1049/rsn2.70173","url":null,"abstract":"<p>Reliable and fine-grained knowledge of near-surface soil moisture is a foundation for precision irrigation, drought forecasting and hydrological modelling. However, existing probes, such as TDR and gravimetric sampling, remain labour-intensive and sparse. This study presents RadMoist, a fully contactless framework that estimates volumetric water content with a single low-cost 77 GHz FMCW radar (TI IWR1443BOOST, 4 GHz sweep and 3.8 cm range resolution). Beyond conventional surface amplitude and time-of-flight (ToF), RadMoist introduces three physics-guided indices: Microangular backscatter slope (μABS) for angular roughness, phase coherence decorrelation index (PCDI) for subsecond stability and diffusion gradient index (DGI) for high-band attenuation, yielding a five-element feature vector. These cues contribute to a custom-designed novel Hybrid-MoistureNet, an ensemble that averages a 200-tree XGBoost regressor with a compact three-layer MLP, enabling sub-millisecond inference on edge CPUs. The system was evaluated on loam, sandy-loam and clay soils spanning 0%–40% volumetric water content. RadMoist achieved a mean absolute error of 6.9% VWC, improving on an amplitude + ToF baseline (9.8%) by 29% and matching laboratory TDR measurements within 2%. Performance remained stable under ± 8°C temperature drift and ± 10° sensor tilt demonstrating robustness to field conditions. Therefore, RadMoist offers a practical calibration-light alternative for dense real-time soil-moisture mapping in precision agriculture and environmental monitoring.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70173","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Implicit-to-Explicit Association Framework for Multi-Object Tracking in Radar Video Sequences","authors":"Wei Xiong,&nbsp;Zhan Kong,&nbsp;Yaqi Cui","doi":"10.1049/rsn2.70177","DOIUrl":"https://doi.org/10.1049/rsn2.70177","url":null,"abstract":"<p>Multi-object tracking (MOT) is a fundamental task in radar technology. Leveraging the visual attributes in radar video data provides an effective approach to enhance tracking robustness, particularly in long-term scenarios where maintaining track continuity is challenging. However, effectively utilising the visual features of targets in radar videos also faces many limitations, primarily due to inter-frame jitter in target positions and limited unstable nature of target appearances. To overcome these limitations, we propose a novel association framework for multi-object tracking in radar video sequences. This framework achieves robust tracking through an implicit-to-explicit association strategy: An implicit association neural network (IANN) first establishes implicit associations between detections across consecutive frames end-to-end while performing detection, which are subsequently transformed into explicit associations by an explicit association module. Experimental results on real radar video data demonstrate the framework's effectiveness and superior performance. The proposed method stablishes a new benchmark for future research in multi-object tracking for radar video sequences.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70177","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}